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Abiel Roche-Lima

Faculty RankAssistant Professor - Bioinformatics
InstitutionUniversity of Puerto Rico
DepartmentDeanship of Academic Affairs
AddressUPR-Medical Sciences Campus, Deanship of Academic Affairs
RCMI Center for Collaborative Research in Health Disparities
San Juan PR 936
Phone17877582525 ext 2669
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    Dr. Roche-Lima has a broad background applying computer science to complex biological data. He joined the Medical Science Campus, University of Puerto Rico (MSC-UPR), where he works on providing data science services and research for biomedical projects. He has expertise on using existing tools for analysis, visualization and interpretation of biomedical data, as well as developing and implementing new computational tools for these purposes. Specifically, Dr. Roche-Lima focuses his research on biomedical data science as the application of machine learning methods for prediction, analysis and interpretation of biomedical data. His research long-term goal is to incorporate data to develop more precise models and tools for personalized medicine to reduce health disparities.
    Dr. Roche-Lima is also the Director of the Integrated Informatics Service core (IIS) RCMI project, which is a federal funded project for minority institutions at MSC-UPR. The goal of this core is to provide one point of contact to assist researchers with the general aspects of biomedical data science (as bioinformatics, health informatics and operational informatics) as they apply to the biomedical science research, through the internal and external collaborations.

    2015 PhD in Computer Science (Bioinformatics). University of Manitoba, Canada.
    2001 Master in Computer Science. University of Santa Catarina. Brazil.
    1993 Bachelor in Computer Science, University of Havana, Cuba.

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    Publications listed below are automatically derived from MEDLINE/PubMed and other sources, which might result in incorrect or missing publications. Faculty can login to make corrections and additions.
    Newest   |   Oldest   |   Most Cited   |   Most Discussed   |   Timeline   |   Field Summary   |   Plain Text
    PMC Citations indicate the number of times the publication was cited by articles in PubMed Central, and the Altmetric score represents citations in news articles and social media. (Note that publications are often cited in additional ways that are not shown here.) Fields are based on how the National Library of Medicine (NLM) classifies the publication's journal and might not represent the specific topic of the publication. Translation tags are based on the publication type and the MeSH terms NLM assigns to the publication. Some publications (especially newer ones and publications not in PubMed) might not yet be assigned Field or Translation tags.) Click a Field or Translation tag to filter the publications.
    1. Heredia FL, Roche-Lima A, Parés-Matos EI. A novel artificial intelligence-based approach for identification of deoxynucleotide aptamers. PLoS Comput Biol. 2021 Aug 03; 17(8):e1009247. PMID: 34343165.
      Citations:    Fields:    
    2. Borges-Vélez G, Rosado-Philippi J, Cantres-Rosario YM, Carrasquillo-Carrion K, Roche-Lima A, Pérez-Vargas J, González-Martínez A, Correa-Rivas MS, Meléndez LM. Zika virus infection of the placenta alters extracellular matrix proteome. J Mol Histol. 2021 Jul 15. PMID: 34264436.
      Citations:    Fields:    
    3. Rogozin IB, Roche-Lima A, Tyryshkin K, Carrasquillo-Carrión K, Lada AG, Poliakov LY, Schwartz E, Saura A, Yurchenko V, Cooper DN, Panchenko AR, Pavlov YI. DNA Methylation, Deamination, and Translesion Synthesis Combine to Generate Footprint Mutations in Cancer Driver Genes in B-Cell Derived Lymphomas and Other Cancers. Front Genet. 2021; 12:671866. PMID: 34093666.
    4. Martínez-Matías N, Chorna N, González-Crespo S, Villanueva L, Montes-Rodríguez I, Melendez-Aponte LM, Roche-Lima A, Carrasquillo-Carrión K, Santiago-Cartagena E, Rymond BC, Babu M, Stagljar I, Rodríguez-Medina JR. Toward the discovery of biological functions associated with the mechanosensor Mtl1p of Saccharomyces cerevisiae via integrative multi-OMICs analysis. Sci Rep. 2021 Apr 01; 11(1):7411. PMID: 33795741.
      Citations:    Fields:    
    5. Gonzalez-Cordero AF, Duconge-Soler J, Franqui-Rivera H, Feliu-Maldonado R, Roche-Lima A, Almodovar-Rivera I. Insight on the Genetics of Atrial Fibrillation in Puerto Rican Hispanics. Stroke Res Treat. 2021; 2021:8819896. PMID: 33505650.
    6. Hernandez-Suarez DF, Ranka S, Kim Y, Latib A, Wiley J, Lopez-Candales A, Pinto DS, Gonzalez MC, Ramakrishna H, Sanina C, Nieves-Rodriguez BG, Rodriguez-Maldonado J, Feliu Maldonado R, Rodriguez-Ruiz IJ, da Luz Sant'Ana I, Wiley KA, Cox-Alomar P, Villablanca PA, Roche-Lima A. Machine-Learning-Based In-Hospital Mortality Prediction for Transcatheter Mitral Valve Repair in the United States. Cardiovasc Revasc Med. 2021 01; 22:22-28. PMID: 32591310.
