A clustering approach to identify candidates to housekeeping genes based on rna-seq data Edian F. Franco Dener Maués Ronnie Cley de Oliveira Alves Luís Carlos Guimarães Vasco Azevedo Artur Silva Preetam Ghosh Jefferson Magalhaes De Morais Rommel Thiago Jucá Ramos Housekeeping gene Gene Computational biology Housekeeping Gene expression In silico RNA-Seq Biology Computer science Genetics Transcriptome 2020 en info:eu-repo/semantics/conferenceObject proceedings-article https://doi.org/10.1007/978-3-030-46417-2_8 Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics urn:issn:0302-9743 urn:issn:1611-3349 Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2020, p. 83-95 info:eu-repo/semantics/closedAccess closedAccess Q3 Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal One-Class SVM to Identify Candidates to Reference Genes Based on the Augment of RNA-seq Data with Generative Adversarial Networks Edian F. Franco Edwin J. Rueda Rommel Thiago Jucá Ramos Orlando Belo Jefferson Magalhaes De Morais Computer science Support vector machine RNA-Seq Generative adversarial network In silico Artificial intelligence Classifier (UML) Gene Machine learning Data mining Deep learning Biology Genetics Gene expression Transcriptome 2020 en info:eu-repo/semantics/conferenceObject proceedings-article https://doi.org/10.1007/978-3-030-58799-4_51 Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics urn:issn:0302-9743 urn:issn:1611-3349 Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2020, p. 704-717 info:eu-repo/semantics/closedAccess closedAccess Q3 Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Computational Genomics Edian F. Franco Fabrício Almeida Araújo Ana Lídia Q. Cavalcante Marcus de Barros Braga Rodrigo Bentes Kato Rommel Thiago Jucá Ramos Computational genomics Computer science Genome Genomics DNA sequencing Computational biology Volume (thermodynamics) Data mining Biology Gene Genetics 2021 en info:eu-repo/semantics/bookPart book-chapter https://doi.org/10.1007/978-981-33-6191-1_11 Advances in Bioinformatics Advances in Bioinformatics urn:issn:1687-8027 urn:issn:1687-8035 Advances in Bioinformatics, 2021, p. 213-241 info:eu-repo/semantics/closedAccess closedAccess Q2 Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Deep Learning applied to computational biology and agricultural sciences Renato Hidaka Torres Fabrício Almeida Araújo Edian Franklin Franco De Los Santos Debmalya Barh Rommel Thiago Jucá Ramos Marcus de Barros Braga Deep learning Artificial intelligence Computer science Field (mathematics) Data science Convolutional neural network Machine learning Artificial neural network Mathematics 2022 en info:eu-repo/semantics/bookPart book-chapter https://doi.org/10.1016/b978-0-323-89778-5.00006-4 Bioinformatics in Agriculture Bioinformatics in Agriculture Bioinformatics in Agriculture, 2022, p. 589-618 info:eu-repo/semantics/closedAccess closedAccess Zero hunger Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Antimicrobial Susceptibility Profiles of Bacteria Isolated from The Ozama River in Santo Domingo, Dominican Republic Yaset Rodriguez Edian F. Franco Roberto Bonnelly Ana Lídia Q. Cavalcante Camila Del Rosario Zorrilla Victor V. Calderón Albert Duarte Rafael Baraúna Rommel T. Ramos Luis E. Rodriguez de Francisco Luis O. Maroto Omar P. Perdomo antimicrobial resistance multidrug resistance environmental water contamination Stenotrophomonas maltophilia river water bacteria antibiotic resistance genes anthropogenic pollution nosocomial pathogens antibiotic use regulation Santo Domingo ABSTRACT The dissemination of antimicrobial-resistant bacteria in environmental waters is an emerging concern in medical and industrial settings. In the present study, our research team analyzed superficial water samples from 3 different collection sites along the Ozama River, the most important river in the Dominican metropolitan area. Seventy-six isolates were obtained from culture media previously enriched with cefotaxime and imipenem and subsequently identified by MALDI-ToF. Our isolates spanned 12 genera of bacteria; over 30% were of clinical relevance, and 43% exhibited a phenotype classified as multi-drug resistance. The most frequent species identified as Stenotrophomonas maltophilia (n = 33), an emerging nosocomial pathogen. This study constitutes part of the initiative to understand the profiles of the perils of multi-drug resistance in metropolitan areas of the Dominican Republic: a nation with poor antibiotic use regulation. IMPORTANCE Nearly two billion people are sourcing their water from low-quality reservoirs world-wide. These reservoirs consist of contaminated waters with anthropogenic pollutants such as antibiotics, disinfectants, and other substances used to treat water in societies with scarce resources and unregulated industries. Furthermore, the exposure of these antibiotics to potable water reservoirs promotes the increase of clinically relevant bacteria with antibiotic-resistance capabilities, becoming a public health crisis. Therefore, treating patients with infectious diseases and providing prophylactic measures against infection-associated conditions (such as post-surgical recovery) has become progressively more difficult. Based on this evidence frame, it is of considerable importance to analyze the bacterial profiles of rivers that fall prey to anthropogenic contamination, as these investigations on antibiotic resistance will, of course, benefit the life of humans. 2022 en info:eu-repo/semantics/preprint preprint https://doi.org/10.1101/2022.09.19.508624 [] [] [], 2022 info:eu-repo/semantics/openAccess openAccess cc-by-nd https://www.biorxiv.org/content/biorxiv/early/2022/09/22/2022.09.19.508624.full.pdf Good health and well-being Clean water and sanitation Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Democratising Artificial Intelligence for Pandemic Preparedness and Global Governance in Latin American and Caribbean Countries Edian F. Franco Ulisses Nunes da Rocha Robson Parmezan Bonidia Jude Dzevela Kong Mariana Dauhajre Claudio José Struchiner Guilherme Tegoni Goedert Peter Florian Stadler Danilo Sipoli Sanches Troy Day Márcia C. Castro John Edmunds Manuel Emilio Colome Hidalgo Demian Arturo Herrera Morban César Ugarte‐Gil Patricia Espinoza‐Lopez Gabriel Carrasco‐Escobar André de Souza Carvalho Preparedness Latin Americans Global health Pandemic Public health Corporate governance Global governance Multinational corporation Global network Infectious diseases continue to pose a significant global health challenge, necessitating innovative approaches for predicting outbreaks, detecting variants, conducting contact tracing, discovering new drugs and managing misinformation. Artificial intelligence (AI) has significantly supported work in these areas, particularly during the COVID-19 pandemic. However, the benefits of AI must be equitably distributed, and its use must be responsible and inclusive. As various nations implement AI regulations, the global nature of AI necessitates international collaboration to establish ethical guidelines and governance frameworks. In response to these needs, the Global South AI for Pandemic & Epidemic Preparedness & Response Network (AI4PEP) is leading a multinational effort across 16 countries to strengthen public health systems through responsible, Southern-led AI solutions. This opinion piece highlights AI4PEP's initiatives in Latin America and the Caribbean (LAC), examining the region's AI governance models and the challenges they present. By lowering barriers to AI adoption and fostering equitable access to AI-driven public health innovations, our network empowers researchers, healthcare professionals and policymakers in LAC to harness AI for infectious disease preparedness and response, ultimately improving health outcomes in low- and middle-income countries. 2025 en info:eu-repo/semantics/article journal-article https://doi.org/10.1111/1751-7915.70256 Microbial Biotechnology Microbial Biotechnology urn:issn:1751-7915 urn:issn:1751-7907 Microbial Biotechnology, 2025, vol. 18, n. 10, p. e70256 info:eu-repo/semantics/openAccess openAccess cc-by https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/1751-7915.70256 Q1 doaj pubmed Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Metagenomic Bioprospecting of Bioremediation‐Related Genes in Amazonian Aquatic Ecosystems 2026 info:eu-repo/semantics/article journal-article https://doi.org/10.1111/1758-2229.70435 Environmental Microbiology Reports Environmental Microbiology Reports Environmental Microbiology Reports, 2026 Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal CrAssphage distribution analysis in an Amazonian river based on metagenomic sequencing data and georeferencing Edian F. Franco David Tavares Martins Oscar Victor Cardenas Alegria Carlos Willian Dias Dantas Paulo Rógenes Monteiro Pontes Rosane Barbosa Lopes Cavalcante Rommel Thiago Jucá Ramos Amazonian Metagenomics Amazon rainforest Biology Population Ecology Abundance (ecology) Viruses are the most abundant biological entities in all ecosystems of the world. Their ubiquity makes them suitable candidates for indicating fecal contamination in rivers. Recently, a group of Bacteroidetes bacteriophages named CrAssphages, which are highly abundant, sensitive, and specific to human feces, were studied as potential viral biomarkers for human fecal pollution in water bodies. In this study, we evaluated the presence, diversity, and abundance of viruses with a focus on crAssphages via metagenomic analysis in an Amazonian river and conducted correlation analyses on the basis of physicochemical and georeferencing data. Several significant differences in viral alpha diversity indexes were observed among the sample points, suggesting an accumulation of viral organisms in the river mouth, whereas beta diversity analysis revealed a significant divergence between replicates of the most downstream point (IT4) when compared to the rest of the samples, possibly due to increased human impact at this point. In terms of the presence of crAssphage, the analysis identified 61 crAssphage contigs distributed along the Itacaiúnas River. Moreover, our analysis revealed significant correlations between 19 crAssphage contigs and human population density, substantiating the use of these viruses as possible markers for human fecal pollution in the Itacaiúnas River. This study is the first to assess the presence of crAssphages in an Amazonian river, with results suggesting the potential use of these viruses as markers for human fecal pollution in the Amazon. IMPORTANCE: The Amazon biome is one of the most diverse ecosystems in the world and contains the most vast river network; however, the continuous advance of urban centers toward aquatic bodies exacerbates the discharge of pollutants into these water bodies. Fecal contamination contributes significantly to water pollution, and the application of an improved fecal indicator is essential for evaluating water quality. In this study, we evaluated the presence, diversity, and abundance of crAssphages in an Amazonian river and performed correlation analysis on the basis of physicochemical and georeferencing data to test whether crAssphages are viable fecal pollution markers. Our analysis revealed both the presence of crAssphages and their correlation with physicochemical data and showed significant correlations between the relative abundance of crAssphages and human density. These results suggest the potential use of these viruses as markers for water quality assessment in Amazonian rivers. 