License
Copyright (C) 2014 Jianxin Wang(jxwang@mail.csu.edu.cn),Huimin Luo(luohuimin@csu.edu.cn)
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(jxwang@mail.csu.edu.cn),Huimin Luo(luohuimin@csu.edu.cn) School of Information Science and Engineering Central South University ChangSha CHINA, 410083
Computational drug repositioning
MBiRW is one novel computational method, which utilizes comprehensive similarity measures and Bi-Random walk algorithm to identify potential novel indications for a given drug.
1.Dataset.
-
DrugSimMat and DiseaseSimMat store drug similarity matrix and disease similarity matrix, respectively;
-
DiDrAMat stores known disease-drug association information;
-
DrugsName and DiseasesName store drug ids and disease ids, respectively;
-
For each drug pair, the number of their sharing common diseases is stored in shareWrr.mat;
-
For each disease pair, the number of their sharing common drugs is stored in shareWdd.mat;
-
CDataSets store the combined datasets; Datasets_indep store the independent dataset.
2.Code.
-
normFun.m: function implementing normalization;
-
setparFun.m: function analyzing similarity network;
-
nManiCluester.m : function implementing cluster operation by calling cluster_one-1.0;
-
MBiRW: predict potential indications for drugs;
All files of Dataset and Code should be stored in the same folder to run MBiRW.