PEP specifications

Unique identifier:
OMICS_25734
Software type:
Toolkit/Suite
Restrictions to use:
None
Programming languages:
Python
Computer skills:
Advanced
Requirements:
XGBoost, scikit-learn, pandas, numpy, gensim
Name:
Predict Enhancer-Promoter
Interface:
Command line interface
Operating system:
Unix/Linux
License:
MIT License
Stability:
Stable
Maintained:
Yes

versioning

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PEP distribution

download

PEP support

Documentation

Maintainer

  • Jian Ma <>

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Credits

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Publications

Institution(s)

Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA; Department of Automation, Tsinghua University, Beijing, China; Machine Learning Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA

Funding source(s)

Supported by National Institutes of Health grant HG007352 and National Science Foundation grants 1054309 and 1262575, Tsinghua University’s Top Open program and National Science Foundation Graduate Research Fellowship DGE-1252522.

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