2025 en info:eu-repo/semantics/article journal-article https://doi.org/10.1128/aem.01470-24 Applied and Environmental Microbiology Applied and Environmental Microbiology urn:issn:0099-2240 urn:issn:1070-6291 Applied and Environmental Microbiology, 2025, vol. 91, n. 5, p. e0147024 info:eu-repo/semantics/openAccess openAccess cc-by https://doi.org/10.1128/aem.01470-24 Q1 doaj pubmed Clean water and sanitation Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Draft genome of a multi-drug, metal and biocide-resistant strain of Klebsiella variicola isolated from the Yaque del Sur River in the Dominican Republic Edian Franco Franklin de Los Santos David Tavares Martins Oscar Victor Cardenas Alegria Thais Azevedo Cardoso Antônio Márcio Gomes Martins-Júnior Luiz Orlando Maroto-Martin Rommel Thiago Jucá Ramos Tainã Figueiredo Cardoso Klebsiella variicola draft genome sequence antimicrobial resistance metal resistance biocide resistance multidrug resistance genes strain YSP4_INTEC was isolated from a Dominican Republic River and had its genome sequenced (size: 5,611,899 bp and GC content: 57.19%). The genomic analysis identified various genes involved in plant colonization mechanisms, plus a wide array of multi-drug, biocide, and multi-metal resistance genes. 2025 en info:eu-repo/semantics/article journal-article https://doi.org/10.1128/mra.00700-25 Microbiology Resource Announcements Microbiology Resource Announcements urn:issn:2576-098X Microbiology Resource Announcements, 2025, vol. 14, n. 11, p. e0070025 info:eu-repo/semantics/openAccess openAccess cc-by https://doi.org/10.1128/mra.00700-25 Q3 pubmed Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Microbial Profiling and Biosafety Assessment of a Sargassum-Based Liquid Biofertilizer Using 16S rRNA Metagenomics Yaset Rodríguez-Rodríguez Ulises Javier Jáuregui-Haza Edian F. Franco Ashley Marie Mejía Disla Máximo Elías Reynoso Ortega Gustavo Gandini Pamela Tejada-Tejada Miguel Ángel Guevara Carlos Willian Dias Dantas Rommel T. Ramos Sargassum liquid biofertilizer seaweed biomass microbial diversity biosafety assessment 16S rRNA metagenomics Staphylococcus bacilli Firmicutes Proteobacteria heavy metals integrated nutrient management tropical agriculture Sargassum seaweed is increasingly abundant in the Caribbean, creating ecological disruption but also providing biomass for agricultural inputs. This study compares the microbial diversity and safety of a Sargassum ‐based liquid biofertilizer (SBLB‐INTEC) with those of a conventional product (LB‐BANELINO) using 16S rRNA amplicon sequencing, rather than culture‐dependent methods. Both formulations contained key nutrients (K, Ca, and Mg) and low levels of heavy metals. They harbored dense but relatively simple bacterial communities dominated by Firmicutes, particularly Bacilli, with Proteobacteria and other phyla at lower abundances. Staphylococcus (Staphylococcaceae) was highly abundant in both products, while SBLB‐INTEC showed a somewhat more balanced community, including Delftia and other Comamonadaceae. Shannon diversity tended to be higher in SBLB‐INTEC, but differences in alpha‐ and beta‐diversity between formulations were not statistically significant. Because 16S data cannot distinguish viable from nonviable cells or resolve strain‐level pathogenicity, these results do not prove the absence of pathogens; instead, they provide a genus‐level baseline to guide targeted culture, qPCR, and functional assays. Overall, the combination of a favorable chemical profile and microbial groups commonly associated with nutrient cycling and plant‐associated functions suggests that SBLB‐INTEC could become a valuable component of integrated nutrient management in tropical agriculture, offering hope for a more sustainable future pending confirmatory plant‐response and biosafety studies. We recommend integrating these microbial data into a national biofertilizer monitoring framework, combining metagenomic surveys with targeted qPCR and resistance gene screening. 2026 en info:eu-repo/semantics/article journal-article https://doi.org/10.1155/ijm/3219583 International Journal of Microbiology International Journal of Microbiology urn:issn:1687-918X urn:issn:1687-9198 International Journal of Microbiology, 2026, vol. 2026, n. 1, p. 3219583 info:eu-repo/semantics/openAccess openAccess cc-by https://doi.org/10.1155/ijm/3219583 Q1 doaj pubmed Zero hunger Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal SATIN: a micro and mini satellite mining tool of total genome and coding regions with analysis of perfect repeats polymorphism in coding regions Carlos Willian Dias Dantas Sebastião Rodrigues da Costa Neto Sandy Ingrid Aguiar Alves Kenny da Costa Pinheiro Edian Franklin Franco De Los Santos Rommel Thiago Jucá Ramos Microsatellite Tandem repeat Biology Genome Genetics Computational biology Computer science Gene Allele BACKGROUND: Tandem repeats are specific sequences in genomic DNA repeated in tandem that are present in all organisms. Among the subcategories of TRs we have Satellite repeats, that is divided into macrosatellites, minisatellites, and microsatellites, being the last two of specific interest because they can identify polymorphisms between organisms due to their instability. Currently, most mining tools focus on Simple Sequence Repeats (SSR) mining, and only a few can identify SSRs in the coding regions. RESULTS: We developed a microsatellite mining software called SATIN (Micro and Mini SATellite IdentificatioN tool) based on a new sliding window algorithm written in C and Python. It represents a new approach to SSR mining by addressing the limitations of existing tools, particularly in coding region SSR mining. SATIN is available at https://github.com/labgm/SATIN.git . It was shown to be the second fastest for perfect and compound SSR mining. It can identify SSRs from coding regions plus SSRs with motif sizes bigger than 6. Besides the SSR mining, SATIN can also analyze SSRs polymorphism on coding-regions from pre-determined groups, and identify SSRs differentially abundant among them on a per-gene basis. To validate, we analyzed SSRs from two groups of Escherichia coli (K12 and O157) and compared the results with 5 known SSRs from coding regions. SATIN identified all 5 SSRs from 237 genes with at least one SSR on it. CONCLUSIONS: The SATIN is a novel microsatellite search software that utilizes an innovative sliding window technique based on a numerical list for repeat region search to identify perfect, and composite SSRs while generating comprehensible and analyzable outputs. It is a tool capable of using files in fasta or GenBank format as input for microsatellite mining, also being able to identify SSRs present in coding regions for GenBank files. In conclusion, we expect SATIN to help identify potential SSRs to be used as genetic markers. 2024 en info:eu-repo/semantics/article journal-article https://doi.org/10.1186/s12859-024-05842-2 BMC Bioinformatics BMC Bioinformatics urn:issn:1471-2105 BMC Bioinformatics, 2024, vol. 25, n. 1, p. 217 info:eu-repo/semantics/openAccess openAccess cc-by https://link.springer.com/content/pdf/10.1186/s12859-024-05842-2.pdf Q1 doaj pubmed Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Evaluation of the Genomic Basis for Alzheimer’s and Parkinson’s Diseases Edian F. Franco Pratip Rana Yug Rao Khajamoinuddin Syed Debmalya Barh Vasco Azevedo Rommel Thiago Jucá Ramos Preetam Ghosh Genome-wide association study Disease Biology Parkinson's disease Genetic association Gene Genetics Computational biology Single-nucleotide polymorphism Medicine Pathology Genotype Alzheimer's disease (AD) and Parkinson's disease (PD) are the most common neurodegenerative disorders related to aging. Though several risk factors are shared between these two diseases, the exact relationship between these two diseases is still unknown. In this paper, we analyzed how these diseases relate to each other from a genomics viewpoint. Using an extensive literature search, we accumulated the list of genes from the major genome-wide association (GWAS) studies. However, we found only one gene (HLA-DRB5) reported in these GWAS studies that are common between AD and PD. We also listed all the miRNAs that have been previously reported for AD and PD. Here we found 15 different miRNAs that were reported in both diseases. In order to get better insights, we predicted the gene coexpression network for both AD and PD. Network analysis on these networks show six clusters of genes related to AD and four clusters of genes related to PD. 2019 en info:eu-repo/semantics/other other https://doi.org/10.20944/preprints201906.0178.v1 Preprints.org Preprints.org Preprints.org, 2019 info:eu-repo/semantics/openAccess openAccess cc-by https://www.preprints.org/manuscript/201906.0178/v1/download Good health and well-being Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Co-Expression Networks for Causal Gene Identification Based on RNA-seq Data of Corynebacterium Pseudotuberculosis Edian F. Franco Pratip Rana Ana Lídia Q. Cavalcante Artur Silva Adriana Ribeiro Carneiro Vasco Azevedo Preetam Ghosh Rommel Thiago Jucá Ramos Corynebacterium pseudotuberculosis Caseous lymphadenitis Gene Biology Yersinia pseudotuberculosis Computational biology RNA-Seq Identification (biology) Genome Genetics Gene regulatory network Virulence Gene expression Transcriptome Bacteria Microbiology Corynebacterium pseudotuberculosis is a Gram-positive bacterium that causes caseous lymphadenitis, a disease that predominantly affects sheep, goat, cattle, buffalo, and horses, but has also been recognized in other animals. This bacterium generates a severe economic impact on countries producing meat. Gene expression studies using RNA-seq is one of the most commonly used techniques to perform transcriptional experiments. Computational analysis on such data through reverse-engineering algorithms leads to a better understanding of the genome-wide complexity of gene interactomes, enabling the identification of genes having the most significant functions inferred by the activated stress response pathways. In this study, we identified the influential or causal genes from four RNA-seq data-sets from different stress conditions (high iron, low iron, acid, osmosis, and PH) in C. pseudotuberculosis, using a consensus-based network inference algorithm called miRsig and identified the causal genes in the network using the miRinfluence tool, which is based on the influence diffusion model. We found that over 50\% of the genes identified as influential have some essential cellular functions in the genomes. In the strains analyzed, most of the causal genes have crucial roles or participate in processes associated with response to extracellular stresses, pathogenicity, membrane components, and essential genes. This research brings new insight into the understanding of virulence and infection by C. pseudotuberculosis. 