Binary Phenotype Classification
Binary Phenotype Classification is a supervised machine learning task in computational biology that involves categorizing biological entities into one of two distinct phenotypic classes based on observed features or measurements.
23
Publications
1.3K
Citations
159
Authors
72
Institutions
Publications per year
2017–2026
12
23
Improving gene set analysis of microarray data by SAM-GS
Irina Dinu, John D. Potter, Thomas Mueller et al. · BMC Bioinformatics · 2007 · 263 citations · Full text
Emma K. Finlay, D.P. Berry, B. Wickham et al. · PLoS ONE · 2012 · 95 citations · Full text
Life Sciences, Biology, Genetics +17
1–5 of 23
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72

University of Colorado Denver
Denver, United States
2 h-index
3 publications
53 citations
Fred Hutch Cancer Center
Seattle, United States
2 h-index
2 publications
292 citations

University of Alberta
Edmonton, Canada
2 h-index
12 publications
2.5K citations
Scotland's Rural College
Edinburgh, United Kingdom
1 h-index
7 publications
420 citations

University of Amsterdam
Amsterdam, The Netherlands
1 h-index
3 publications
60 citations
Equilibrium Research
Bristol, United Kingdom
1 h-index
2 publications
22 citations
Kaiser Permanente
Oakland, United States
1 h-index
1 publications
58 citations
Indiana University School of Medicine
Indianapolis, United States
1 h-index
6 publications
300 citations
1–8 of 72
1 publications · 50 citations
1
h-index
1 publications · 10 citations
1
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1 publications · 11 citations
1
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1 publications · 12 citations
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1 publications · 21 citations
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