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

Authors

2.8K

  1. YC
    Yu‐Dong Cai

    Shanghai University, China

    13 publications · 566 citations

    13

    h-index

  2. TH
    Tao Huang

    Shanghai Institutes for Biological Sciences, China

    13 publications · 539 citations

    13

    h-index

  3. LC
    Lei Chen

    Shanghai Maritime University, China

    10 publications · 411 citations

    10

    h-index

  4. XK
    Xiangyin Kong

    Shanghai Institutes for Biological Sciences, China

    7 publications · 324 citations

    7

    h-index

  5. YZ
    Yuhang Zhang

    Shanghai University, China

    6 publications · 236 citations

    6

    h-index

1–5 of 2.8K

Venues

  1. BMC Bioinformatics

    37 publications · 3.1K citations

    27

    h-index

  2. Bioinformatics

    30 publications · 4.5K citations

    23

    h-index

  3. PLoS ONE

    26 publications · 953 citations

    19

    h-index

  4. Scientific Reports

    19 publications · 616 citations

    15

    h-index

  5. IEEE Access

    14 publications · 720 citations

    14

    h-index

1–5