Computational Feature Extraction

Computational Feature Extraction is a systematic method within single-cell metabolomics that identifies and isolates quantifiable molecular signals from complex raw data through algorithmic processing, distinguishing itself by enabling high-resolution metabolic characterization at the individual cell level.

268

Publications

14.9K

Citations

1.1K

Authors

467

Institutions

Publications per year

2017–2026

129

Authors

1.1K

  1. QZ
    Quan Zou

    University of Electronic Science and Technology of China, China

    3 publications · 205 citations

    3

    h-index

  2. NS
    Natalie Shih

    University of Pennsylvania, United States

    2 publications · 451 citations

    2

    h-index

  3. MK
    Masashi Koga

    Hitachi (Japan), Japan

    2 publications · 116 citations

    2

    h-index

  4. LC
    Lei Chen

    Shanghai Maritime University, China

    2 publications · 75 citations

    2

    h-index

  5. SY
    Shihui Ying

    Shanghai University, China

    2 publications · 247 citations

    2

    h-index

1–5 of 1.1K

Venues

  1. IEEE Access

    8 publications · 677 citations

    8

    h-index

  2. Bioinformatics

    7 publications · 275 citations

    7

    h-index

  3. arXiv (Cornell University)

    Repository · 4 publications · 58 citations

    5

    h-index

  4. PLoS ONE

    4 publications · 191 citations

    5

    h-index

  5. 4

    h-index

1–5