2020 en info:eu-repo/semantics/other research-technique https://doi.org/10.20944/preprints202006.0144.v1 Reprint Reprint Reprint, 2020 info:eu-repo/semantics/openAccess openAccess cc-by https://doi.org/10.20944/preprints202006.0144.v1 Partnerships for the goals Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Comparison of Two Bacterial Characterization Techniques for the Genomic Analysis of Aquatic Environments Edian F. Franco Roberto Bonelly Víctor V. Calderón Confesora Pinales Irene Ortiz Argenys Ovando Willy Lara Santo E. Mateo-Perez Oscar Victor Cardenas Alegria Rommel Thiago Jucá Ramos Luis O. Maroto genomic DNA Mass spectrometry Chromatography Extraction (chemistry) Computational biology DNA extraction Biology Environmental chemistry Analytical Chemistry (journal) Environmental science DNA Chemistry Genetics Polymerase chain reaction Gene Our research team compared the performance of matrix-assisted laser desorption/ionization followed by a time of flight (MALDI-TOF) mass spectrometry and genomic DNA extraction followed by sequencing, assembly and alignment for phylogenetic assessment. We performed these comparisons to determine our methodology’s overall efficacy and accuracy for environmental bacteria. In addition, we collected samples from various contaminated rivers in the Dominican Republic. For both methods, we analyzed these results and reported the main differences between each method. 2022 en info:eu-repo/semantics/preprint preprint https://doi.org/10.20944/preprints202209.0098.v1 Preprints.org Preprints.org Preprints.org, 2022 info:eu-repo/semantics/openAccess openAccess cc-by https://www.preprints.org/manuscript/202209.0098/v1/download Life below water Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Comparison of Two Bacterial Characterization Techniques for the Genomic Analysis of River Microbiome Yaset Rodríguez-Rodríguez Edian Franklin Franco De Los Santos Roberto Bonnelly Victor V. Calderon Irene Ortiz Argenys Ovando Confesora Pinales Willy Lara Santo Emilio Mateo-Perez Oscar Victor Cardenas-Alegría Rommel Thiago Jucá Ramos Luis Orlando Maroto Martín MALDI-TOF mass spectrometry whole genome sequencing bacterial identification antibiotic resistance resource-constrained environments We compared the performance of matrix-assisted laser desorption/ionization followed by a time of flight (MALDI-TOF) mass spectrometry and genomic DNA extraction followed by sequencing, assembly, and alignment for phylogenetic assessment (Genomics method). We collected the samples from four contaminated rivers in the Dominican Republic and analyzed MALDI-TOF efficacy and accuracy for identifying bacteria in the samples. We evaluated the results for both methods (MALDI-TOF and Genomics) and reported a similarity percentage between each method's results. The MALDI-TOF method had a 72.41\% of coincidence with the Genomics method. This could have been sequence contamination found in the Genomics method. When it was later filtered, the result's coincidence rate went up to 90\%. 2023 en info:eu-repo/semantics/preprint preprint https://doi.org/10.20944/preprints202307.0696.v1 Preprints.org Preprints.org Preprints.org, 2023 info:eu-repo/semantics/openAccess openAccess cc-by https://doi.org/10.20944/preprints202307.0696.v1 doaj Clean water and sanitation Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Bacterial Foodborne Diseases in Central America and the Caribbean: A Systematic Review Edian Franklin Franco De Los Santos Nicole Severino Claudia Reyes Yumeris Fernandez Vasco Ariston de Carvalho Azevedo Luis Enrique Rodríguez De Francisco Rommel Thiago Ramos Luis Orlando Maroto-Martín foodborne pathogens Salmonella Escherichia coli Campylobacter poultry contamination egg contamination vegetable contamination foodborne disease surveillance risk factors whole genome sequencing Central America and the Caribbean Foodborne diseases (FBD) represent a significant public health concern, particularly in regions like Central America and the Caribbean (CAC), where surveillance gaps due to lack of resources, knowledge and technical abilities, hinder control over outbreaks. This review investigates the bacterial pathogens responsible for FBD, their prevalence, challenges in management, and strategies for prevention. A systematic review was conducted following PRISMA guidelines, focusing on bacterial FBD in CAC from 2000 to 2024. PubMed and Google Scholar were used as primary databases, supported by other sources to identify relevant studies. Inclusion criteria encompassed studies focusing on bacterial pathogens, prevalence, risk factors, and surveillance practices. Out of 509 studies initially identified, 35 met the inclusion criteria. The most prevalent pathogens were Salmonella spp., Escherichia coli, Campylobacter spp., and Aliarcobacter spp., with contamination often associated with poultry, eggs, and vegetables. Key challenges included inadequate surveillance systems, limited resources, and inconsistent reporting practices. Greater investment in pathogen monitoring, documentation, and education, along with the use of technologies like whole-genome sequencing (WGS), is crucial. Institutional and governmental funding is vital to improve surveillance and strengthen risk analysis across the region. 2024 en info:eu-repo/semantics/preprint preprint https://doi.org/10.20944/preprints202411.1874.v1 Preprints.org Preprints.org Preprints.org, 2024 info:eu-repo/semantics/openAccess openAccess cc-by https://doi.org/10.20944/preprints202411.1874.v1 doaj Good health and well-being Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Bacterial Foodborne Diseases in Central America and the Caribbean: A Systematic Review Edian Franklin Franco De Los Santos Nicole Severino Claudia Reyes Yumeris Fernandez Vasco Ariston de Carvalho Azevedo Luis Enrique Rodríguez De Francisco Rommel Thiago Ramos Luis Orlando Maroto-Martín foodborne pathogens Salmonella Escherichia coli Campylobacter poultry contamination egg contamination vegetable contamination foodborne disease surveillance risk factors whole genome sequencing Central America and the Caribbean Foodborne diseases (FBD) represent a significant public health concern, particularly in regions like Central America and the Caribbean (CAC), where surveillance gaps due to lack of resources, knowledge and technical abilities, hinder control over outbreaks. This review investigates the bacterial pathogens responsible for FBD, their prevalence, challenges in management, and strategies for prevention. A systematic review was conducted following PRISMA guidelines, focusing on bacterial FBD in CAC from 2000 to 2024. PubMed and Google Scholar were used as primary databases, supported by other sources to identify relevant studies. Inclusion criteria encompassed studies focusing on bacterial pathogens, prevalence, risk factors, and surveillance practices. Out of 509 studies initially identified, 35 met the inclusion criteria. The most prevalent pathogens were Salmonella spp., Escherichia coli, Campylobacter spp., and Aliarcobacter spp., with contamination often associated with poultry, eggs, and vegetables. Key challenges included inadequate surveillance systems, limited resources, and inconsistent reporting practices. Greater investment in pathogen monitoring, documentation, and education, along with the use of technologies like whole-genome sequencing (WGS), is crucial. Institutional and governmental funding is vital to improve surveillance and strengthen risk analysis across the region. 2025 en info:eu-repo/semantics/preprint preprint https://doi.org/10.20944/preprints202411.1874.v2 Preprints.org Preprints.org Preprints.org, 2025 info:eu-repo/semantics/openAccess openAccess cc-by https://doi.org/10.20944/preprints202411.1874.v2 doaj Good health and well-being Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Microbiological and Biosecurity Assessment of Sargassum‐Based Liquid Biofertilizers Yaset Rodríguez-Rodríguez Edian F. Franco De Los Santos Ashley Marie Mejía-Disla Máximo Elías Reynoso-Ortega Gustavo Gandini Pamela Tejeda-Tejeda Miguel Ángel Guevara Carlos Willian Dias Dantas Rommel T. J. Ramos Ulises Javier Jáuregui-Haza liquid biofertilizer biosecurity microbiological safety heavy metals bacterial and archaeal communities phytotoxicity lettuce ecotoxicology soil fertility coastal agriculture Dominican Republic seaweed waste valorization Sargassum seaweed has inundated Caribbean coastlines, disrupting ecosystems while presenting opportunities for sustainable products like liquid biofertilizers. This study evaluated the microbiological and biosecurity profiles of two liquid biofertilizers produced in the Dominican Republic: Sargassum-based (SBLB-INTEC) and conventional (LB-BANELINO). Both exhibited essential minerals (K, Ca, Mg) and low heavy metal concentrations, meeting agricultural safety standards. Metagenomic analysis (16S rRNA) identified diverse bacterial and archaeal communities, mainly consisting of beneficial taxa such as Firmicutes, Proteobacteria, and Methanobacteria, with no detectable pathogens. Ecotoxicological assays with Lactuca sativa showed phytotoxicity at high concentrations, mitigated by dilution (≤6.25%) and pH adjustment (7.0), achieving germination indexes above 80%. These results suggest that Sargassum-based biofertilizers could be a viable alternative for enhancing soil fertility and promoting sustainable crop production, particularly in coastal agricultural systems where conventional fertilizers may be limited or environmentally harmful. Moreover, this study highlights the critical role of ecotoxicological testing in ensuring biofertilizer safety and underscores Sargassum’s potential as a renewable resource for sustainable farming. 