Publications and Research


Gil Alterovitz, Harvard Medical School
Dennis Dean, Seven Bridges
Carole Globe, University of Manchester
Michael R. Crusoe, Common Workflow Language Project
Stiam Soiland-Reyes, University of Manchester
Amanda Bell, George Washington University
Anais Hayes, George Washington University
Anita Suresh, Foundation for Innovative New Diagnostics
Anjan Purkkayastha, George Washington University
Charles H. King, George Washington University
Dan Taylor, Internet 2
Elaine Johanson, US Food and Drug Administration
Elaine E. Thompson, US Food and Drug Administration
Eric Donaldson, US Food and Drug Administration
Hiroki Morizono, Children’s National Medical Center
Hsinyi Tsang, National Cancer Institute
Jeet K. Vora, George Washington University
Jeremy Goecks, Oregon Health & Science University
Jianchao Yao, MRL IT, Merck & Co.
Jonas S. Almeida, SUNY Stony Brook
Jonathon Keeney, George Washington University
KanakaDurga Addepalli, Attain, McClean
Konstantinos Krampis, CUNY Hunter CollegeFollow
Krista M. Smith, George Washington University
Lydia Guo, Wellesley College
Mark Walderhaug, George Washington University
Marco Schito, Critical Path Institute
Matthew Ezewudo, Critical Path Institute
Nuria Guimera, DDL Diagnostic Laboratory
Paul Walsh, University College Dublin
Robel Kahsay, George Washington University
Srikanth Gottipati, OTSUKA Pharmaceutical Development & Commercialization
Timothy C. Rodwell, Foundation for Innovative New Diagnostics
Toby Bloom, New York Genome Center
Yuching Lai, DDL Diagnostic Laboratory
Vahan Simonyan, George Washington University
Raja Mazumder, George Washington University

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A personalized approach based on a patient's or pathogen’s unique genomic sequence is the foundation of precision medicine. Genomic findings must be robust and reproducible, and experimental data capture should adhere to findable, accessible, interoperable, and reusable (FAIR) guiding principles. Moreover, effective precision medicine requires standardized reporting that extends beyond wet-lab procedures to computational methods. The BioCompute framework ( enables standardized reporting of genomic sequence data provenance, including provenance domain, usability domain, execution domain, verification kit, and error domain. This framework facilitates communication and promotes interoperability. Bioinformatics computation instances that employ the BioCompute framework are easily relayed, repeated if needed, and compared by scientists, regulators, test developers, and clinicians. Easing the burden of performing the aforementioned tasks greatly extends the range of practical application. Large clinical trials, precision medicine, and regulatory submissions require a set of agreed upon standards that ensures efficient communication and documentation of genomic analyses. The BioCompute paradigm and the resulting BioCompute Objects (BCOs) offer that standard and are freely accessible as a GitHub organization ( following the “ principles for collaborative open standards development.” With high-throughput sequencing (HTS) studies communicated using a BCO, regulatory agencies (e.g., Food and Drug Administration [FDA]), diagnostic test developers, researchers, and clinicians can expand collaboration to drive innovation in precision medicine, potentially decreasing the time and cost associated with next-generation sequencing workflow exchange, reporting, and regulatory reviews.


This article was originally published in PLOS Biology, available at

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