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LECIF

Learning Evidence of Conservation from Integrated Functional genomic annotations

Software and Resources
  • CMImpute
  • CNEP
  • CSREP
  • ChromActivity
  • ChromGene
  • ChromHMM
  • ChromImpute
  • ChromTime
  • ConsHMM Atlas
  • ConsHMM
  • DREM
  • LECIF
  • Roadmap Enhancer-Gene Links
  • SEREND
  • SHARPR
  • STEM
  • χ-CNN
Illustrating of LECIF output.

LECIF is a supervised machine learning method that learns a genome-wide score of evidence for conservation at the functional genomics level.

Access the LECIF project on GitHub

Citation:
Kwon SB, Ernst J.
Learning a genome-wide score of human-mouse conservation at the functional genomics level.
Nature Communications, 12:2495, 2021.

Jason Ernst Research Lab
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UCLA Biological Chemistry
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Email: jason.ernst@ucla.edu
Phone: 310-825-3658

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