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A field guide to cultivating computational biology.
Way, Gregory P; Greene, Casey S; Carninci, Piero; Carvalho, Benilton S; de Hoon, Michiel; Finley, Stacey D; Gosline, Sara J C; Lȇ Cao, Kim-Anh; Lee, Jerry S H; Marchionni, Luigi; Robine, Nicolas; Sindi, Suzanne S; Theis, Fabian J; Yang, Jean Y H; Carpenter, Anne E; Fertig, Elana J.
Affiliation
  • Way GP; Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America.
  • Greene CS; Center for Health AI, University of Colorado School of Medicine, Aurora, Colorado, United States of America.
  • Carninci P; Center for Health AI, University of Colorado School of Medicine, Aurora, Colorado, United States of America.
  • Carvalho BS; RIKEN Center for Integrative Medical Sciences Yokohama, Kanagawa, Japan.
  • de Hoon M; Human Technopole, Milan, Italy.
  • Finley SD; Department of Statistics, Institute of Mathematics, Statistics and Scientific Computing, University of Campinas, Campinas, Brazil.
  • Gosline SJC; RIKEN Center for Integrative Medical Sciences Yokohama, Kanagawa, Japan.
  • Lȇ Cao KA; Department of Biomedical Engineering, Quantitative and Computational Biology, and Chemical Engineering & Materials Science, University of Southern California, Los Angeles, California, United States of America.
  • Lee JSH; Pacific Northwest National Laboratory, Seattle, Washington, United States of America.
  • Marchionni L; Melbourne Integrative Genomics, School of Mathematics and Statistics, The University of Melbourne, Melbourne, Australia.
  • Robine N; Ellison Institute and Departments of Medicine/Oncology, Chemical Engineering, and Material Sciences, University of Southern California, Los Angeles, California, United States of America.
  • Sindi SS; Department of Pathology and Laboratory Medicine, Weill-Cornell Medicine, New York, New York, United States of America.
  • Theis FJ; Computational Biology Lab, New York Genome Center, New York, New York, United States of America.
  • Yang JYH; Department of Applied Mathematics, University of California Merced, Merced, California, United States of America.
  • Carpenter AE; Institute of Computational Biology, Helmholtz Center Munich and Department of Mathematics, Technical University of Munich, Munich, Germany.
  • Fertig EJ; Charles Perkins Centre and School of Mathematics and Statistics, The University of Sydney, Australia.
PLoS Biol ; 19(10): e3001419, 2021 10.
Article in En | MEDLINE | ID: mdl-34618807
Evolving in sync with the computation revolution over the past 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.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Computational Biology Type of study: Health_economic_evaluation Limits: Humans Language: En Journal: PLoS Biol Journal subject: BIOLOGIA Year: 2021 Type: Article Affiliation country: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Computational Biology Type of study: Health_economic_evaluation Limits: Humans Language: En Journal: PLoS Biol Journal subject: BIOLOGIA Year: 2021 Type: Article Affiliation country: United States