2025 en info:eu-repo/semantics/preprint preprint https://doi.org/10.20944/preprints202504.2450.v1 Preprints.org Preprints.org Preprints.org, 2025 info:eu-repo/semantics/openAccess openAccess cc-by https://www.preprints.org/frontend/manuscript/ffaf78dd8d9fba29628347b1f841f51f/download_pub Zero hunger Responsible consumption and production Clean water and sanitation Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Microbiota of the intestinal tract of salinity-tolerant Cyprinodon variegatus riverendi Edian F. Franco Oscar Victor Cardenas Alegria Linette Indhira Dominguez-Araujo Carlos Willians Dias Danta Victor Benedito Costa Ferreira Luise Adriane Viana da Silva Claudia Reyes Yumeris Fernandez Mariel Polanco Valdez Carlos M. Rodríguez-Peña Rommel Thiago Jucá Ramos Luis Orlando Maroto-Martín gut microbiota salt tolerance osmoregulation oxidative stress resistance Serratia marcescens Glutamicibacter Klebsiella pneumoniae methanogenic archaea giant viruses fungi Cetobacterium functional genes metagenomics 2025 en info:eu-repo/semantics/other other https://doi.org/10.21203/rs.3.rs-6947971/v1 Research Square Research Square Research Square, 2025 info:eu-repo/semantics/openAccess openAccess cc-by https://www.researchsquare.com/article/rs-6947971/latest.pdf Life below water Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Aprendizaje de máquina y aprendizaje profundo en biotecnología: aplicaciones, impactos y desafíos Edian F. Franco Rommel J. Ramos Humanities Philosophy La bioinformática es un área que ha modificado la forma en que se diseñan y se desarrollan los experimentos e investigaciones de las áreas biológicas. La biotecnología no ha quedado fuera de los alcances de la bioinformática, impactando directamente áreas como el descubrimiento y el desarrollo de fármacos, mejoramiento de cultivos, biorremediación, estudios de la diversidad ambiental, patología molecular, entre otras. Esto se debe, en gran medida, al desarrollo de las tecnologías de secuenciación de alto rendimiento o Next-generation sequencing (NGS), que han generado gran cantidad de datos que deben ser procesados y analizados para producir nuevos conocimientos y descubrimientos. Lo anterior ha promovido que dos áreas de la bioinformática y la ciencia de la computación, machine learning y deep learning, hayan sido utilizadas para el análisis de estos datos. El “aprendizaje de máquina” aplica técnicas que permiten que las computadoras aprendan, mientras que el “aprendizaje profundo” genera modelos de redes neuronales artificiales que intenta imitar el funcionamiento del cerebro humano, permitiéndoles aprender a partir de los datos y mejorar su aprendizaje a través de las experiencias. Estas dos áreas son esenciales para poder identificar, analizar, interpretar y obtener conocimientos de la gran cantidad de datos biológicos (Big biological data). En este trabajo hacemos una revisión de estas dos áreas: el aprendizaje de máquina y el aprendizaje profundo, orientado al impacto y sus aplicaciones en el área de biotecnología. 2019 es info:eu-repo/semantics/article journal-article https://doi.org/10.22206/cac.2019.v2i2.pp7-26 Ciencia, Ambiente y Clima Ciencia, Ambiente y Clima urn:issn:2636-2317 urn:issn:2636-2333 Ciencia, Ambiente y Clima, 2019, vol. 2, n. 2, p. 7-26 info:eu-repo/semantics/openAccess openAccess cc-by-nc-sa https://revistas.intec.edu.do/index.php/cienacli/article/download/1579/2173 Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Modelos de predicción del impacto y evolución del COVID-19 en República Dominicana Edian F. Franco Víctor V. Calderón Rommel Thiago Jucá Ramos Humanities Coronavirus disease 2019 (COVID-19) Geography Political science Philosophy Medicine COVID-19 Predicciones Modelos matemáticos Después de su descubrimiento en China, en diciembre de 2019, el virus SARS-CoV-2 causante de la enfermedad COVID-19, comenzó a propagarse por la mayoría de los países del mundo, provocando una cantidad importante de infectados y muertos, situación que ha generado una gran presión en los sistemas de salud y gobiernos de los diferentes países, que en muchos casos no contaban con los recursos e infraestructuras para enfrentar una pandemia provocada por el virus, como fue el caso de República Dominicana. Usando los datos públicos del avance de la pandemia en la Republica Dominicana, desde el 1 de marzo hasta el 30 de abril, se modeló y pronosticó la posible evolución del COVID-19 en este país, utilizando de tres modelos matemáticos SIR, SEIR-Extendido y log-lineal. Estos modelos permitieron proyectar los diferentes escenarios de contagios y evolución de la enfermedad, además de pronosticar el pico y el descenso de la curva de casos. Según los resultados obtenidos, el país se encontraba en un proceso de crecimiento exponencial de los contagios; el pico de los contagios fue pronosticado ocurriría entre la segunda mitad del mes de mayo y la primera mitad del mes de junio, con un estimado de infectados entre 100,000 y 200,000 individuos. Los resultados obtenidos en este estudio permiten obtener una idea de cuál podría ser el impacto humano y social del COVID-19 en la República Dominicana. 2020 es info:eu-repo/semantics/article journal-article https://doi.org/10.22206/cac.2020.v3i1.pp5-21 Ciencia, Ambiente y Clima Ciencia, Ambiente y Clima urn:issn:2636-2317 urn:issn:2636-2333 Ciencia, Ambiente y Clima, 2020, vol. 3, n. 1, p. 5-21 info:eu-repo/semantics/openAccess openAccess cc-by-nc-sa https://revistas.intec.edu.do/index.php/cienacli/article/download/1804/2333 Good health and well-being Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Determinación de contaminantes orgánicos persistentes en leche de vaca de producción nacional por medio de la técnica de cromatografía de gases acoplada a espectrometría de masas (GC/MS) Lizaira Bello Camila Marranzini Alejandro Vallejo Degaudenzi Aris Mendis Gómez Enmanuel Echavarría Franco, Edian F persistent organic pollutants cow's milk milk contamination food safety consumer exposure QuEChERS gas chromatography-mass spectrometry Dominican Republic Contaminantes Leche Química agrícola Los contaminantes orgánicos persistentes (COP) son sustancias químicas orgánicas capaces de persistir en el ambiente, transportase a larga distancia, bioacumularse y biomagnificarse en los ecosistemas. Los efectos nocivos de estos compuestos sobre el medio ambiente y la salud de los seres vivos son preocupantes. En particular, los seres humanos pueden entrar en contacto con los COP al consumir alimentos contaminados de origen animal con un alto contenido en grasa. En la República Dominicana estos compuestos se han utilizado y generado ampliamente. Sin embargo, se desconoce cuáles son los niveles de exposición de COP a los que está expuesta la población. Por tanto, este estudio tuvo como objetivo determinar la presencia de 34 COP en cinco principales marcas de leche de vaca de producción nacional. La preparación de las muestras se realizó mediante el método de extracción QuEChERS y la técnica analítica utilizada fue la GC/MS. Los resultados obtenidos indicaron que no hay presencia de los COP evaluados en ninguna de las muestras de leche de vaca, lo cual sugiere que su consumo no representa una amenaza para la salud de los consumidores. Además, este estudio aporta al conocimiento sobre la evaluación de los COP en la República Dominicana. 2020 spa info:eu-repo/semantics/article journal-article https://doi.org/10.22206/cac.2020.v3i2.pp5-18 Ciencia, Ambiente y Clima Ciencia, Ambiente y Clima urn:issn:2636-2317 urn:issn:2636-2333 Ciencia, Ambiente y Clima, 2020 info:eu-repo/semantics/openAccess openAccess cc-by-nc-sa https://revistas.intec.edu.do/index.php/cienacli/article/download/2013/2455 Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Sensores de calidad de agua para el control de la contaminación fisicoquímica en los acuíferos de Latinoamérica: una revisión Edian F. Franco Rommel Thiago Jucá Ramos Argenys Ovando Emanuel Montero-Espaillat Solhanlle Bonilla Atharva Veda Humanities Geography Art El monitoreo de la calidad del agua es un aspecto crítico para garantizar agua segura y limpia para el consumo humano, los procesos industriales y la vida acuática. El empleo de sensores automáticos basados en el internet de las cosas y algoritmos de aprendizaje de máquina utilizados para el monitoreo de la calidad del agua se ha vuelto cada vez más popular, debido a su facilidad de uso, precisión y rentabilidad. En esta revisión, discutiremos algunos de los sensores comúnmente utilizados para la vigilancia de la calidad del agua, así como sus posibles usos para la gestión y supervisión de acuíferos en América Latina. En la primera parte se discute sobre la contaminación de las fuentes de agua en Latinoamérica y, especialmente, en República Dominicana, donde se brinda una revisión de los diferentes trabajos que evalúan la contaminación en afluentes de agua. Además, se explora como el uso cotidiano de estas fuentes de agua puede afectar a los seres humanos. En la última parte del trabajo se presentan las tecnologías de los sensores y sus diferentes implementaciones, así como los principales retos para su integración al monitoreo de la calidad de agua de las fuentes de agua. Esta revisión demostró que el uso de sensores remotos de calidad de agua, basados en tecnologías de IoT y algoritmos de inteligencia artificial son de gran importancia para el control de la contaminación fisicoquímica en los acuíferos de los países latinoamericanos. Estos sensores constituyen una herramienta clave para el manejo sostenible de los recursos hídricos. 2023 es info:eu-repo/semantics/article journal-article https://doi.org/10.22206/cac.2023.v6i1.pp45-70 Ciencia, Ambiente y Clima Ciencia, Ambiente y Clima urn:issn:2636-2317 urn:issn:2636-2333 Ciencia, Ambiente y Clima, 2023, vol. 6, n. 1, p. 45-70 info:eu-repo/semantics/openAccess openAccess cc-by-nc-sa https://revistas.intec.edu.do/index.php/cienacli/article/download/2878/3316 Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Bioprospección de lectinas en plantas de la familia rubiaceae endémicas de la República Dominicana Edian F. Franco Marqui Ramos Abreu Luis Orlando Maroto Martín Luis Enrique De Francisco lectins Rubiaceae endemic plants lectin characterization agglutination Saccharomyces cerevisiae glycoproteins plant biotechnology Las lectinas son proteínas que se unen específicamente a carbohidratos de manera reversible y no catalítica. Debido a sus múltiples funciones biológicas dentro de los organismos, son de amplio interés en la biotecnología. Esta investigación tuvo por objetivo la detección y caracterización de lectinas en tres especies endémicas de la República Dominicana, pertenecientes a la familia Rubiaceae. De estas especies, se detectó al menos una posible lectina en las hojas de Stevensia grandiflora, fuertemente aglutinante para todos los grupos sanguíneos humanos y de forma leve para la levadura Saccharomyces cerevisiae. La lectina mostró estabilidad a 100°C, tener carácter glicoproteico, precipitar a concentraciones de 40% con sulfato de amonio y ser específica para los disacáridos sacarosa y lactosa. Además, mostró cierta especificidad frente a varios monosacáridos, característica semejante a las lectinas con dominios proteicos de leguminosas. Por otro lado, las bandas visualizadas en la electroforesis SDS-PAGE, en condiciones reductoras, demostraron la posible estructura monomérica o dimérica de la(s) lectina(s) detectada(s). Estos resultados representan nuevas lectinas para la tribu de rubiáceas Rondeletieae, con el potencial de servir como herramientas en biotecnología y medicina. 