RT Journal Article
SR Electronic
T1 Advancing Computational Biology and Bioinformatics Research Through Open Innovation Competitions
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 565481
DO 10.1101/565481
A1 Andrea Blasco
A1 Michael G. Endres
A1 Rinat A. Sergeev
A1 Anup Jonchhe
A1 Max Macaluso
A1 Rajiv Narayan
A1 Ted Natoli
A1 Jin H. Paik
A1 Bryan Briney
A1 Chunlei Wu
A1 Andrew I. Su
A1 Aravind Subramanian
A1 Karim R. Lakhani
YR 2019
UL http://biorxiv.org/content/early/2019/03/01/565481.abstract
AB 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 where 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.