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  • Dana-Farber Cancer Institute
  • Boston, MA

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  1. deepDegron Public

    Deep learning model to predict degron sequences

    Python 19 8

  2. KarchinLab/2020plus Public

    Classifies genes as an oncogene, tumor suppressor gene, or as a non-driver gene by using Random Forests

    Python 49 17

  3. KarchinLab/probabilistic2020 Public

    Simulates somatic mutations, and calls statistically significant oncogenes and tumor suppressor genes based on a randomization-based test

    Python 8 5

  4. KarchinLab/cancerSeqStudy Public

    Analysis of statistical power and false positives for cancer exome sequencing studies

    R 3 3

  5. KarchinLab/CHASMplus Public

    Predicts which missense mutations will drive growth of human cancers

    Python 11 3

  6. KarchinLab/HotMAPS_2016 Public

    Detects hotspot regions for somatic mutations in 3D protein structures

    Python 2

14 contributions in the last year

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March 2025

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