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Cited by 8Genetics, Bioinformatics, and Biomedical ResearchInterdisciplinary Research and CollaborationDoctoral Education Challenges and Solutions

The DOI matches its Crossref record; 33 of the 33 references it cites were found in a registry or an index.

Graduate Training at the Interface of Computational and Experimental Biology: An Outcome Report from a Partnership of Volunteers between a University and a National Laboratory

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von Arnim, Albrecht G., Missra, Anamika·2017·CBE—Life Sciences Education
DOI 10.1187/cbe.17-02-0038PMC PMC5749963
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Abstract

Leading voices in the biological sciences have called for a transformation in graduate education leading to the PhD degree. One area commonly singled out for growth and innovation is cross-training in computational science. In 1998, the University of Tennessee (UT) founded an intercollegiate graduate program called the UT-ORNL Graduate School of Genome Science and Technology in partnership with the nearby Oak Ridge National Laboratory. Here, we report outcome data that attest to the program’s effectiveness in graduating computationally enabled biologists for diverse careers. Among 77 PhD graduates since 2003, the majority came with traditional degrees in the biological sciences, yet two-thirds moved into computational or hybrid (computational–experimental) positions. We describe the curriculum of the program and how it has changed. We also summarize how the program seeks to establish cohesion between computational and experimental biologists. This type of program can respond flexibly and dynamically to unmet training needs. In conclusion, this study from a flagship, state-supported university may serve as a reference point for creating a stable, degree-granting, interdepartmental graduate program in computational biology and allied areas.

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FIGURE 1. Medium-term career tracks of PhD alumni from GST 6–16 years after graduation. Of PhD alumni, 63% were in academia given the most recent data available (compare 43% nationwide), 19% in industry, 9% in government, 6% in science-related careers, and 3% in science-unrelated careers. None were known to be unemployed. Data are compared with national estimates from 2008 (Tilghman and Rockey, 2012). The GST data are from PhD graduates from 2000 to 2009.
FIGURE 1. Medium-term career tracks of PhD alumni from GST 6–16 years after graduation. Of PhD alumni, 63% were in academia given the most recent data available (compare 43% nationwide), 19% in industry, 9% in government, 6% in science-related careers, and 3% in science-unrelated careers. None were known to be unemployed. Data are compared with national estimates from 2008 (Tilghman and Rockey, 2012). The GST data are from PhD graduates from 2000 to 2009.CC BY-NC-SA · PubMed Central
FIGURE 2. Career transitions for alumni from the GST program (left) and BCMB (right). For each program, the left column shows the sector of the graduate's first position after PhD and the right column shows a subsequent position, usually the second position. The numbers reflect numbers of individuals, not percentages; note that about half of the alumni have not yet moved into a second position. Transitions from one sector to another are depicted by arrows; the flux is indicated by the number of individuals and line thickness.
FIGURE 2. Career transitions for alumni from the GST program (left) and BCMB (right). For each program, the left column shows the sector of the graduate's first position after PhD and the right column shows a subsequent position, usually the second position. The numbers reflect numbers of individuals, not percentages; note that about half of the alumni have not yet moved into a second position. Transitions from one sector to another are depicted by arrows; the flux is indicated by the number of individuals and line thickness.CC BY-NC-SA · PubMed Central

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Citations

Cites

Research works printed but not linked: 7

  1. Griffiths P. A., 1995, Reshaping the graduate education of scientists and engineers
  2. Hogan A., 2015, Monthly Labor Reviews, 1
  3. Johnson C. Y., 2014, Boston Globe, A-1
  4. Kuehnle K., 2009, Swiss Medical Weekly, 139, 540
  5. Lacey T. A., 2009, Monthy Labor Reports, 132, 82
  6. Teitelbaum M. S., 2014, The Atlantic
  7. Yamamoto K., 2014, iBiomagazine

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Metadata

Authors
von Arnim, A. G., & Missra, A.
Affiliations
Oak Ridge National Laboratory (US)
Corresponding author
von Arnim, Albrecht G.
ORCID
von Arnim, Albrecht G.
Venue
CBE—Life Sciences Education
Publisher
American Society for Cell Biology (ASCB)
Published
2017-12
Volume
16
Issue
4
Pages
ar61
ISSN
1931-7913 (ISSN-L)
DOI
10.1187/cbe.17-02-0038
PMC
PMC5749963
OpenAlex
W2770242051
Cited by
8
References
33
Citations by year
2026: 1 · 2024: 1 · 2023: 1 · 2021: 3 · 2019: 2
FWCI
0.22
Type
journal article
Language
en
Open access
Licence
cc-by-nc-sa
Locations
  • CBE—Life Sciences Education (publishedVersion, cc-by-nc-sa)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by-nc-sa)
  • PubMed Central (publishedVersion, cc-by-nc-sa)
  • PubMed (publishedVersion)
  • OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion)
Funders
  • National Science Foundation (1546402, 1456988)
  • National Institutes of Health
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genetics, Bioinformatics, and Biomedical Research
  • Social Sciences › Arts and Humanities › History and Philosophy of Science › Interdisciplinary Research and Collaboration
  • Social Sciences › Education › Doctoral Education Challenges and Solutions
Keywords
computational biology education, graduate education, doctoral programs, curriculum development, career outcomes, Oak Ridge National Laboratory, University of Tennessee
MeSH terms
Career Choice, Cooperative Behavior, Curriculum, Demography, Education, Graduate, Female, Humans, Laboratories, Male, Universities, Volunteers, Computational Biology, Research Report

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