Constructing biological networks through combined literature mining and microarray analysis: a LMMA approach

Authors:
Shao Li;Lijiang Wu;Zhongqi Zhang
Affiliations:
Bioinformatics Division, TNLIST and Department of Automation, Tsinghua University Beijing 100084, China;Bioinformatics Division, TNLIST and Department of Automation, Tsinghua University Beijing 100084, China;Bioinformatics Division, TNLIST and Department of Automation, Tsinghua University Beijing 100084, China
Venue:
Bioinformatics
Year:
2006

Citing 0
Cited 4

Inferring biomolecular interaction networks based on convex optimization

Computational Biology and Chemistry
Methodological Review: Towards knowledge-based gene expression data mining

Journal of Biomedical Informatics
Methodological Review: Text mining for traditional Chinese medical knowledge discovery: A survey

Journal of Biomedical Informatics
Computational identification of potential microRNA network biomarkers for the progression stages of gastric cancer

International Journal of Data Mining and Bioinformatics

Quantified Score

Hi-index	3.84

Visualization

Abstract

Motivation: Network reconstruction of biological entities is very important for understanding biological processes and the organizational principles of biological systems. This work focuses on integrating both the literatures and microarray gene-expression data, and a combined literature mining and microarray analysis (LMMA) approach is developed to construct gene networks of a specific biological system. Results: In the LMMA approach, a global network is first constructed using the literature-based co-occurrence method. It is then refined using microarray data through a multivariate selection procedure. An application of LMMA to the angiogenesis is presented. Our result shows that the LMMA-based network is more reliable than the co-occurrence-based network in dealing with multiple levels of KEGG gene, KEGG Orthology and pathway. Availability: The LMMA program is available upon request. Contact: shaoli@mail.tsinghua.edu.cn Supplementary Information: Supplementary data are available at Bioinformatics online.