Biomedical and Translational Informatics Laboratory

Anni Moore

  Graduate Student

  A301 Richards Building 
  3700 Hamilton Walk, Philadelphia, PA 19104

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  Github

  Linkedin

 

 

 

  

Current Projects

  • Using genomic, expression, and EHR data to build pipelines investigating human disease associations

Education

  • University of Pennsylvania, Philadelphia, PA 2021 – Present
    PhD Student in Genomics and Computational Biology
  • B.S. in Biology, 2019
    University of Virginia, Charlottesville, VA

Work Experience

  • Post-baccalaureate IRTA Fellow 2019 – 2021
    Computational Biology Group
    Lab of Neurogenetics
    NIH/NIA
    Bethesda, MD
  • Computational Research Assistant 2018-2019
    Danna and Pearson Labs
    University of Virginia
    Charlottesville, VA
  • Bioinformatics Intern 2018
    Translational Sciences Group
    Sanofi
    Framingham, MA

Publications:

For the list of my publications please visit Google Scholar

 

Chris Jones

  Graduate Student 

  A301 Richards Building 
  3700 Hamilton Walk, Philadelphia, PA 19104

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Current Projects

I am interested in leveraging human genomic diversity, multi-omics data, and phenotypic data such as electronic health records (EHR) to investigate the role of genomic variation in immune-related traits.

Education

  • University of Pennsylvania, Philadelphia, PA 2021 - Present
    Ph.D. Genomics and Computational Biology
  • Johns Hopkins University, Baltimore, MD 2019 - 2021
    MS, Bioinformatics
  • Dickinson College, Carlisle, PA 2015 - 2019
    BS. Biology & Computer Science

Work Experience

  • GeneOne Life Science, Fort Washington, PA 2019 - 2021
    Clinical Scientist, Clinical Development Group
  • Monell Chemical Senses Center, Philadelphia, PA 2019 - 2021
    Visiting Scientist, Lab of Danielle Reed, PhD.

Publications:

 

Daniel Hui

 Graduate Student

  A301 Richards Building 
  3700 Hamilton Walk, Philadelphia, PA 19104

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Current Projects

I am interested in the genetic basis for human traits and diseases, with a focus on cardiometabolic diseases and related anthropometric traits. I am especially interested in using individuals from diverse ancestry and environment in order to facilitate discovering and quantifying the effects of different genetic loci. I hope the research I conduct will improve human health for populations all around the world, especially for conditions that have a large healthcare burden and are significantly genetic in their etiology. 

Education

  • University of Pennsylvania, PhD Genomics and Computational Biology, 2019-Present
  • University of Pittsburgh, B.S. Computer Science,  2013-2017

Research Experience

  •  Graduate Research Assistant, University of Pennsylvania, Perelman School of Medicine, Fall 2019 - Present. Advisors: Drs. Marylyn Ritchie and Sarah Tishkoff
  • Bioinformatician, Brigham and Women's Hospital, Harvard Medical School, The Broad Institute, September 2019-May 2019
  • Undergraduate Research Assistant, Children's Hospital of University of Pittsburgh Medical Center, University of Pittsburgh, May 2014-May 2017

Publications:

For the list of my publications please visit Google Scholar

David Zhang

  Graduate Student 

  A301 Richards Building 
  3700 Hamilton Walk, Philadelphia, PA 19104

  This email address is being protected from spambots. You need JavaScript enabled to view it.

  Twitter

  GitHub

  LinkedIn

 

 

Current Projects

  • Computational genetics, biomedical informatics, disease pathophysiology

Education

  • Perelman School of Medicine, Philadelphia, PA 2020 - Present
    MD-PhD Candidate in Genomics and Computational Biology
  • Cornell University, Ithaca, NY 2020
    B.A. in Biology, Computer Science 

Work Experience

  • Harvard Summer Institute in Biomedical Informatics (Kohane Lab) - Summer 2018
  • Summer Research Intern (Brigham Genomic Medicine group) - Summer 2017

Publications:

For the list of my publications please visit Google Scholar

 

Karl Keat

  Graduate Student 

  A301 Richards Building 
  3700 Hamilton Walk, Philadelphia, PA 19104

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  Twitter

  ORCID

  GitHub

  LinkedIn

Current Projects

  • Using genomics, machine learning, and multi-omics data to improve drug response prediction and precision medicine.