2024 es info:eu-repo/semantics/article journal-article https://doi.org/10.22206/cac.2024.v7i1.3177 Ciencia, Ambiente y Clima Ciencia, Ambiente y Clima urn:issn:2636-2317 urn:issn:2636-2333 Ciencia, Ambiente y Clima, 2024, vol. 7, n. 1, p. 99-122 info:eu-repo/semantics/openAccess openAccess cc-by-nc-sa https://revistas.intec.edu.do/index.php/cienacli/article/download/3177/3691 Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Modelos econométricos para determinar la calidad del agua en los ríos Yaque del Norte y Yaque del Sur de la República Dominicana: 1990-2022 Johanna Antonia Díaz Jiménez Luis Orlando Maroto Rommel T. Ramos Boanerges Domínguez Edian F. Franco river water quality water quality index phosphate nitrate fecal coliforms total dissolved solids agricultural fertilizers urbanization climate extremes environmental policy wastewater treatment sanitation facilities Dominican Republic 2025 info:eu-repo/semantics/article journal-article https://doi.org/10.22206/cac.2024.v7i2.3411 Ciencia, Ambiente y Clima Ciencia, Ambiente y Clima urn:issn:2636-2317 urn:issn:2636-2333 Ciencia, Ambiente y Clima, 2025 info:eu-repo/semantics/openAccess openAccess cc-by-nc-sa https://revistas.intec.edu.do/index.php/cienacli/article/download/3411/3939 Clean water and sanitation Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Bioinformatics on the Road: Taking Training to Students and Researchers Beyond State Capitals Marcus de Barros Braga Fabrício Araujo Edian Franco Kenny da Costa Pinheiro Jakelyne Silva Denner Maués Sebastião Rodrigues da Costa Neto Lucas Pompeu Luís Guimarães Adriana Ribeiro Carneiro Igor Hamoy Rommel Thiago Jucá Ramos Training (meteorology) State (computer science) Computer science Mathematics education Psychology Geography Meteorology Programming language In Brazil, training capable bioinformaticians is done, mostly, in graduate programs, sometimes with experiences during the undergraduate period. However, this formation tends to be inefficient in attracting students to the area and mainly in attracting professionals to support research projects in research groups. To solve these issues, participation in short courses is important for training students and professionals in the usage of tools for specific areas that use bioinformatics, as well as in ways to develop solutions tailored to the local needs of academic institutions or research groups. In this aim, the project “Bioinformática na Estrada” (Bioinformatics on the Road) proposed improving bioinformaticians’ skills in undergraduate and graduate courses, primarily in the countryside of the State of Pará, in the Amazon region of Brazil. The project scope is practical courses focused on the areas of interest of the place where the courses are occurring to train and encourage students and researchers to work in this field, reducing the existing gap due to the lack of qualified bioinformatics professionals. Theoretical and practical workshops took place, such as Introduction to Bioinformatics, Computer Science Basics, Applications of Computational Intelligence applied to Bioinformatics and Biotechnology, Computational Tools for Bioinformatics, Soil Genomics and Research Perspectives and Horizons in the Amazon Region. In the end, 444 undergraduate and graduate students from higher education institutions in the state of Pará and other Brazilian states attended the events of the Bioinformatics on the Road project. 2021 en info:eu-repo/semantics/article journal-article https://doi.org/10.3389/feduc.2021.726930 Frontiers in Education Frontiers in Education urn:issn:2504-284X Frontiers in Education, 2021, vol. 6 info:eu-repo/semantics/openAccess openAccess cc-by https://doi.org/10.3389/feduc.2021.726930 Q2 doaj Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Microbiome analyses of the Uraim River in the Amazon and georeferencing analyses to establish correlation with anthropogenic impacts of land use Edian F. Franco Oscar Victor Cardenas Alegria Victor Benedito Costa Ferreira Wylerson Guimarães Noguera David Tavares Martins Artur Pedro Martins Neto Paulo Rógenes Monteiro Pontes Rosane Barbosa Lopes Cavalcante Sandy Ingrid Aguiar Alves Artur Silva Rosilene Gomes Costa Vasco Azevedo Rommel Thiago Jucá Ramos Virulence Pathogenic bacteria Metagenomics Bacteria Biology Water quality Population Urbanization Amazon rainforest Ecology Environmental science Gene Environmental health Genetics One of the primary challenges in the spread of infectious diseases is the consumption of poorly or untreated water, which is increasingly being used due to the growth of different human activities and the effect of urbanization on freshwater sources, which are often used for consumption purposes. The determination of pathogenic bacteria in freshwater rivers influenced by anthropogenic activities allows for the assessment of the impact these factors have on water quality. Thus, the purpose of this study was to identify the diversity of pathogenic bacteria and virulence genes in the Uraim River in the northern region of Brazil. For this purpose, surface water was collected from five points with varying degrees of anthropogenic impact along the Uraim River. In situ measurements of physicochemical components were conducted, and metagenomic analysis was used for the identification of pathogenic bacteria and virulence genes. Regarding the physicochemical parameters, variability was observed among the different analysis points, as well as diversity among bacteria and virulence genes. Notably, enterobacteria and the ESKAPE group were highlighted among the bacteria, with significant negative associations found between dissolved oxygen and the diversity of virulence genes and between deforestation and population density with the presence of ESKAPE group bacteria. 2024 en info:eu-repo/semantics/article journal-article https://doi.org/10.3389/fenvs.2024.1404230 Frontiers in Environmental Science Frontiers in Environmental Science urn:issn:2296-665X Frontiers in Environmental Science, 2024, vol. 12 info:eu-repo/semantics/openAccess openAccess cc-by https://public-pages-files-2025.frontiersin.org/journals/environmental-science/articles/10.3389/fenvs.2024.1404230/pdf Q1 doaj Sustainable cities and communities Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal PhageWeb – Web Interface for Rapid Identification and Characterization of Prophages in Bacterial Genomes Edian F. Franco Ailton Lopes de Sousa Dener Maués Amália Raiana Fonseca Lobato Kenny C. Pinheiro Fabrício Almeida Araújo Yan Pantoja Artur Silva Jefferson Magalhaes De Morais Rommel Thiago Jucá Ramos Prophage Computer science Identification (biology) Genome Computational biology Interface (matter) Data mining Software Cluster analysis Biology Artificial intelligence Genetics Gene Bacteriophage Programming language This study developed a computational tool with a graphical interface and a web-service that allows the identification of phage regions through homology search and gene clustering. It uses G+C content variation evaluation and tRNA prediction sites as evidence to reinforce the presence of prophages in indeterminate regions. Also, it performs the functional characterization of the prophages regions through data integration of biological databases. The performance of PhageWeb was compared to other available tools (PHASTER, Prophinder, and PhiSpy) using Sensitivity (Sn) and Positive Predictive Value (PPV) tests. As a reference for the tests, more than 80 manually annotated genomes were used. In the PhageWeb analysis, the Sn index was 86.1% and the PPV was approximately 87%, while the second best tool presented Sn and PPV values of 83.3 and 86.5%, respectively. These numbers allowed us to observe a greater precision in the regions identified by PhageWeb while compared to other prediction tools submitted to the same tests. Additionally, PhageWeb was much faster than the other computational alternatives, decreasing the processing time to approximately one-ninth of the time required by the second best software. PhageWeb is freely available at http://computationalbiology.ufpa.br/phageweb. 2018 en info:eu-repo/semantics/article journal-article https://doi.org/10.3389/fgene.2018.00644 Frontiers in Genetics Frontiers in Genetics urn:issn:1664-8021 Frontiers in Genetics, 2018, vol. 9, p. 644 info:eu-repo/semantics/openAccess openAccess cc-by https://www.frontiersin.org/articles/10.3389/fgene.2018.00644/pdf Q1 doaj pubmed Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Distribution of Beta-Lactamase Producing Gram-Negative Bacterial Isolates in Isabela River of Santo Domingo, Dominican Republic Edian F. Franco Luis Enrique Rodríguez De Francisco Víctor V. Calderón Roberto Bonnelly Camila Del Rosario Albert Duarte Rafael Azevedo Baraúna Rommel Thiago Jucá Ramos Omar Paíno Perdomo Enterobacter Acinetobacter Antibiotic resistance Biology Microbiology Veterinary medicine Escherichia coli Antibiotics Medicine Gene Genetics Bacteria carrying antibiotic resistance genes (ARGs) are naturally prevalent in lotic ecosystems such as rivers. Their ability to spread in anthropogenic waters could lead to the emergence of multidrug-resistant bacteria of clinical importance. For this study, three regions of the Isabela river, an important urban river in the city of Santo Domingo, were evaluated for the presence of ARGs. The Isabela river is surrounded by communities that do not have access to proper sewage systems; furthermore, water from this river is consumed daily for many activities, including recreation and sanitation. To assess the state of antibiotic resistance dissemination in the Isabela river, nine samples were collected from these three bluedistinct sites in June 2019 and isolates obtained from these sites were selected based on resistance to beta-lactams. Physico-chemical and microbiological parameters were in accordance with the Dominican legislation. Matrix-assisted laser desorption ionization-time of flight mass spectrometry analyses of ribosomal protein composition revealed a total of 8 different genera. Most common genera were as follows: Acinetobacter (44.6%) and Escherichia (18%). Twenty clinically important bacterial isolates were identified from urban regions of the river; these belonged to genera Escherichia (n = 9), Acinetobacter (n = 8), Enterobacter (n = 2), and Klebsiella (n = 1). Clinically important multi-resistant isolates were not obtained from rural areas. Fifteen isolates were selected for genome sequencing and analysis. Most isolates were resistant to at least three different families of antibiotics. Among beta-lactamase genes encountered, we found the presence of blaTEM, blaOXA, blaSHV, and blaKPC through both deep sequencing and PCR amplification. Bacteria found from genus Klebsiella and Enterobacter demonstrated ample repertoire of antibiotic resistance genes, including resistance from a family of last resort antibiotics reserved for dire infections: carbapenems. Some of the alleles found were KPC-3, OXA-1, OXA-72, OXA-132, CTX-M-55, CTX-M-15, and TEM-1. 