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Connection

Tina Pesaran to Bayes Theorem

This is a "connection" page, showing publications Tina Pesaran has written about Bayes Theorem.
Connection Strength

0.254
  1. A Bayesian framework for efficient and accurate variant prediction. PLoS One. 2018; 13(9):e0203553.
    View in: PubMed
    Score: 0.144
  2. A quantitative, Bayesian-informed approach to gene-specific variant classification: Updated Expert Panel recommendations improve classification of TP53 germline variants for Li-Fraumeni syndrome. Genome Med. 2025 10 22; 17(1):128.
    View in: PubMed
    Score: 0.059
  3. ClinGen guidance for use of the PP1/BS4 co-segregation and PP4 phenotype specificity criteria for sequence variant pathogenicity classification. Am J Hum Genet. 2024 01 04; 111(1):24-38.
    View in: PubMed
    Score: 0.052
Connection Strength

The connection strength for concepts is the sum of the scores for each matching publication.

Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.