DimiG

KO | EN

gitlite — search

#javascript #python #hacktoberfest #react #typescript #golang #machine-learning #nodejs #windows #awesome #awesome-list #vue #security #open-source

(★ 10)

Inferring disease-associated miRNAs

DimiG Latest Version Download

Download Latest Version (.zip)

// repository documentation

Was this content helpful?

★ 0 (0 ratings)

# DimiG for inferring disease-associated miRNAs
The microRNAs (miRNAs) play crucial roles in many biological processes involved in diseases and miRNAs function with protein coding genes (PCGs). In this study, we present a semi-supervised multi-label framework to integrate PCG-PCG interactions, PCG-miRNA interactions, PCG-disease associations using graph convolutional network (GCN). DimiG is then trained on a graph, which is further used to score associations between diseases and miRNAs.

# System Requirements

## Hardware Requirements

The DimiG requires only a standard computer with enough RAM to support the operations. For minimal performance, this will be a computer with about 8 GB of RAM. For optimal performance, we recommend a computer with the following specs:

* RAM: 8+ GB 
  * CPU: Intel® Core™ i5-3337U CPU @ 1.80GHz × 4

### OS Requirements

This package is supported for *Linux* operating systems. The package has been tested on the following systems:

Linux: Ubuntu 16.04

## Package dependencies
 * <a href=https://github.com/scikit-learn/scikit-learn>sklearn</a> 
 * GCN
 * <a href=https://pytorch.org/>PyTorch 0.4 or 0.5</a> 
 * Python 2.7

## Installation of GCN
Here we modified the orginal GCN (https://github.com/tkipf/pygcn) to support multi-label learning. 
```python setup.py install```

# Demo
1. To run the demo code, some big file needs be downloaded from other website: 
 - PCG-PCG interaction file "9606.protein.links.v10.txt.gz" can be downloaded from <a href="https://string-db.org/">STRING</a> v10 database. 
 - Disease-PCG assications file "human_disease_integrated_full.tsv" can be downloaded from <a href="https://diseases.jensenlab.org/Downloads">DISEASES </a> database. We also upload the file human_disease_integrated_full.zip in this repository, please decompress it at directory data/. 
 - PCG-miRNA interaction file "9606.v1.combined.tsv.gz" can be downloaded from <a href="https://rth.dk/resources/rain/">RAIN</a> v1.0 database. 
 - The above three files need be saved at dir "data/".

2. You can directly get the prediction and give the ROC curve by running: 
``` python DimiG.py```

It will output training and validaiton loss. In total, It takes < 20 minutes to run.

DimiG

DimiG Latest Version Download

Today's picks

Was this content helpful?

Recent Feedback

DimiG

DimiG Latest Version Download

Today's picks

Was this content helpful?

Recent Feedback

Download README