A field guide to cultivating computational biology

Gregory P. Way, Casey S. Greene, Piero Carninci, Benilton S. Carvalho, Michiel de Hoon, Stacey Finley, Sara J.C. Gosline, Kim Anh Le Cao, Jerry S.H. Lee, Luigi Marchionni, Nicolas Robine, Suzanne S. Sindi, Fabian J. Theis, Jean Y.H. Yang, Anne E. Carpenter, Elana J. Fertig

Research output: Contribution to journalReview articlepeer-review

Abstract

Evo:lvPinlegaisnecsoynnfcirwmitthhatthalelhceoamdipnugtleavtieolnsarreevreopluretisoenntoevdecor rtrheectplya:st 30 years, computational biology has emerged as a mature scientific field. While the field has made major contributions toward improving scientific knowledge and human health, individual computational biology practitioners at various institutions often languish in career development. As optimistic biologists passionate about the future of our field, we propose solutions for both eager and reluctant individual scientists, institutions, publishers, funding agencies, and educators to fully embrace computational biology. We believe that in order to pave the way for the next generation of discoveries, we need to improve recognition for computational biologists and better align pathways of career success with pathways of scientific progress. With 10 outlined steps, we call on all adjacent fields to move away from the traditional individual, single-discipline investigator research model and embrace multidisciplinary, data-driven, team science.

Original languageEnglish (US)
Article numbere3001419
JournalPLoS biology
Volume19
Issue number10
DOIs
StatePublished - Oct 2021

ASJC Scopus subject areas

  • Neuroscience(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Immunology and Microbiology(all)
  • Agricultural and Biological Sciences(all)

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