Systems-level Functional Annotation

Systems-Level Functional Annotation is a systematic approach to functional genomics that integrates diverse biological data types across molecular, cellular, and organismal scales to infer the functional roles of genes and proteins within the context of complex biological systems, distinguishing it from gene- or pathway-centric annotation methods by emphasizing emergent properties and network-level interactions.

16

Publications

17.1K

Citations

186

Authors

70

Institutions

Publications per year

2017–2026

5

Authors

186

  1. MS
    M Snyder

    Stanford University, United States

    3 publications · 495 citations

    3

    h-index

  2. JC
    Juan Carlos Rivera‐Mulia

    Florida State University, United States

    2 publications · 200 citations

    2

    h-index

  3. DM
    David M. Gilbert

    Florida State University, United States

    2 publications · 200 citations

    2

    h-index

  4. PJ
    Peng Jiang

    Dana-Farber Cancer Institute, United States

    2 publications · 200 citations

    2

    h-index

  5. SK
    Sumit K. Chanda

    Sanford Burnham Prebys Medical Discovery Institute, United States

    2 publications · 15.8K citations

    2

    h-index

1–5 of 186

Venues

  1. PLoS ONE

    2 publications · 51 citations

    2

    h-index

  2. Nature Chemical Biology

    2 publications · 268 citations

    2

    h-index

  3. Nature Communications

    2 publications · 15.8K citations

    2

    h-index

  4. Neural Computing and Applications

    1 publications · 16 citations

    1

    h-index

  5. Proceedings of the National Academy of Sciences

    PNAS · 1 publications · 35 citations

    1

    h-index

1–5