Networking pathways unveils association between obesity and non-insulin dependent diabetes mellitus.
Genetic related health problems are often interrelated. Current practices to establish associations between diseases are expensive and rarely can reflect underlying molecular mechanisms, We propose a general framework to associate diseases by networking pathways. By applying our method on association study of non-insulin dependent diabetes mellitus (NIDDM) and obesity, we demonstrate that our method can both identify signature pathways for each disease and establish valid association of two diseases.
Hu
Haiyan
H
School of lnformatics and Center for Computational Biology and Bioinformatics, Indiana University, 410 West 10th street, Suite 5000, Indianapolis, IN 46202, USA.
Li
Xiaoman
X
D019295:Computational Biology; D030541:Databases, Genetic; D003924:Diabetes Mellitus, Type 2 / Q000150:complications* / Q000235:genetics*; D020869:Gene Expression Profiling / Q000706:statistics & numerical data; D006801:Humans; D008297:Male; D008954:Models, Biological; D015233:Models, Statistical; D018482:Muscle, Skeletal / Q000378:metabolism; D009765:Obesity / Q000150:complications* / Q000235:genetics*; D020411:Oligonucleotide Array Sequence Analysis / Q000706:statistics & numerical data; D049490:Systems Biology