Education

  • University of Pennsylvania, Philadelphia, PA 2020 – Present
    PhD Candidate in Genomics and Computational Biology
  • University of Virginia, Charlottesville, VA 2020
    B.A. in Biology, Computer Science

Work Experience

  • Harvard Summer Institute in Biomedical Informatics (Sunyaev Lab) - Summer 2019
  • Broad Summer Research Program (Regev Lab) - Summer 2018
  • TecBio REU at The University of Pittsburgh (Cooper Lab) - Summer 2017
  • NIH Summer Internship Program (Baxevanis Lab) - Summer 2015, 2016

Publications:

For the list of my publications please visit Google Scholar

 

Rachit Kumar

 Graduate Student

  A301 Richards Building 
  3700 Hamilton Walk, Philadelphia, PA 19104

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  Github           

  Website

  Google Scholar

 

Current Projects

  • Incorporation of domain knowledge in a domain-agnostic way using network representations of data and known relationships
  • Developing methods of representing patients that allow us to identify treatment plans for individual patients
  • Using machine learning and deep learning to improve clinical and basic science understanding through rigorous hypothesis generation from preexisting data

Education

  • MD-PhD, University of Pennsylvania, 08/2020-Present

Doctor of Medicine, Perelman School of Medicine, University of Pennsylvania, 08/2020-Present

Doctor of Philosophy, Genomics and Computational Biology, University of Pennsylvania, 08/2022-Present

  • B.S. in Biomedical Engineering, Georgia Institute of Technology, 08/2016-05/2020
 

 Work Experience

 Publications 

For the list of my publications please visit Google Scholar 

 

Rasika Venkatesh

  Graduate Student

  A301 Richards Building 
  3700 Hamilton Walk, Philadelphia, PA 19104

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  LinkedIn 

  Github

 

 

 

Current Projects

  • Utilizing machine learning and statistical methods for the integration multiple data modalities to improve risk prediction of complex diseases

Education

  • University of Pennsylvania, PhD Genomics and Computational Biology, 2022 - Present
    Pursuing a Dual MA in Statistics and Data Science
  • University of California Davis, B.S. Biotechnology - Bioinformatics, 2017 - 2021

Work Experience

  • Bioinformatics Research Specialist - Carvajal-Carmona Lab (2020 - 2022)
    UC Davis Genome Center, Davis CA
  • Bio-Development Sequencing Intern - Cepheid (2020 - 2021)
    Cepheid, Sunnyvale CA
  • Assay Development Intern - Roche R&D (2019 - 2019)
    Roche Sequencing Solutions, Pleasanton CA
  • Research Assistant - Wiltgen Lab (2018 - 2021)
    UC Davis Center for Neuroscience, Davis CA

Publications:

For the list of my publications please visit Google Scholar

Van Truong

 Graduate Student

  Co-Mentored by Dr. Marylyn Ritchie and Dr. John Wherry

  A301 Richards Building 
  3700 Hamilton Walk, Philadelphia, PA 19104

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Current Projects

My primary research interests are in knowledge representation in immunology. My current research focuses on developing an immune-focused ontology and high-quality knowledge graph for autoimmunity from heterogeneous multi-omics databases. I am passionate about data integration, structuring information into explicit reasoning, improving the machine-readability of heterogeneous data, and developing user-friendly tools for computational immunology.

My interests outside of science include mountain biking, rock climbing, ultimate frisbee, camping, cooking, foraging, freelance scientific illustration, designing interactive art sculptures, and serving as the Executive Director of Village Bridges, a social impact organization I co-founded with a team of young women from my village to serve our Vietnamese diaspora community. 

