Diversifying the Genomic Data Science Research Community

Network, The Genomic Data Science Community, Alcazar, Rosa, Alvarez, Maria, Arnold, Rachel, Ayalew, Mentewab, Best, Lyle G, Campbell, Michael C, Chowdhury, Kamal, Cox, Katherine EL, Daulton, Christina, Deng, Youping, Easter, Carla, Fuller, Karla, Hakim, Shazia Tabassum, Hoffman, Ava M, Kucher, Natalie, Lee, Andrew, Lee, Joslynn, Leek, Jeffrey T, Meller, Robert, Méndez, Loyda B, Méndez-González, Miguel P, Mosher, Stephen, Nishiguchi, Michele, Pratap, Siddharth, Rolle, Tiffany, Roy, Sourav, Saidi, Rachel, Schatz, Michael C, Sen, Shurjo, Sniezek, James, Martinez, Edu Suarez, Tan, Frederick, Vessio, Jennifer, Watson, Karriem, Westbroek, Wendy, Wilcox, Joseph, Xie, Xianfa (January 2022) Diversifying the Genomic Data Science Research Community. (Submitted)

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Over the last 20 years, there has been an explosion of genomic data collected for disease association, functional analyses, and other large-scale discoveries. At the same time, there have been revolutions in cloud computing that enable computational and data science research, while making data accessible to anyone with a web browser and an internet connection. However, students at institutions with limited resources have received relatively little exposure to curricula or professional development opportunities that lead to careers in genomic data science. To broaden participation in genomics research, the scientific community needs to support students, faculty, and administrators at Underserved Institutions (UIs) including Community Colleges, Historically Black Colleges and Universities, Hispanic-Serving Institutions, and Tribal Colleges and Universities in taking advantage of these tools in local educational and research programs. We have formed the Genomic Data Science Community Network (this http URL) to identify opportunities and support broadening access to cloud-enabled genomic data science. Here, we provide a summary of the priorities for faculty members at UIs, as well as administrators, funders, and R1 researchers to consider as we create a more diverse genomic data science community.

Item Type: Paper
Subjects: bioinformatics
bioinformatics > genomics and proteomics > genetics & nucleic acid processing
bioinformatics > genomics and proteomics
bioinformatics > genomics and proteomics > genetics & nucleic acid processing > genomes
CSHL Authors:
Communities: CSHL labs > Schatz lab
SWORD Depositor: CSHL Elements
Depositing User: CSHL Elements
Date: 20 January 2022
Date Deposited: 11 Oct 2023 17:37
Last Modified: 16 Jan 2024 20:41
Related URLs:
URI: https://repository.cshl.edu/id/eprint/41198

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