eCommons

 

A comprehensive study of the notion of functional link between genes based on microarray data, promoter signals, protein-protein interactions and pathway analysis

dc.contributor.authorDirks, Williamen_US
dc.contributor.authorYona, Golanen_US
dc.date.accessioned2007-04-04T19:28:49Z
dc.date.available2007-04-04T19:28:49Z
dc.date.issued2004-01-12en_US
dc.description.abstractIt is commonly accepted that genes with similar expression profiles are functionally related. However, so far no clear distinction has been made as for the type of the functional link between genes as suggested by microarray data. Similarly expressed genes can be part of the same complex as interacting partners; they can participate in the same pathway without interacting directly; they can perform similar functions; or they can simply have similar regulatory sequences. Here we embark on a rigorous study of the notion of functional link as implied from expression data. We analyze different similarity measures of gene expression profiles and assess their usefulness and robustness in detecting biological relationships by comparing the similarity scores with results obtained from databases of interacting proteins, promoter signals, and cellular pathways, as well as through sequence comparisons and pathway modeling. We also introduce new similarity measures we specifically developed for the analysis of expression data. These measures are based on statistical analysis and better discriminate genes which are functionally nearby and faraway. With the optimized similarity measures we proceed to analyze other aspects of this data. Specifically, we introduce a method of inferring the type of relationship by correlating the expression data with all the other data sets. This method allows us to not only predict when genes are functionally related but also to suggest how they are related. We then cluster the data using clustering algorithms that are specially tailored to deal with noisy data. Finally we propose methods for assessing the significance of clusters and study the correspondence between gene clusters and biochemical pathways.en_US
dc.format.extent5221052 bytes
dc.format.mimetypeapplication/postscript
dc.identifier.citationhttp://techreports.library.cornell.edu:8081/Dienst/UI/1.0/Display/cul.cis/TR2004-1921en_US
dc.identifier.urihttps://hdl.handle.net/1813/5633
dc.language.isoen_USen_US
dc.publisherCornell Universityen_US
dc.subjectcomputer scienceen_US
dc.subjecttechnical reporten_US
dc.titleA comprehensive study of the notion of functional link between genes based on microarray data, promoter signals, protein-protein interactions and pathway analysisen_US
dc.typetechnical reporten_US

Files

Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
TR2004-1921.ps
Size:
4.98 MB
Format:
Postscript Files