Education

8/2020 – Present, University of Pennsylvania (Philadelphia, PA)
  • PhD Genomics & Computational Biology, Perelman School of Medicine
  • MA Statistics (Dual-Degree), Dept. of Statistics & Data Science, Wharton School of Business
8/2018 – 5/2020, Johns Hopkins University (Baltimore, MD)
  • MS Biotechnology, Concentrations in Bioinformatics and Molecular Targets & Drug Discovery
6/2017 – 6/2018, Virginia Tech (Blacksburg, VA)
  • Postbac Research Education Program,  NIGMS/NIH R25 Training Program, Concentration: Computational Epidemiology
8/2013 – 4/2017, University of Florida (Gainesville, FL)
  • BA Anthropology, Concentrations: Cultural and Biological Anthropology

 Work Experience

  • National Cancer Institute, 2018-2022
    Biotechnology Fellow
  • Women In Bio Non-Profit, 2019-2020
    Sponsorship Chair
  • Harvard University, 2018
    Irene and Eric Simon Foundation Fellow
  • Harvard T.H. Chan School of Public Health, 2018
    Biostatistics Research Intern
  • Virginia Tech, 2017-2018
    PREP (Post-bac Research Education Program) Fellow

 Publications 

  • Van Q. Truong*, Jakob A. Woerner*, Tess A. Cherlin*, Yuki Bradford, Daniel H. Hui, Anastasia M. Lucas, Manu K. Shivakumar, Rachit Kumar, Milton Pividori, Chelsea C. Okeh, S. Chris Jones, Abigail C. Bossa, Stephen D. Turner, Marylyn D. Ritchie and Shefali S. Verma. Quality Control Procedures for Genome-Wide Association Studies. Curr Protoc Hum Genet. (2022) *Denotes equal first-author contributions
  • Momchil S. Tomov, Van Q. Truong, Rohan A. Hundia, Sam J. Gershman. Dissociable Neural Correlates of Uncertainty Underlie Different Exploration Strategies. Nature Communications, (2020). DOI: 10.1038/s41467-020-15766-z.
  • Marshall Goodwin, Cara L. Croft, Hunter S. Futch, Daniel Ryu, Carolina Ceballos-Diaz, Xuefei Liu, Giavanna Paterno, Catalina Mejia, Doris Deng, Kimberly Menezes, Laura Londono, Kefren Arjona, Mary Parianos, Van Truong, Eva Rostonics, Amanda Hernandez, Sanford L. Boye, Shannon E. Boye, Yona Levites, Pedro E. Cruz, Todd E. Golde. Utilizing minimally purified secreted rAAV for rapid and cost-effective manipulation of gene expression in the CNS. BMC Molecular Neurodegeneration, 15:15 (2020). DOI: 10.1186/s13024-020-00361-z.
  • Hunter S. Futch, Cara L. Croft, Van Q. Truong, Eric G. Krause, Todd E. Golde. Targeting psychological stress signaling pathways in Alzheimer's disease. BMC Molecular Neurodegeneration, Volume 12, Number 1, Page 1 (2017). DOI: 10.1186/s13024-017-0190-z
  • William Brewer, Yan Xin, Chris Hatem, David Diercks, Van Truong, Kevin Jones. Lateral GE Diffusion During Oxidation of Si/SiGe Fins. Nano Letters, 2017, 12 (4), pp 2159-2164. DOI: 10.1021/acs.nanolett.6b04407
  • A. G. Lind, T. P. Martin Jr., V. C. Sorg, E. L. Kennon, V. Q. Truong, H. L. Aldridge, C. Hatem, M. O Thompson, K. S. Jones. Activation of Si Implants Into InAs Characterized by Raman Scattering. Journal of Applied Physics, 119, 095705 (2016). DOI: 10.1063/1.4942880
Editorials
  • Moore, J.H., Truong, V.Q., Robbins, A.B., Nicholson, D., Williams-Devane, CL. Ten important roles for academic leaders to promote equity, diversity, and inclusion in data science. BioData Mining 14, 22 (2021).
  • Van Truong. “Beyond Zoom: Virtual Gathering Spaces for the Holidays and Beyond” ExtremeTech. (2020)