Advancing computational biology and bioinformatics research through open innovation competitions.
Journal
PloS one
ISSN: 1932-6203
Titre abrégé: PLoS One
Pays: United States
ID NLM: 101285081
Informations de publication
Date de publication:
2019
2019
Historique:
received:
08
04
2019
accepted:
22
08
2019
entrez:
28
9
2019
pubmed:
29
9
2019
medline:
17
3
2020
Statut:
epublish
Résumé
Open data science and algorithm development competitions offer a unique avenue for rapid discovery of better computational strategies. We highlight three examples in computational biology and bioinformatics research in which the use of competitions has yielded significant performance gains over established algorithms. These include algorithms for antibody clustering, imputing gene expression data, and querying the Connectivity Map (CMap). Performance gains are evaluated quantitatively using realistic, albeit sanitized, data sets. The solutions produced through these competitions are then examined with respect to their utility and the prospects for implementation in the field. We present the decision process and competition design considerations that lead to these successful outcomes as a model for researchers who want to use competitions and non-domain crowds as collaborators to further their research.
Identifiants
pubmed: 31560691
doi: 10.1371/journal.pone.0222165
pii: PONE-D-19-10061
pmc: PMC6764653
doi:
Substances chimiques
Antibodies
0
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.
Langues
eng
Sous-ensembles de citation
IM
Pagination
e0222165Subventions
Organisme : NHGRI NIH HHS
ID : U01 HG008699
Pays : United States
Organisme : NIAID NIH HHS
ID : UM1 AI100663
Pays : United States
Déclaration de conflit d'intérêts
The authors have declared that no competing interests exist.
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