Time-series Transcriptomics

Time-Series Transcriptomics is a specialized approach within bulk transcriptomics that involves the systematic collection and analysis of gene expression data across multiple sequential time points to capture dynamic changes in transcriptional activity over time.

104

Publications

7.5K

Citations

420

Authors

198

Institutions

Publications per year

2017–2026

35

Authors

420

  1. ZB
    Ziv Bar‐Joseph

    Carnegie Mellon University, United States

    9 publications · 2.4K citations

    9

    h-index

  2. SC
    Sara C. Madeira

    University of Lisbon, Portugal

    5 publications · 284 citations

    5

    h-index

  3. IS
    Itamar Simon

    Hebrew University of Jerusalem, Israel

    3 publications · 404 citations

    3

    h-index

  4. AL
    Arlindo L. Oliveira

    Instituto de Engenharia de Sistemas e Computadores Investigação e Desenvolvimento, Portugal

    3 publications · 241 citations

    3

    h-index

  5. TJ
    Tommi Jaakkola

    Massachusetts Institute of Technology, United States

    3 publications · 405 citations

    3

    h-index

1–5 of 420

Venues

  1. Bioinformatics

    22 publications · 1.5K citations

    17

    h-index

  2. BMC Bioinformatics

    15 publications · 2.1K citations

    14

    h-index

  3. PLoS Computational Biology

    6 publications · 430 citations

    6

    h-index

  4. Scientific Reports

    5 publications · 240 citations

    5

    h-index

  5. Proceedings of the National Academy of Sciences

    PNAS · 4 publications · 440 citations

    4

    h-index

1–5