2021 en info:eu-repo/semantics/article journal-article https://doi.org/10.3389/fmicb.2020.519169 Frontiers in Microbiology Frontiers in Microbiology urn:issn:1664-302X Frontiers in Microbiology, 2021, vol. 11, p. 519169 info:eu-repo/semantics/openAccess openAccess cc-by https://www.frontiersin.org/articles/10.3389/fmicb.2020.519169/pdf Q1 doaj pubmed Clean water and sanitation Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Environmental resistome of culturable gram-negative bacilli from the Yaque del Norte River: baseline genomic evidence for one health surveillance María F. Chevalier-Alba Dionis I. Hoepelman Larianna Pineda-Cabrera Lázaro M. Acosta-Rivera Seudimar Blanco Roberto Bonelly Holly Rosario María Gonzalez Dairelys Guerrero Irene Ortiz Argeny Ovando Claudia Reyes Luis Enrique Rodríguez de Francisco Rommel Ramos Luis O. Maroto-Martín Edian F. Franco antimicrobial resistance environmental resistome Gram-negative bacilli river water One Health antimicrobial resistance genes plasmid replicons IncFIB plasmid IncY plasmid Pseudomonas aeruginosa Klebsiella pneumoniae Klebsiella quasipneumoniae Acinetobacter multidrug resistance efflux pumps antibiotic resistance surveillance freshwater ecosystems 2026 info:eu-repo/semantics/article journal-article https://doi.org/10.3389/fmicb.2026.1780969 Frontiers in Microbiology Frontiers in Microbiology urn:issn:1664-302X Frontiers in Microbiology, 2026 info:eu-repo/semantics/openAccess openAccess cc-by https://public-pages-files-2025.frontiersin.org/journals/microbiology/articles/10.3389/fmicb.2026.1780969/pdf Q1 doaj pubmed Good health and well-being Clean water and sanitation Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Comparison of Two Bacterial Characterization Techniques for the Genomic Analysis of River Microbiomes Yaset Rodríguez-Rodríguez Edian Franklin Franco De Los Santos Roberto Bonnelly Victor V. Calderon Irene Ortiz Argenys Ovando Confesora Pinales Willy Lara Santo Emilio Mateo-Perez Oscar Victor Cardenas-Alegría Rommel Thiago Jucá Ramos Luis Orlando Maroto Martín MALDI-TOF mass spectrometry whole genome sequencing bacterial identification antibiotic resistance resource-constrained environments This study compares the feasibility of matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometry with whole genome sequencing (WGS) for identifying bacteria in river surface water samples. We collected samples from four rivers in the Dominican Republic and used both techniques to characterize bacterial profiles. MALDI-TOF demonstrated high precision, with 86.2% similarity to WGS results, except for a few discordant cases due to database limitations. MALDI-TOF provided cost-effective and rapid identification, making it a promising alternative to WGS in resource-constrained regions. In particular, good effectiveness of MALDI-TOF in identifying bacteria with a high probability of being resistant to antibiotics was observed, which allows this technology to be used in the monitoring processes of this type of microorganism for their rapid, accurate, and low-cost identification. We found this technology to be advantageous for environmental bacterial profiling, with potential applications in understanding waterborne pathogenic bacteria. Our findings underline the relevance of MALDI-TOF in microbiology and its potential to expand its capabilities in bacterial identification and protein profiling. 2023 en info:eu-repo/semantics/article journal-article https://doi.org/10.3390/applmicrobiol3030071 Applied Microbiology Applied Microbiology urn:issn:2673-8007 Applied Microbiology, 2023, vol. 3, n. 3, p. 1037-1045 info:eu-repo/semantics/openAccess openAccess cc-by https://www.mdpi.com/2673-8007/3/3/71/pdf?version=1693903418 doaj Clean water and sanitation Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Unlocking the Hidden Microbiome of Food: The Role of Metagenomics in Analyzing Fresh Produce, Poultry, and Meat Edian F. Franco De Los Santos Tania Isabel Muñoz-Martinez Bianca Rodríguez-Hernández Milagros Rodríguez-Montaño Jessica Alfau Claudia Reyes Yumeris Fernandez Rommel T. Ramos Luis Orlando Maroto-Martín metagenomics food microbiome food safety fresh produce poultry meat pathogen detection microbial contamination shotgun sequencing metabarcoding long-read sequencing data analysis challenges standardization The increasing complexity of food safety concerns, driven by the rising risks of contamination from pathogens, chemical hazards, and environmental influences, has highlighted the need for more effective detection and prevention strategies. Metagenomics, a powerful molecular tool, is transforming the food industry by providing a comprehensive understanding of the microbial communities in fresh produce, poultry, and meat. Advances in microbial detection techniques, such as shotgun sequencing, metabarcoding, and long-read sequencing technologies, have led to faster and more accurate pathogen detection, reducing the risk of outbreaks and ensuring public health protection. Despite its promise, several challenges remain in implementing metagenomics on a broader scale, including the high cost of sequencing technologies, the complexity of analyzing large datasets, and the lack of standardized procedures across platforms. These limitations hinder its adoption, particularly for smaller operations or in regions with fewer resources. This review examines the applications of metagenomics in food safety, focusing on its impact on meat, poultry, and fresh produce, while discussing the obstacles to its widespread use and potential solutions to overcome these barriers. 2025 en info:eu-repo/semantics/article journal-article https://doi.org/10.3390/applmicrobiol5010026 Applied Microbiology Applied Microbiology urn:issn:2673-8007 Applied Microbiology, 2025, vol. 5, n. 1, p. 26 info:eu-repo/semantics/openAccess openAccess cc-by https://doi.org/10.3390/applmicrobiol5010026 Q2 doaj Zero hunger Good health and well-being Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Performance comparison of deep learning autoencoders for cancer subtype detection using multi-omics data Edian F. Franco Pratip Rana Aline Maria Pereira Cruz Víctor V. Calderón Vasco Azevedo Rommel Thiago Jucá Ramos Preetam Ghosh Subtyping Autoencoder Genomics Computational biology Feature selection Cancer Artificial intelligence Deep learning Computer science Bioinformatics Genome Biology Gene Genetics A heterogeneous disease such as cancer is activated through multiple pathways and different perturbations. Depending upon the activated pathway(s), the survival of the patients varies significantly and shows different efficacy to various drugs. Therefore, cancer subtype detection using genomics level data is a significant research problem. Subtype detection is often a complex problem, and in most cases, needs multi-omics data fusion to achieve accurate subtyping. Different data fusion and subtyping approaches have been proposed over the years, such as kernel-based fusion, matrix factorization, and deep learning autoencoders. In this paper, we compared the performance of different deep learning autoencoders for cancer subtype detection. We performed cancer subtype detection on four different cancer types from The Cancer Genome Atlas (TCGA) datasets using four autoencoder implementations. We also predicted the optimal number of subtypes in a cancer type using the silhouette score and found that the detected subtypes exhibit significant differences in survival profiles. Furthermore, we compared the effect of feature selection and similarity measures for subtype detection. For further evaluation, we used the Glioblastoma multiforme (GBM) dataset and identified the differentially expressed genes in each of the subtypes. The results obtained are consistent with other genomic studies and can be corroborated with the involved pathways and biological functions. Thus, it shows that the results from the autoencoders, obtained through the interaction of different datatypes of cancer, can be used for the prediction and characterization of patient subgroups and survival profiles. 2021 en info:eu-repo/semantics/article journal-article https://doi.org/10.3390/cancers13092013 Cancers Cancers urn:issn:2072-6694 Cancers, 2021, vol. 13, n. 9, p. 2013 info:eu-repo/semantics/openAccess openAccess cc-by https://www.mdpi.com/2072-6694/13/9/2013/pdf?version=1619073745 Q1 doaj pubmed Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Co-Expression Networks for Causal Gene Identification Based on RNA-Seq Data of Corynebacterium pseudotuberculosis Edian F. Franco Pratip Rana Ana Lídia Q. Cavalcante Artur Silva Anne Cybelle Pinto Gomide Adriana Ribeiro Carneiro Vasco Azevedo Preetam Ghosh Rommel Thiago Jucá Ramos Corynebacterium pseudotuberculosis Caseous lymphadenitis Biology Gene RNA-Seq Computational biology Genome Identification (biology) Yersinia pseudotuberculosis Genetics Virulence Gene regulatory network Gene expression Bacteria Microbiology Transcriptome Corynebacterium pseudotuberculosis is a Gram-positive bacterium that causes caseous lymphadenitis, a disease that predominantly affects sheep, goat, cattle, buffalo, and horses, but has also been recognized in other animals. This bacterium generates a severe economic impact on countries producing meat. Gene expression studies using RNA-Seq are one of the most commonly used techniques to perform transcriptional experiments. Computational analysis of such data through reverse-engineering algorithms leads to a better understanding of the genome-wide complexity of gene interactomes, enabling the identification of genes having the most significant functions inferred by the activated stress response pathways. In this study, we identified the influential or causal genes from four RNA-Seq datasets from different stress conditions (high iron, low iron, acid, osmosis, and PH) in C. pseudotuberculosis, using a consensus-based network inference algorithm called miRsigand next identified the causal genes in the network using the miRinfluence tool, which is based on the influence diffusion model. We found that over 50% of the genes identified as influential had some essential cellular functions in the genomes. In the strains analyzed, most of the causal genes had crucial roles or participated in processes associated with the response to extracellular stresses, pathogenicity, membrane components, and essential genes. This research brings new insight into the understanding of virulence and infection by C. pseudotuberculosis. 