TY  - JOUR
A1  - Asthana, Saurabh
A1  - King, Oliver D.
A1  - Gibbons, Francis D.
A1  - Roth, Frederick P.
T1  - Predicting Protein Complex Membership Using Probabilistic Network Reliability
Y1  - 2004/06/01 
JF  - Genome Research 
JO  - Genome Research 
SP  - 1170 
EP  - 1175 
DO  - 10.1101/gr.2203804 
VL  - 14 
IS  - 6 
UR  - http://genome.cshlp.org/content/14/6/1170.abstract 
N2  - Evidence for specific protein–protein interactions is increasingly available from both small- and large-scale studies, and can be viewed as a network. It has previously been noted that errors are frequent among large-scale studies, and that error frequency depends on the large-scale method used. Despite knowledge of the error-prone nature of interaction evidence, edges (connections) in this network are typically viewed as either present or absent. However, use of a probabilistic network that considers quantity and quality of supporting evidence should improve inference derived from protein networks. Here we demonstrate inference of membership in a partially known protein complex by using a probabilistic network model and an algorithm previously used to evaluate reliability in communication networks. 
ER  -