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Predicting cross-tissue hormone-gene relations using balanced word embeddings.

This is the official repository of the paper "Predicting cross-tissue hormone-gene relations using balanced word embeddings." by Aditya Jadhav, Tarun Kumar+, Mohit Raghavendra+, Tamizhini Loganathan, and Manikandan Narayanan (+ equal contributions).

The code was developed by Aditya Jadhav, Mohit R, and Manikandan Narayanan (in consultation with the other co-authors of the paper listed above), and these developers are jointly referred to as the "BIRDS Group, IIT Madras" in the preamble of all code files in this BioEmbedS project.

License preamble

Copyright 2020 BIRDS Group, IIT Madras

BioEmbedS is free software: you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

BioEmbedS is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details.

You should have received a copy of the GNU Lesser General Public License along with BioEmbedS. If not, see https://www.gnu.org/licenses/.

Installation

See requirements.txt file for the list of dependencies. Setup everything by executing
pip install -r requirements.txt.

Running

  1. Navigate to either BioEmbedS or BioEmbedS-TS
  2. Follow the instructions in the README file of the appropriate folder.

Results

Results are available at the project webpage https://cross-tissue-signaling.herokuapp.com/

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  • Jupyter Notebook 77.4%
  • Python 22.6%