Novel application of multi-stimuli network inference to synovial fibroblasts of rheumatoid arthritis patients

• Published in: BMC medical genomics Vol. 7; no. 1; p. 40
• Main Authors: Kupfer, Peter, Huber, René, Weber, Michael, Vlaic, Sebastian, Häupl, Thomas, Koczan, Dirk, Guthke, Reinhard, Kinne, Raimund W
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 03.07.2014; BioMed Central
• Subjects: Aged; Analysis; Arthritis, Rheumatoid - genetics; Arthritis, Rheumatoid - pathology; Biology; Computational Biology - methods; DNA binding proteins; Enzymes; Experiments; Female; Fibroblasts - drug effects; Fibroblasts - metabolism; Gene expression; Gene Expression Profiling; Genes; Genetic aspects; Genetic engineering; Genetic transcription; Growth factors; Heuristic; Humans; Hypotheses; Interleukin-1beta - pharmacology; Male; Methods; Middle Aged; Ordinary differential equations; Orthopedics; Pathogenesis; Platelet-Derived Growth Factor - pharmacology; Proteins; Rheumatoid arthritis; Rheumatology; Synovial Membrane - pathology; Transforming Growth Factor beta - pharmacology; Tumor necrosis factor; Tumor Necrosis Factor-alpha - pharmacology; Writing; Germany

Network inference of gene expression data is an important challenge in systems biology. Novel algorithms may provide more detailed gene regulatory networks (GRN) for complex, chronic inflammatory diseases such as rheumatoid arthritis (RA), in which activated synovial fibroblasts (SFBs) play a major...