title: Automatic construction of gene relation networks using text mining and gene expression data.
abstract: Microarray gene expression analysis is a powerful high-throughput technique that enables researchers to monitor the expression of thousands of genes simultaneously. Using this methodology huge amounts of data are produced which have to be analysed. Clustering algorithms are used to group genes together based on a predefined distance measure. However, clustering algorithms do not necessarily group the genes in a biological meaningful way. Additional information is needed to improve the identification of disease relevant genes. The primary objective of our project is to support the analysis of microarray gene expression data by construction of gene relation networks (GRNs). Required information can not be found in a structured representation like a database. In contrast, a large number of relations are described in biomedical literature. The main outcome of this project is the implementation of a software system that provides clinicians and researchers with a tool that supports the analysis of microarray gene expression data by mapping known relationships from the biomedical literature to local gene expression experiments.
authors.affiliation: Institute of Medical Informatics and Biometry, University of Rostock, Rembrandt-Strasse 16/17, 18055 Rostock, Germany. thomas.karopka@medizin.uni-rostock.de
authors.forename: Thomas
authors.initials: T
authors.lastname: Karopka
authors.forename: Thomas
authors.initials: T
authors.lastname: Scheel
authors.forename: Sven
authors.initials: S
authors.lastname: Bansemer
authors.forename: Anne
authors.initials: A
authors.lastname: Glass
mesh_terms: D000004:Abbreviations as Topic; D000043:Abstracting and Indexing; D000465:Algorithms; D016000:Cluster Analysis; D030541:Databases, Genetic / Q000592:standards*; D020869:Gene Expression Profiling / Q000379:methods* / Q000592:standards; D006801:Humans; D007256:Information Systems / Q000458:organization & administration*; D015470:Leukemia, Myeloid, Acute / Q000145:classification / Q000235:genetics; D016239:MEDLINE; D009323:Natural Language Processing; D016571:Neural Networks, Computer; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods* / Q000592:standards; D054198:Precursor Cell Lymphoblastic Leukemia-Lymphoma / Q000145:classification / Q000235:genetics; D014584:User-Computer Interface