Iterative Profile Refinement

Iterative Profile Refinement is a computational method in the context of Profile Hidden Markov Models that progressively enhances the alignment and parameter estimation of the model by successively retraining on updated sequence alignments to improve sensitivity and specificity in remote homology detection.

3

Publications

551

Citations

6

Authors

3

Institutions

Publications per year

2017–2026

0

Authors

6

  1. MK
    Michael K. Chan

    The Ohio State University, United States

    1 publications · 31 citations

    1

    h-index

  2. MM
    Marianne M. Lee

    Chinese University of Hong Kong, Hong Kong SAR China

    1 publications · 31 citations

    1

    h-index

  3. LH
    Liisa Holm

    University of Helsinki, Finland

    1 publications · 340 citations

    1

    h-index

  4. AH
    Andreas Heger

    University of Oxford, United Kingdom

    1 publications · 340 citations

    1

    h-index

  5. LA
    L. Aravind

    National Center for Biotechnology Information, United States

    1 publications · 180 citations

    1

    h-index

1–5 of 6

Venues

  1. Bioinformatics

    1 publications · 31 citations

    1

    h-index

  2. Proteins Structure Function and Bioinformatics

    1 publications · 340 citations

    1

    h-index

  3. PubMed

    Repository · 1 publications · 180 citations

    1

    h-index

  4. In Silico Biology

    ISB · 1 publications · 76 citations

1–4