2020 en info:eu-repo/semantics/article journal-article https://doi.org/10.3390/genes11070794 Genes Genes urn:issn:2073-4425 Genes, 2020, vol. 11, n. 7, p. 794 info:eu-repo/semantics/openAccess openAccess cc-by https://doi.org/10.3390/genes11070794 Q2 doaj pubmed Partnerships for the goals Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Evaluation of the Common Molecular Basis in Alzheimer’s and Parkinson’s Diseases Edian F. Franco Pratip Rana Yug Rao Khajamoinuddin Syed Debmalya Barh Vasco Azevedo Rommel Thiago Jucá Ramos Preetam Ghosh Parkinson's disease Alzheimer's disease Medicine Neuroscience Disease Psychology Pathology Alzheimer’s disease (AD) and Parkinson’s disease (PD) are the most common neurodegenerative disorders related to aging. Though several risk factors are shared between these two diseases, the exact relationship between them is still unknown. In this paper, we analyzed how these two diseases relate to each other from the genomic, epigenomic, and transcriptomic viewpoints. Using an extensive literature mining, we first accumulated the list of genes from major genome-wide association (GWAS) studies. Based on these GWAS studies, we observed that only one gene (HLA-DRB5) was shared between AD and PD. A subsequent literature search identified a few other genes involved in these two diseases, among which SIRT1 seemed to be the most prominent one. While we listed all the miRNAs that have been previously reported for AD and PD separately, we found only 15 different miRNAs that were reported in both diseases. In order to get better insights, we predicted the gene co-expression network for both AD and PD using network analysis algorithms applied to two GEO datasets. The network analysis revealed six clusters of genes related to AD and four clusters of genes related to PD; however, there was very low functional similarity between these clusters, pointing to insignificant similarity between AD and PD even at the level of affected biological processes. Finally, we postulated the putative epigenetic regulator modules that are common to AD and PD. 2019 en info:eu-repo/semantics/article journal-article https://doi.org/10.3390/ijms20153730 International Journal of Molecular Sciences International Journal of Molecular Sciences urn:issn:1422-0067 urn:issn:1661-6596 International Journal of Molecular Sciences, 2019, vol. 20, n. 15, p. 3730 info:eu-repo/semantics/openAccess openAccess cc-by https://www.mdpi.com/1422-0067/20/15/3730/pdf?version=1564558214 Q1 doaj pubmed Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Bacterial Foodborne Diseases in Central America and the Caribbean: A Systematic Review Edian Franklin Franco De Los Santos Nicole Severino Claudia Reyes Yumeris Fernandez Vasco Ariston de Carvalho Azevedo Luis Enrique Rodríguez De Francisco Rommel Thiago Ramos Luis Orlando Maroto-Martín foodborne pathogens Salmonella Escherichia coli Campylobacter poultry contamination egg contamination vegetable contamination foodborne disease surveillance risk factors whole genome sequencing Central America and the Caribbean Foodborne diseases (FBDs) represent a significant public health concern, particularly in regions like Central America and the Caribbean (CAC), where surveillance gaps due to a lack of resources, knowledge, and technical abilities hinder control over outbreaks. This review investigates the bacterial pathogens responsible for FBDs, their prevalence, management challenges, and prevention strategies. This systematic review followed PRISMA guidelines, focusing on bacterial FBDs in CAC from 2000 to 2024. PubMed and Google Scholar were used as primary databases, supported by other sources to identify relevant studies. Inclusion criteria encompassed studies focusing on bacterial pathogens, prevalence, risk factors, and surveillance practices. Out of the 509 studies initially identified, 35 met the inclusion criteria. The most prevalent pathogens were Salmonella spp., Escherichia coli, Campylobacter spp., and Aliarcobacter spp., with contamination often associated with poultry, eggs, and vegetables. Key challenges included inadequate surveillance systems, limited resources, and inconsistent reporting practices. A more significant investment in pathogen monitoring, documentation, and education, along with technologies like whole-genome sequencing (WGS), is crucial. Institutional and governmental funding is vital to improve surveillance and strengthen regional risk analysis. 2025 en info:eu-repo/semantics/article journal-article https://doi.org/10.3390/microbiolres16040078 Microbiology Research Microbiology Research urn:issn:2036-7473 urn:issn:2036-7481 Microbiology Research, 2025, vol. 16, n. 4, p. 78 info:eu-repo/semantics/openAccess openAccess cc-by https://www.mdpi.com/2036-7481/16/4/78/pdf?version=1743503637 Q3 doaj Good health and well-being Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Household Solid Waste Management in the Dominican Republic: Case of the Municipality of Puñal, Santiago Edian F. Franco Wilfredo Padrón Iglesias Karina Pérez Teruel Municipal solid waste Waste management Waste collection Population Business Government (linguistics) Service (business) Environmental planning Environmental science Engineering Environmental health One of the biggest problems that the Dominican Republic has had in recent decades is the efficient management of solid domestic waste. This problem has worsened in recent years due to the decrease in available areas for the construction of sanitary landfills, the lack of recycling culture in the population, the deficiency in waste collection, and the scarce legal controls aimed at preserving water, air and soil among other factors. The objective of this study is to explore the management of solid waste by the population and the municipality of Puñal, province of Santiago, to evaluate and analyze the situation and generation of solid waste, municipal solid waste management services, and the attitudes of the population regarding recycling projects and waste management. A total of 275 households from 29 localities in the municipality of Puñal were surveyed, which allowed for a significant population sample. According to the results, the most significant type of waste produced by families is organic waste, followed by plastic waste and paper. Of the total organic waste produced in the municipality, 53% of solids wastes are handled through the municipal waste collection system, while 47% is used as plant fertilizers or animal feed. On the other hand, most households receive the municipal waste collection service and pay for this service, through which the municipal government collects, processes, and deposits the waste in different landfills. However, a more efficient waste collection system and the development of programs and projects that allow households to manage the solid waste efficiently they produce would be necessary. 2022 en info:eu-repo/semantics/article journal-article https://doi.org/10.3390/su14063149 Sustainability Switzerland Sustainability Switzerland urn:issn:2071-1050 Sustainability Switzerland, 2022, vol. 14, n. 6, p. 3149 info:eu-repo/semantics/openAccess openAccess cc-by https://www.mdpi.com/2071-1050/14/6/3149/pdf?version=1646809730 Q1 Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Beta-Lactam Susceptibility Profiles of Bacteria Isolated from the Ozama River in Santo Domingo, Dominican Republic Yaset Rodríguez-Rodríguez Edian Franklin Franco De Los Santos Roberto Bonnelly Ana Lidia Queiroz Cavalcante Victor V. Calderon Rafael Azevedo Baraúna Rommel Thiago Jucá Ramos Luis Enrique Rodríguez De Francisco Luis Orlando Maroto Martín Omar Paino Perdomo beta-lactam resistance antimicrobial resistance multidrug resistance antibiotic-resistant bacteria surface water contamination wastewater discharge cefotaxime imipenem MALDI-TOF identification metagenomic sequencing urban rivers Santo Domingo The spread and contamination of antimicrobial-resistant bacteria in ambient waters is an emerging concern in urban, rural, medical, and industrial settings. A large amount of domestic, hospital, and industrial wastewater discharged directly into the rivers through the different channels can turn them into extensive reservoirs of antibiotic-resistant bacteria. In the present study, surface water samples from three collection sites were analyzed, according to different levels of anthropogenic impacts, along the Ozama River, one of the most important rivers in the Dominican metropolitan area, a source of water and food for human consumption. Seventy-six bacterial isolates were selected based on resistance to beta-lactams, using culture media previously enriched with cefotaxime and imipenem. Matrix-Assisted Laser Desorption/Ionization Time of Flight Mass Spectrometry (MALDI-TOF) subsequently identified them. The isolates covered 12 genera of bacteria; more than 30% were clinically relevant, and 43% had phenotypes classified as multidrug resistance. A total of 10 (44%) presented resistance. However, only seven presented resistance to 3 or more of the 14 groups of antibiotics, considered to be a multiresistant phenotype, which was sequenced using the high-throughput sequencing technique or New Generation (NGS). This study is part of the initiative to understand the profiles of the dangers of multidrug resistance in the metropolitan and rural areas of the Dominican Republic and its possible implications for human health. 