A network inference approach to understanding musculoskeletal disorders

摘要: Musculoskeletal disorders are among the most important health problem affecting quality of life and contributing to a high burden on healthcare systems worldwide. Understanding molecular mechanisms underlying these is crucial for development efficient treatments. In this thesis, musculoskeletal including muscle wasting, bone loss cartilage deformation have been studied using biology approaches. Muscle wasting occurring as systemic effect in COPD patients has investigated with an integrative network inference approach. This work lead model describing relationship between physiological response training inflammatory mediators. shown first time that oxygen dependent changes expression epigenetic modifiers not chronic inflammation may be causally linked dysfunction. Bone observed ageing, arthritis multiple myeloma (MM) also by novel modularization approach developed within thesis. methodology allows integration multi-level dataset large interaction networks. It aims identify sub-networks genes differentially expressed experimental conditions co-regulated across samples different biological systems. study identified several potential key players such Myc, DUSP6 components Notch could enhance osteogenic differentiation MM patients. conclusion, thesis present effectiveness approaches understanding complex diseases applied studying other datasets.