Developing Networks in Obesity using Text Mining
Developing networks in obesity and related disorders such as diabetes, PCOD & hypertension using text mining systems
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Obesity is a global epidemic affecting over 1.5 billion people and is one of the risk factors for several diseases such as Type 2 diabetes mellitus and hypertension. Despite measures taken by public health authorities to control obesity, number of people affected with obesity and its related disorders are increasing at alarming rate. It is imperative therefore to understand the molecular pathophysiology of obesity prior to undertaking any containment measures. This book summarizes our research work for developing a system with the capability to mine an extensive corpus of scientific articles a...
Obesity is a global epidemic affecting over 1.5 billion people and is one of the risk factors for several diseases such as Type 2 diabetes mellitus and hypertension. Despite measures taken by public health authorities to control obesity, number of people affected with obesity and its related disorders are increasing at alarming rate. It is imperative therefore to understand the molecular pathophysiology of obesity prior to undertaking any containment measures. This book summarizes our research work for developing a system with the capability to mine an extensive corpus of scientific articles and produce a network of genes implicated in a given disease. The system has been developed taking Obesity as a test case. The constructed network holds a central place in understanding the pathophysiology of Obesity and will serve as an important tool for the identification of drug targets. This work has been further extended to seven other obesity related disorders (Diabetes Mellitus II, Cholelithiasis, Hypertension, Hyperlipidemia, Polycystic Ovarian Syndrome, Osteoarthritis and Fatty Liver) and four control sets (Rheumatoid Arthritis, Contact Dermatitis, Asthma and Urticaria).
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