Protein interaction verification and functional annotation by integrated analysis of genome-scale data.
Assays capable of determining the properties of thousands of genes in parallel present challenges with regard to accurate data processing and functional annotation. Collections of microarray expression data are applied here to assess the quality of different high-throughput protein interaction data sets. Significant differences are found. Confidence in 973 out of 5342 putative two-hybrid interactions from S. cerevisiae is increased. Besides verification, integration of expression and interaction data is employed to provide functional annotation for over 300 previously uncharacterized genes. The robustness of these approaches is demonstrated by experiments that test the in silico predictions made. This study shows how integration improves the utility of different types of functional genomic data and how well this contributes to functional annotation.
Kemmeren
Patrick
P
Genomics Laboratory, Department of Biomedical Genetics, University Medical Center Utrecht, P.O. Box 85060, 3508 AB Utrecht, The Netherlands.
van Berkum
Nynke L
NL
Vilo
Jaak
J
Bijma
Theo
T
Donders
Rogier
R
Brazma
Alvis
A
Holstege
Frank C P
FC
D000818:Animals; D016678:Genome; D006801:Humans; D020411:Oligonucleotide Array Sequence Analysis / Q000706:statistics & numerical data*; D011485:Protein Binding / Q000235:genetics; D011506:Proteins / Q000235:genetics*; D012326:RNA Splicing; D012333:RNA, Messenger / Q000378:metabolism; D013223:Statistics as Topic / Q000379:methods*
D011506:Proteins; D012333:RNA, Messenger