Transcript Quantification

Transcript Quantification is the computational process of estimating the abundance levels of transcripts within a biological sample from high-throughput RNA sequencing data, distinguished from related analyses by its focus on assigning discrete expression values to full-length or assembled transcript isoforms rather than individual genes or exons.

470

Publications

151K

Citations

2.7K

Authors

903

Institutions

Publications per year

2017–2026

135

Authors

2.7K

  1. MI
    Michael I. Love

    University of North Carolina at Chapel Hill, United States

    13 publications · 21.5K citations

    13

    h-index

  2. RP
    Rob Patro

    Stony Brook University, United States

    9 publications · 14.6K citations

    9

    h-index

  3. CS
    Charlotte Soneson

    SIB Swiss Institute of Bioinformatics, Switzerland

    7 publications · 7.2K citations

    7

    h-index

  4. LP
    Lior Pachter

    University of California, Berkeley, United States

    7 publications · 13.1K citations

    7

    h-index

  5. RA
    Rafael A. Irizarry

    Johns Hopkins University, United States

    6 publications · 14.5K citations

    6

    h-index

1–5 of 2.7K

Venues

  1. BMC Genomics

    23 publications · 2.1K citations

    21

    h-index

  2. PLoS ONE

    25 publications · 2.1K citations

    21

    h-index

  3. Nucleic Acids Research

    23 publications · 36.6K citations

    19

    h-index

  4. Bioinformatics

    19 publications · 1.7K citations

    17

    h-index

  5. BMC Bioinformatics

    16 publications · 24.1K citations

    15

    h-index

1–5