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Bioinformatics Research and Training at UTEP

College of Science. Bioinformatics. www.bioinformatics.utep.edu. The University of Texas at El Paso. Bioinformatics Research and Training at UTEP. Ming-Ying Leung, Ph.D. Professor, Department of Mathematical Sciences and Director, Bioinformatics and Computational Science Programs

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Bioinformatics Research and Training at UTEP

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  1. College of Science Bioinformatics www.bioinformatics.utep.edu The University of Texas at El Paso Bioinformatics Research and Training at UTEP Ming-Ying Leung, Ph.D. Professor, Department of Mathematical Sciences and Director, Bioinformatics and Computational Science Programs Director, Bioinformatics Core Facility Border Biomedical Research Center (BBRC) The University of Texas at El Paso, El Paso, Texas

  2. College of Science Bioinformatics www.bioinformatics.utep.edu The University of Texas at El Paso Bioinformatics Program • Interdisciplinary program supported by departments of • Biological Sciences • Chemistry • Computer Science • Mathematical Sciences • With 24 faculty and staff members from the Colleges of Science, Engineering, and Health Sciences.

  3. Bioinformatics Faculty and Staff • Biological Sciences:Steve Aley, Igor Almeida, Sid Das, Krinstine Garza, Kyle Johnson, Carl Lieb, Vanessa Lougheed, Elizabeth Walsh, Jianying Zhang • Chemistry:James Becvar, Ricardo Bernal, Mahesh Narayan, Chuan Xiao • Clinical Laboratory Science:Delfina Dominguez • Computer Science:Martine Ceberio, Olac Fuentes, VladikKreinovich, • Electrical and Computer Engineering:Wei Qian • Mathematical Sciences:Art Duval, HamideDogan, Ming-Ying Leung, NaijunSha • Staff:OlianaAlikaj, Gerardo Cardenas

  4. Program Goals 1. Training • NSF-Funded Undergraduate Participation in Bioinformatics Training (UPBiT) • Professional Science Master (PSM) degree in Bioinformatics • Computational Bioscience for Ph.D. in Computational Science

  5. Program Goals 2. Research • Biomolecular Sequence Analysis • Ecoinformatics and Phylogenetics • Medical Imaging Informatics • Molecular Structure and Dynamics • Proteomics Data Analysis

  6. Students and Graduates Current students and trainees: 16 Undergrad trainees in UPBiT, 16 M.S. , and 4 Ph.D. students in computational bioscience.

  7. Students and Graduates Over 50 graduates working at: • Academic Institutions (e.g., Stanford, Vanderbilt, Texas Tech., UTEP) • Research Labs (e.g., Broad Inst., Whitehead Inst., M.D. Anderson) • Government agencies (e.g., NIH, USDA, USAMRIID) • Industry (Pfizer, Monsanto)

  8. Undergraduate Participation in Bioinformatics Training (UPBiT)

  9. NIH-Funded Bioinformatics Core Facility in theBorder Biomedical Research Center (BBRC) Analytical Cytology Cell Culture Biomolecule Analysis DNA Analysis Study Design & Data Analysis Integrate Computational & Experimental Approaches e.g., RNA structure prediction Statistical Bioinformatics Statistical Consulting Lab e.g., data mining Bioinformatics Computing Lab

  10. BBRC Bioinformatics Core Facility • Bioinformatics Computing Lab • Translational Bioinformatics Lab • Structural Bioinformatics Lab

  11. Specific Aims for Bioinformatics Core Facility Provide bioinformatics support to biomedical research: • Supporting BBRC research clusters throughcomputational modeling, data management and interpretations, to final production of and dissemination bioinformatics tools. • Interfacing with other BBRC core facilities by establishing protocols and operation manuals integrating computational components in the experimental procedure. • Providing consulting services for non-BBRC researchers, strengthening collaborative efforts for interdisciplinary research in the border region. 11

  12. Computing Resources Development Plan

  13. Connection with Other BBRC Units

  14. Software Development • RNAVLab: Virtual laboratory for RNA sequence analysis and secondary structure prediction (with DNA sequencing core) • RNASSA: RNA Secondary Structure Analysis • InversFinder: Finding inversions • Segmenta: RNA Segmentation • Grid and Cloud Computing • Post-translational modification studies (with Biomolecular Characterization Core) • GPI and GPI-anchored protein structure prediction based on mass spectrometry data (in collaboration with Dr. Clemente Aguilar, National Institute of Mathematical and Biological Synthesis) • ISOGlyP (Isoform Specific O-Glycosylation Prediction) (with Dr. Thomas Gerken as PI, submitted R01 in January 2014) 14

  15. Glycosylation Site Prediction Software (isoglyp.utep.edu) 15

  16. Protein Structure, Dynamics and Interactions • Establish a standard toolset on Bioinformatics Grid to facilitate the workflow for computational prediction of protein structures, interactions, and docking models. • Current BBRC projects include: • Searching for cancer-related interactors for tumor-associated antigens from Human Protein Reference Database (HPRD) and other sources. • In silico design of nociceptin agonists for Post-Traumatic Stress Disorder (PTSD) through halogen bonding. Poster to be presented by Dr. Mahesh Narayan at the Advancing Computational Biology @ Howard University Symposium. 16

  17. Sequence Analysis Projects • Motif detection to identify potential enhancer elements critical for learning and memory (led by Dr. K. Han) • GPCR prediction and vaccine development (Collaboration with Dr. Felix Guerrero of the USDA-ARS and Dr. Kyle Johnson, funded by the USDA-HSI Program) • Functional genomic analysis of high-risk childhood leukemia (BBRC pilot project, led by Dr. Jeremy Ross)

  18. Pilot Project: Functional Genomic Analysis of High-Risk Childhood Leukemia Relevance to Health Disparities: Hispanic children have the highest rates of incidence and death from acute lymphoblastic leukemia (ALL) in the U.S. Major Objective:Provide significant insight into the genetic abnormalities driving ALL tumor cell growth and drug resistance in the Hispanic population. Approach: 1) Identify protein-encoding somatic mutations using whole-exome sequencing of DNA isolated from an Hispanic pediatric leukemia patient cohort of new onset or relapsed ALL. 2) Develop and employ a pathway-based computational pipeline to prioritize functionally relevant sequence variants and aid biological interpretation. Project Highlight - BBRC “OncoMiner” Pipeline

  19. Future Plan • Continue to strengthen bioinformatics support to genomics and proteomics data analysis. • Expand software development capabilities for biomedical informatics and translational bioinformatics research. • Create portals from Bioinformatics Grid to high performance computing platforms at UTEP and TACC, and the RTRN Data Coordinating Center. • Explore further training and professional opportunities for students and graduates of the program

  20. College of Science Bioinformatics www.bioinformatics.utep.edu The University of Texas at El Paso Contact Us Email: bioinformatics@utep.edu Web: www.bioinformatics.utep.edu Facebook: www.facebook.com/Bioinformatics.UTEP Phone: 915.747.8484

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