Selective integration of multiple biological data for supervised network inference
نویسندگان
چکیده
منابع مشابه
Selective integration of multiple biological data for supervised network inference
MOTIVATION Inferring networks of proteins from biological data is a central issue of computational biology. Most network inference methods, including Bayesian networks, take unsupervised approaches in which the network is totally unknown in the beginning, and all the edges have to be predicted. A more realistic supervised framework, proposed recently, assumes that a substantial part of the netw...
متن کاملSelective Integration of Multiple Genomic Data for Biological Network Inference
In the field of computational biology, recently there has been a surge of interest in biological networks such as protein interaction networks, gene regulatory networks, or metabolic networks, which help us to understand the cellular machinery. Most of biological networks represent the relationships between genes or proteins. Namely the existence of edges means that the corresponding genes/prot...
متن کاملA Transfer Learning Approach and Selective Integration of Multiple Types of Assays for Biological Network Inference
Inferring the relationship among proteins is a central issue of computational biology and a diversity of biological assays are utilized to predict the relationship. However, as experiments are usually expensive to perform, automatic data selection is employed to reduce the data collection cost. Although data useful for link prediction are different in each local sub-network, existing methods ca...
متن کاملA Transfer Learning Approach and Selective Integration of Multiple Assays for Biological Network Inference
1 AIST Computational Biology Research Center, 2-42 Aomi, Koto-ku, Tokyo 135.0064, Japan. 2 Center for Informational Biology, Ochanomizu University, 2-1-1 Ohtsuka, Bunkyo-ku, Tokyo 112.8610, Japan. 3 KO Institute for Medical Bioinformatics, Yokohama, Kanagawa 227.0033, Japan. 4 IBM Research, Tokyo Research Laboratory, 1623-14 Shimo-tsuruma, Yamato, Kanagawa, 242-8502 Japan. 5 Tokyo Institute of ...
متن کاملProtein network inference from multiple genomic data: a supervised approach
MOTIVATION An increasing number of observations support the hypothesis that most biological functions involve the interactions between many proteins, and that the complexity of living systems arises as a result of such interactions. In this context, the problem of inferring a global protein network for a given organism, using all available genomic data about the organism, is quickly becoming on...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Bioinformatics
سال: 2005
ISSN: 1367-4803,1460-2059
DOI: 10.1093/bioinformatics/bti339