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    7. Roche-Lima A, Roman-Santiago A, Feliu-Maldonado R, Rodriguez-Maldonado J, Nieves-Rodriguez BG, Carrasquillo-Carrion K, Ramos CM, da Luz Sant'Ana I, Massey SE, Duconge J. Machine Learning Algorithm for Predicting Warfarin Dose in Caribbean Hispanics Using Pharmacogenetic Data. Front Pharmacol. 2019; 10:1550. PMID: 32038238.
    8. Hernandez-Suarez DF, Villablanca PA, Kim Y, Wiley J, Sanina C, Roche-Lima A. Reply: Leveraging Machine Learning to Generate Prediction Models for Structural Valve Interventions. JACC Cardiovasc Interv. 2019 10 28; 12(20):2113-2114. PMID: 31648770.
      Citations: 1     Fields:    
    9. Hernandez-Suarez DF, Kim Y, Villablanca P, Gupta T, Wiley J, Nieves-Rodriguez BG, Rodriguez-Maldonado J, Feliu Maldonado R, da Luz Sant'Ana I, Sanina C, Cox-Alomar P, Ramakrishna H, Lopez-Candales A, O'Neill WW, Pinto DS, Latib A, Roche-Lima A. Machine Learning Prediction Models for In-Hospital Mortality After Transcatheter Aortic Valve Replacement. JACC Cardiovasc Interv. 2019 07 22; 12(14):1328-1338. PMID: 31320027.
      Citations: 10     Fields:    Translation:Humans
    10. Gómez-Moreno R, Martínez-Ramírez R, Roche-Lima A, Carrasquillo-Carrión K, Pérez-Santiago J, Baerga-Ortiz A. Hotspots of Sequence Variability in Gut Microbial Genes Encoding Pro-Inflammatory Factors Revealed by Oligotyping. Front Genet. 2019; 10:631. PMID: 31354787.
    11. Graydon JS, Claudio K, Baker S, Kocherla M, Ferreira M, Roche-Lima A, Rodríguez-Maldonado J, Duconge J, Ruaño G. Ethnogeographic prevalence and implications of the 677C>T and 1298A>C MTHFR polymorphisms in US primary care populations. Biomark Med. 2019 06; 13(8):649-661. PMID: 31157538.
      Citations: 1     Fields:    Translation:Humans
    12. Hernandez-Suarez DF, Lopez-Menendez F, Roche-Lima A, Lopez-Candales A. Assessment of Mitral Annular Plane Systolic Excursion in Patients With Left Ventricular Diastolic Dysfunction. Cardiol Res. 2019 Apr; 10(2):83-88. PMID: 31019637.
    13. Hernandez-Suarez DF, Ranka S, Villablanca P, Yordan-Lopez N, González-Sepúlveda L, Wiley J, Sanina C, Roche-Lima A, Nieves-Rodriguez BG, Thomas S, Cox-Alomar P, Lopez-Candales A, Ramakrishna H. Racial/Ethnic Disparities in Patients Undergoing Transcatheter Aortic Valve Replacement: Insights from the Healthcare Cost and Utilization Project's National Inpatient Sample. Cardiovasc Revasc Med. 2019 07; 20(7):546-552. PMID: 30987828.
      Citations: 1     Fields:    Translation:Humans
    14. Rogozin IB, Roche-Lima A, Lada AG, Belinky F, Sidorenko IA, Glazko GV, Babenko VN, Cooper DN, Pavlov YI. Nucleotide Weight Matrices Reveal Ubiquitous Mutational Footprints of AID/APOBEC Deaminases in Human Cancer Genomes. Cancers (Basel). 2019 Feb 12; 11(2). PMID: 30759888.
    15. Vélez-Segarra V, Carrasquillo-Carrión K, Santini-González JJ, Ramos-Valerio YA, Vázquez-Quiñones LE, Roche-Lima A, Rodríguez-Medina JR, Parés-Matos EI. Modelling and molecular docking studies of the cytoplasmic domain of Wsc-family, full-length Ras2p, and therapeutic antifungal compounds. Comput Biol Chem. 2019 Feb; 78:338-352. PMID: 30654316.
      Citations:    Fields:    Translation:Animals
    16. Roche-Lima A, Carrasquillo-Carrión K, Gómez-Moreno R, Cruz JM, Velázquez-Morales DM, Rogozin IB, Baerga-Ortiz A. The Presence of Genotoxic and/or Pro-inflammatory Bacterial Genes in Gut Metagenomic Databases and Their Possible Link With Inflammatory Bowel Diseases. Front Genet. 2018; 9:116. PMID: 29692798.
