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4 changes: 3 additions & 1 deletion README.md
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We provided the evaluation script using target function proposed in the manuscript, as well as a gene2vec file in word2vec format.

## Introduction
Gene2Vec is a distributed representation of genes based on co-expression. From a pure data-driven fashion, we trained a
Gene2Vec is a distributed representation of genes based on co-expression. From a pure data-driven fashion, we trained a
200-dimension vector representation of all human genes, using gene co-expression patterns in 984 data sets from the GEO databases.

In this repository, we provided the relevent codes as well as pre-trained gene2vec files.
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pip install -r requirements.txt
```

*NOTE: If you get an error with `certifi`, add `--ignore-installed certifi` to the end of the `pip install` command.*

## Usage

### gene2vec.py
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7 changes: 5 additions & 2 deletions requirements.txt
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tensorflow>=1.6.0
gensim>=3.4.0
gensim==3.4.0
numpy>=1.14.0
matplotlib>=2.1.2
matplotlib>=2.1.2
scikit-learn==0.18.2
scipy==1.2.0
MulticoreTSNE==0.1