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Rule Based Learning for Transcriptional Regulation

This is the GitHub repo for the hackseq19 project: Rule Based Learning for Transcriptional Regulation! Our goals during hackseq19 are to:
  • a) Build an accurate classifier for a given gene regulation dataset.
  • b) Build an interpretable classifier that outputs useful rules, describing each dataset.

Our leaderboard page is available here. You are required to sign in using your Google account. Once signed in, you can choose your username and submit files to the leaderboard. The leaderboard is based on a hacked version of my Natural Language Processing course professor's website.

Datasets:

  • 1 Human Chromosome #1 TFBS
  • 1 Ecoli K12 TFBS
  • 2 Ecoli K12 Promoter Region
  • 1 Pokemon

These come from a variety of sources, including gene regulation databases and previous Kaggle competitions.

Team Lead:
Alex Sweeten

Participants:
Aris Grout

Chahat Upreti

Jade Chen

Kate Gibson

Oriol Fornes

Priyanka Mishra

Shawn Hsueh

Zakhar Krekhno

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Repo for the hackseq19 project "Rule Based Learning for Transcriptional Regulation"

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  • Jupyter Notebook 92.0%
  • Python 8.0%