Multi-omics Prognostic Modeling

Multi-Omics Prognostic Modeling is a computational framework that integrates diverse omics data types to predict clinical outcomes by identifying molecular signatures associated with disease progression or treatment response.

81

Publications

5.6K

Citations

541

Authors

262

Institutions

Publications per year

2017–2026

76

Authors

541

  1. OP
    Olivier Poirion

    University of California San Diego, United States

    5 publications · 1.5K citations

    5

    h-index

  2. KC
    Kumardeep Chaudhary

    Institute of Microbial Technology, India

    5 publications · 1.5K citations

    5

    h-index

  3. SH
    Sijia Huang

    University of Hawaiʻi at Mānoa, United States

    2 publications · 316 citations

    2

    h-index

  4. LL
    Liangqun Lu

    University of Memphis, United States

    2 publications · 1.2K citations

    2

    h-index

  5. AI
    Ana I. Vázquez

    Michigan State University, United States

    2 publications · 74 citations

    2

    h-index

1–5 of 541

Venues

  1. Scientific Reports

    5 publications · 246 citations

    5

    h-index

  2. Bioinformatics

    5 publications · 180 citations

    5

    h-index

  3. Computers in Biology and Medicine

    5 publications · 307 citations

    4

    h-index

  4. Methods

    3 publications · 118 citations

    3

    h-index

  5. Frontiers in Genetics

    3 publications · 320 citations

    3

    h-index

1–5