This is version 1 2 3 4 . It is not the current version, and thus it cannot be edited.
Back to current version   Restore this version

GRNInfer: A Gene Regulatory Network Inference tool from multiple microarray datasets

• Version 1.0
• Last updated: December 22, 2005

Reference#

• Yong Wang, Trupti Joshi, Xiang-Sun Zhang, Dong Xu, and Luonan Chen. Inferring gene regulatory networks from multiple microarray datasets. Bioinformatics, Vol. 22, No. 19, pp. 2413-2420, 2006.

Method#

GRNInfer aims to derive the most consistent network structure with respect to Multiple Microarray Datasets, by exploiting available information from a variety of experiments. Specifically, inferring gene network is formulated as an optimization problem with minimization of L1 norm for the objective function, which involves both forced matching and sparse terms. An efficient algorithm is developed to solve such a large-scale linear programming in an iterative manner. With such a procedure, a consistent and sparse structure that is also considered to be biologically plausible, can be expected to be derived.

Procedure#

• Step 1: Format the Multiple Microarray Datasets into desired data file (See the attached example file as a reference).
• Step 2: Open the data file by click the 'open' button and browse the data file location.
• Step 3: Choose proper parameters. There are two parameters you can choose by altering the default value. Specifically,
  • Lambda: This parameter is used in the inferring algorithm to adjust the sparsity of the structure. The default value is 0.0.
  • Threshold: This parameter is used in the control the output file GRN.dot, which can be visualized by the neato tool of the software package Graphviz. The threshold parameter controls the number of the edge whose strength of link is smaller than Threshold not shown in the network graph. The smaller this parameter, the more edges in the network graph. The default value is set to 1e-6.
• Step 4: Computing by click the 'Infer' button when the data file and parameters are ready.
• Step 5: Checking the results. There are two files are output in the same directory with the software.
  • GRN.dat: This file records the matrix assessing the strengths of edges of the network, i.e. the element located on the i-th row and the j-th column means the regulatory strength from the j-th gene to the i-th gene, the sign + means the activation and the sign - means repression.
  • GRN.dot: This file records the information to output the network structure which can be illustrated by Graphviz. Note that only the edges whose regulatory strength in GRN.dat is larger than Threshold parameter are shown. The software Graphviz can be downloaded from http://www.graphviz.org freely.

Software#

This is a beta version of the program for preliminary testing. The program is still under development.

• GRNInfer.zip

---

There are APORC Document Center : GRNInfer - Plugin insertion failed: Could not find plugin org.goodjava.plugin.hitcounter.HitCounterAPORC Document Center : GRNInfer - 插件插入失败：找不到插件 org.goodjava.plugin.hitcounter.HitCounter visitors since January 18, 2009