DEEPSEN

DEEPSEN is a computational tool that utilizes convolutional neural networks to predict super-enhancers, clusters of highly active enhancers that regulate the expression of genes crucial for cell identity and implicated in various diseases, including cancer and Alzheimer's. Additionally, DEEPSEN identifies the most essential features for super-enhancer prediction, providing insights into the underlying biology.

Topic

Machine learning;Transcription factors and regulatory sites;Genetic variation;Protein interactions

Detail

  • Operation: Variant effect prediction;Pathway or network prediction

  • Software interface: Command-line user interface

  • Language: Shell,Python

  • License: Not stated

  • Cost: Free of charge

  • Version name: -

  • Credit: National Natural Science Foundation of China, National Key Research and Development Program of China, Shanghai Natural Science Foundation.

  • Input: -

  • Output: -

  • Contact: Jihong Guan jhguan@tongji.edu.cn

  • Collection: -

  • Maturity: -

Publications

  • DEEPSEN: a convolutional neural network based method for super-enhancer prediction.
  • Bu H, et al. DEEPSEN: a convolutional neural network based method for super-enhancer prediction. DEEPSEN: a convolutional neural network based method for super-enhancer prediction. 2019; 20:598. doi: 10.1186/s12859-019-3180-z
  • https://doi.org/10.1186/S12859-019-3180-Z
  • PMID: 31874597
  • PMC: PMC6929276

Download and documentation

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