    17. Manfredi B, Morales-Ortíz J, Díaz-Díaz LM, Hernandez-Matias L, Barreto-Vázquez D, Menéndez-Pérez J, Rodríguez-Cordero JA, Villalobos-Santos JC, Santiago-Rivera E, Rivera-Dompenciel A, Lozada-Delgado EL, Kuchibhotla M, Carrasquillo-Carrión K, Roche-Lima A, Washington AV. The Characterization of Monoclonal Antibodies to Mouse TLT-1 Suggests That TLT-1 Plays a Role in Wound Healing. Monoclon Antib Immunodiagn Immunother. 2018 Apr; 37(2):78-86. PMID: 29708866.
      Citations: 3     Fields:    Translation:AnimalsCellsPHPublic Health
    18. Ordoñez P, Schwarz N, Figueroa-Jiménez A, Garcia-Lebron LA, Roche-Lima A. Learning stochastic finite-state transducer to predict individual patient outcomes. Health Technol (Berl). 2016; 6(3):239-245. PMID: 27942425.
    19. Roche-Lima A. Implementation and comparison of kernel-based learning methods to predict metabolic networks. Netw Model Anal Health Inform Bioinform. 2016; 5:26. PMID: 27471658.
    20. Roche-Lima, A., Ordóñez, P. Supervised Learning Methods based on Finite-State Transducers to Classify Physiological Data. Proceedings of Machine Learning in health care, NIPS'2015. Montreal, Canada. 2015. View Publication.
    21. Roche-Lima, A.; Domaratzki, M., Fristensky, B. . Predicting Metabolic Networks through Pairwise Rational Kernels. Proceedings of Conference on Regulatory and Systems Genomics. Philadelphia, Nov. 2015. View Publication.
    22. Roche-Lima A, Domaratzki M, Fristensky B. Metabolic network prediction through pairwise rational kernels. BMC Bioinformatics. 2014 Sep 26; 15:318. PMID: 25260372.
      Citations: 1     Fields:    Translation:Animals
    23. Roche-Lima, A.; Domaratzki, M., Fristensky, B. . Pairwise Rational Kernels Based on Automaton Operations. Springer's Lecture Notes in Computer Science. 2014; 8587:332-345. View Publication.
    24. Alvare, G. Roche-Lima, A. Fristensky, B. BioLegato: A Programmable, Object-Oriented Graphic User Interface. APBC 2012 - The Tenth Asia Pacific Bioinformatics Conference. Melbourne, Australia. 2013. View Publication.
    25. Roche-Lima, A. Domaratzki, M. Fristensky, B. Supervised Learning Methods to Infer Metabolic Network using Sequence and Non-sequence Kernels. Workshop Machine Learning in System Biology, ISBM/ECCB'13. Berlin, Germany. 2013. View Publication.
    26. Alvare GG, Roche-Lima A, Fristensky B. BioPCD - A Language for GUI Development Requiring a Minimal Skill Set. Int J Comput Appl. 2012 Nov; 57(6):9-16. PMID: 27818582.
    27. Roche-Lima A, Thulasiram RK. Bioinformatics algorithm based on a parallel implementation of a machine learning approach using transducers. J Phys Conf Ser. 2012; 341. PMID: 27795731.
    28. Alvare, G.; Roche-Lima, A.; Fristensky, B. BioPCD - A Language for GUI Development Requiring a Minimal Skill Set. International Journal of Computer Applications. 2012; 6(57):9-16. View Publication.
    29. Roche-Lima, A. Thulasiram, R.K. Bioinformatics algorithm based on a parallel implementation on Westgrid (Cloud/Grid environment). Journal of Physics. J.Phys.: Conf.Ser. 2012; 012034(341). View Publication.
    30. Roche-Lima, A. Thulasiram, R.K. A Parallel Conditional Transducer Learning Algorithm Applied to Bioinformatics. International Conference HPCS 2011: High Performance Computer in Medical Science. Montreal, QC, Canada. 2011. View Publication.
    31. Roche-Lima, A. Oncina, J. Grave de Peralta, R. A. Cora Gonzalez, M. A. Figueroa, Y. Calderius, D. F. Hernandez,, B Gamboa, R. D. Moreno, N. Bioinformatics applied to genetic study of microorganism. Proceedings of 2nd Conference of IT in Animal Science. Institute of Animal Science, Havana, Cuba. 2007.
    32. Roche-Lima, A. . Modelling and Simulation Applied to Animal Nutrition and Feeding. Proceedings of 1st International Conference of Tropical Animal Production. Havana, Cuba. 2005.
    33. Roche-Lima, A. Kakes, A. Gomez S. Noda, A. Sotolongo, A. Vega, Y. Comparison of the SIMPLEX and Interior Points Method to solve the linear optimization problem for nutritional rations. Cuban Journal of Agricultural Science. 2005; 1(40):1411-1415.
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