Skip to content

Prediction of lncRNA-disease associations based on inductive matrix completion

Notifications You must be signed in to change notification settings

bioinfomaticsCSU/SIMCLDA

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

5 Commits
 
 
 
 
 
 

Repository files navigation

License

Copyright (C) 2017 Jianxin Wang([email protected]),Chengqian Lu([email protected])

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

This program 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 General Public License for more details.

You should have received a copy of the GNU General Public License along with this program; if not, see http://www.gnu.org/licenses/.

Jianxin Wang([email protected]),Chengqian Lu([email protected]) School of Information Science and Engineering Central South University ChangSha CHINA, 410083

Type: Package Title: Prediction of lncRNA-disease associations based on inductive matrix completion

Description: This package implements the SIMCLDA algorithm with inductive matrix completion framework, predicting lncRNA-disease associations.

Files: 1.Dataset

  1. lncSim.mat and disSim_Jaccard.mat store lncRNA similarity matrix and disease similarity matrix, respectively;

  2. interMatrix.mat stores known lncRNA-disease association information;

  3. lncRNA_Name.txt and diseases_Name.txt store lncRNA ids and disease ids, respectively;

2.Code

  1. gKernel.m: function computing Gaussian interaction profile kernel;

  2. pca_energy.m: function extracting feature vectors via PCA;

  3. SIMC.m : function completing matrix;

  4. SIMCLDA: predict potential lncRNA-disease associations;

About

Prediction of lncRNA-disease associations based on inductive matrix completion

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published