2023 en info:eu-repo/semantics/article journal-article https://doi.org/10.3390/su15065109 Sustainability Switzerland Sustainability Switzerland urn:issn:2071-1050 Sustainability Switzerland, 2023, vol. 15, n. 6, p. 5109 info:eu-repo/semantics/openAccess openAccess cc-by https://www.mdpi.com/2071-1050/15/6/5109/pdf?version=1678785968 Q1 Good health and well-being Clean water and sanitation Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Democratising Artificial Intelligence for Pandemic Preparedness and Global Governance in Latin American and Caribbean Countries Edian F. Franco André C. P. L. F. de Carvalho Robson Parmezan Bonidia Jude Dzevela Kong Mariana Dauhajre Claudio José Struchiner Guilherme Tegoni Goedert Peter Florian Stadler Maria Emília M. T. Walter Danilo Sipoli Sanches Troy Day Márcia C. Castro John Edmunds Manuel Emilio Colome Hidalgo Demian Arturo Herrera Morban César Ugarte‐Gil Patricia Espinoza‐Lopez Gabriel Carrasco‐Escobar Ulisses Nunes da Rocha Preparedness Latin Americans Pandemic Corporate governance Political science Caribbean region Development economics Economic growth Coronavirus disease 2019 (COVID-19) Business Economics Finance Medicine Infectious diseases, transmitted directly or indirectly, are among the leading causes of epidemics and pandemics. Consequently, several open challenges exist in predicting epidemic outbreaks, detecting variants, tracing contacts, discovering new drugs, and fighting misinformation. Artificial Intelligence (AI) can provide tools to deal with these scenarios, demonstrating promising results in the fight against the COVID-19 pandemic. AI is becoming increasingly integrated into various aspects of society. However, ensuring that AI benefits are distributed equitably and that they are used responsibly is crucial. Multiple countries are creating regulations to address these concerns, but the borderless nature of AI requires global cooperation to define regulatory and guideline consensus. Considering this, The Global South AI for Pandemic & Epidemic Preparedness & Response Network (AI4PEP) has developed an initiative comprising 16 projects across 16 countries in the Global South, seeking to strengthen equitable and responsive public health systems that leverage Southern-led responsible AI solutions to improve prevention, preparedness, and response to emerging and re-emerging infectious disease outbreaks. This opinion introduces our branches in Latin American and Caribbean (LAC) countries and discusses AI governance in LAC in the light of biotechnology. Our network in LAC has high potential to help fight infectious diseases, particularly in low- and middle-income countries, generating opportunities for the widespread use of AI techniques to improve the health and well-being of their communities. 2024 en info:eu-repo/semantics/other other https://doi.org/10.48550/arxiv.2409.14181 Arxiv Arxiv urn:issn:2331-8422 Arxiv, 2024 info:eu-repo/semantics/openAccess openAccess cc-by-nc-nd https://arxiv.org/pdf/2409.14181 Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Análisis computacional de isoformas de doublesex en Anopheles gambiae Computational analysis of doublesex isoforms in Anopheles gambiae Edian F. Franco Manuel Emilio Colome Hidalgo Mabel Serrano Cheryl Marte Nasla Gomez Pedro María Alarcón‐Elbal Alejandro Vallejo Degaudenzi Anopheles gambiae Doublesex RNA splicing In silico El gen doublesex (dsx) participa en la determinación sexual de Anopheles gambiae sensu stricto y constituye una posible diana para control vectorial. El objetivo fue caracterizar computacionalmente sus isoformas sexo-específicas. Se realizó un análisis in silico de las isoformas RA y RB con datos de VectorBase, evaluando arquitectura génica, longitud del CDS y productos proteicos predichos. RA y RB mostraron diferencias en organización estructural y longitud proteica, conservando el marco de lectura. Las variantes teóricas derivadas de RB permitieron explorar el efecto de modificaciones terminales sin introducir cambios de fase. La diversidad funcional de dsx se asocia al splicing alternativo y refuerza su interés como diana molecular para futuras investigaciones en control genético de vectores. 2026 info:eu-repo/semantics/article journal-article https://doi.org/10.62430/rtb20262412138 The Biologist The Biologist urn:issn:1816-0719 urn:issn:1994-9073 The Biologist, 2026, vol. 24, n. 1, p. 165-171 info:eu-repo/semantics/openAccess openAccess cc-by-nc-nd https://revistas.unfv.edu.pe/rtb/article/download/2138/3517 Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Distribution of Beta-Lactamase Producing Gram-Negative Bacterial Isolates in Isabela River of Santo Domingo, Dominican Republic 2021 info:eu-repo/semantics/article journal-article cris:cris-0a929b16 Frontiers in Microbiology Frontiers in Microbiology Frontiers in Microbiology, 2021 Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal La anosmia y su interacción en las infecciones causadas por el SARS-CoV2 una revisión Franco, Edian F Jucá Ramos, Rommel T Thomaz Maia, Maria H Anosmia Ageusia COVID-19 La anosmia es uno de los síntomas frecuentes identificados como parte del cuadro clínico de la infección por SARS-CoV2, sin embargo, los mecanismos por los cuales ocurre la disfunción olfatoria no están completamente esclarecidos. Previamente los coronavirus fueron identificados como una familia de virus que pueden causar anosmia, pero en el COVID-19, a diferencia de la familia de los rinovirus, esta no se relaciona con un proceso inflamatorio de la mucosa nasal asociado a obstrucción nasal o rinorrea, lo cual sugiere que la anosmia podría deberse a disturbios en la conducción nerviosa del estímulo olfatorio. La anosmia de los pacientes con COVID-19 recuerda en algunos aspectos al síndrome de Kallman, el cual también cursa con anosmia, su etiología es genética y se debe a mutaciones en el gen ANOS 1 que codifica la molécula de adhesión celular anosmia. En esta revisión se suministrará una recopilación de evidencias fisiopatológicas e interacciones moleculares mediante la cual la proteína anosmia podría modificar el curso de la infección por SARS-CoV2, para ello, se realizó una búsqueda computarizada de literatura para desvendar las posibles relaciones que existen en entre la anosmia y las infecciones causadas por el SARS-CoV2. 2021 spa info:eu-repo/semantics/bookPart book-chapter cris:cris-30846d69 Ciencia, ambiente y clima Ciencia, ambiente y clima urn:issn:(impreso): 2636-2317 urn:issn:(en línea): 2636-233 Ciencia, ambiente y clima, 2021 info:eu-repo/semantics/openAccess openAccess https://revistas.intec.edu.do/index.php/cienacli/article/view/2370 Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Determinación de contaminantes orgánicos persistentes en leche de vaca de producción nacional por medio de la técnica de cromatografía de gases acoplada a espectrometría de masas (GC/MS) Franco, Edian F Bello, Lizaira Vallejo Degaudenzi, Alejandro Gómez, Aris Mendis Echavarría, Enmanuel Contaminantes Leche Química agrícola Los contaminantes orgánicos persistentes (COP) son sustancias químicas orgánicas capaces de persistir en el ambiente, transportase a larga distancia, bioacumularse y biomagnificarse en los ecosistemas. Los efectos nocivos de estos compuestos sobre el medio ambiente y la salud de los seres vivos son preocupantes. En particular, los seres humanos pueden entrar en contacto con los COP al consumir alimentos contaminados de origen animal con un alto contenido en grasa. En la República Dominicana estos compuestos se han utilizado y generado ampliamente. Sin embargo, se desconoce cuáles son los niveles de exposición de COP a los que está expuesta la población. Por tanto, este estudio tuvo como objetivo determinar la presencia de 34 COP en cinco principales marcas de leche de vaca de producción nacional. La preparación de las muestras se realizó mediante el método de extracción QuEChERS y la técnica analítica utilizada fue la GC/MS. Los resultados obtenidos indicaron que no hay presencia de los COP evaluados en ninguna de las muestras de leche de vaca, lo cual sugiere que su consumo no representa una amenaza para la salud de los consumidores. Además, este estudio aporta al conocimiento sobre la evaluación de los COP en la República Dominicana. 2020 spa info:eu-repo/semantics/bookPart book-chapter cris:cris-4be64515 Ciencia, ambiente y clima Ciencia, ambiente y clima urn:issn:(impreso): 2636-2317 urn:issn:(en línea): 2636-233 Ciencia, ambiente y clima, 2020 info:eu-repo/semantics/openAccess openAccess https://revistas.intec.edu.do/index.php/cienacli/article/view/2013/2455 Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Aprendizaje de máquina y aprendizaje profundo en biotecnología aplicaciones, impactos y desafíos Franco, Edian F Ramos, Rommel J Biotecnología Bioinformática La bioinformática es un área que ha modificado la forma en que se diseñan y se desarrollan los experimentos e investigaciones de las áreas biológicas. La biotecnología no ha quedado fuera de los alcances de la bioinformática, impactando directamente áreas como el descubrimiento y el desarrollo de fármacos, mejoramiento de cultivos, biorremediación, estudios de la diversidad ambiental, patología molecular, entre otras. Esto se debe, en gran medida, al desarrollo de las tecnologías de secuenciación de alto rendimiento o Next-generation sequencing (NGS), que han generado gran cantidad de datos que deben ser procesados y analizados para producir nuevos conocimientos y descubrimientos. Lo anterior ha promovido que dos áreas de la bioinformática y la ciencia de la computación, machine learning y deep learning, hayan sido utilizadas para el análisis de estos datos. El “aprendizaje de máquina” aplica técnicas que permiten que las computadoras aprendan, mientras que el “aprendizaje profundo” genera modelos de redes neuronales artificiales que intenta imitar el funcionamiento del cerebro humano, permitiéndoles aprender a partir de los datos y mejorar su aprendizaje a través de las experiencias. Estas dos áreas son esenciales para poder identificar, analizar, interpretar y obtener conocimientos de la gran cantidad de datos biológicos (Big biological data). En este trabajo hacemos una revisión de estas dos áreas: el aprendizaje de máquina y el aprendizaje profundo, orientado al impacto y sus aplicaciones en el área de biotecnología. 2018 spa info:eu-repo/semantics/bookPart book-chapter cris:cris-6e1c520f Ciencia, ambiente y clima Ciencia, ambiente y clima Ciencia, ambiente y clima, 2018 info:eu-repo/semantics/openAccess openAccess https://revistas.intec.edu.do/index.php/cienacli/article/view/1579/2173 Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Uso de datos abiertos y técnicas de mineŕia de datos para la clasificación de estudiantes de instituciones privadas de educación superior de Belem-PA 2018 info:eu-repo/semantics/conferenceObject proceedings-article cris:cris-852f8869 Research in Computing Science Research in Computing Science Research in Computing Science, 2018 Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal