title: Constructing biological networks through combined literature mining and microarray analysis: a LMMA approach.
abstract: BACKGROUND
  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.
  
  
  BACKGROUND
  The LMMA program is available upon request.
authors.affiliation: Bioinformatics Division, TNLIST and Department of Automation, Tsinghua University, Beijing 100084, China. shaoli@mail.tsinghua.edu.cn
authors.forename: Shao
authors.initials: S
authors.lastname: Li
authors.forename: Lijiang
authors.initials: L
authors.lastname: Wu
authors.forename: Zhongqi
authors.initials: Z
authors.lastname: Zhang
mesh_terms: D000043:Abstracting and Indexing / Q000379:methods; D003628:Database Management Systems; D030562:Databases, Protein; D020869:Gene Expression Profiling / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods*; D016239:MEDLINE; D009323:Natural Language Processing; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D010506:Periodicals as Topic; D020543:Proteome / Q000145:classification / Q000235:genetics / Q000378:metabolism*; D015398:Signal Transduction / Q000502:physiology*; D018511:Systems Integration
chemical_list: D020543:Proteome