Genomic Feature Selection
Genomic Feature Selection is a computational methodology that identifies and prioritizes biologically relevant genomic elements from high-dimensional datasets by distinguishing functional features from non-informative or redundant ones based on statistical, machine learning, or biological criteria.
651
Publications
35.4K
Citations
2.8K
Authors
1.1K
Institutions
Publications per year
2017–2026
297
651
BEDOPS: high-performance genomic feature operations
Shane Neph, Michael S. Kuehn, Alex Reynolds et al. · Bioinformatics · 2012 · 1.2K citations · Full text
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Chinese Academy of Sciences
Beijing, China
17 h-index
54 publications
2.8K citations

Shanghai University
Shanghai, China
16 h-index
38 publications
1.8K citations
Shanghai Institutes for Biological Sciences
Shanghai, China
15 h-index
47 publications
2.2K citations

Shanghai Maritime University
Shanghai, China
10 h-index
12 publications
509 citations
Harvard University
Cambridge, United States
10 h-index
21 publications
562 citations
The University of Tokyo
Tokyo, Japan
9 h-index
17 publications
1K citations
Texas A&M University
College Station, United States
9 h-index
11 publications
468 citations
University of Pennsylvania
Philadelphia, United States
9 h-index
27 publications
626 citations
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37 publications · 3.1K citations
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26 publications · 953 citations
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14 publications · 720 citations
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