NARROMI: a noise and redundancy reduction technique improves
accuracy of gene regulatory network inference

 

MATLAB source code, dataset and tutorial

 
This page provides the free MATLAB source codes, dataset and Tutorial.

 

Introduction:

NARROMI is a MATLAB program for inferring gene regulatory networks from gene expression data. It is a novel method combining ordinary differential equation based recursive optimization (RO) and information-theory based mutual information (MI). In this algorithm, both noisy regulations with low pair-wise correlations and redundant regulations from indirect regulators are removed by measuring MI and implementing RO, respectively. Moreover, the dimension shrinking technique improves the efficiency of optimization and further the accuracy of network inference. In particular, our approach is the first one to handle the redundancy problem in GRNs for model based network inference methods.

 
Download:
Source Code: NARROMI ;

Datasets: Ecoli_Data;

Tutorial: Tutorial for NARROMI.
 
Reference:
[1] Xiujun Zhang, Keqin Liu, Zhi-Ping Liu, B¨¦atrice Duval, Jean-Michel Richer, Xing-Ming Zhao, Jin-Kao Hao and Luonan Chen. NARROMI: a noise and redundancy reduction technique improves accuracy of gene regulatory network inference. Bioinformatics, doi: 10.1093/bioinformatics/bts619, 2012. (pdf)
[2] Xiujun Zhang, Xing-Ming Zhao, Kun He, Le Lu, Yongwei Cao, Jingdong Liu, Jin-Kao Hao, Zhi-Ping Liu, Luonan Chen. Inferring gene regulatory networks from gene expression data by path consistency algorithm based on conditional mutual information. Bioinformatics, 28 (1):98- 104, 2012. (pdf)
 

Contact:

The MATLAB codes and dataset are free to use. If you encounter any problem, please do not hesitate to contact us at zhang-xiujun@163.com or zhaoxingming@gmail.com or hao@info.univ-angers.fr or lnchen@sibs.ac.cn.  Thanks!