Correlation between transcriptome and interactome mapping data from Saccharomyces cerevisiae. Export

@article{citeulike:309439, abstract = {Genomic and proteomic approaches can provide hypotheses concerning function for the large number of genes predicted from genome sequences. Because of the artificial nature of the assays, however, the information from these high-throughput approaches should be considered with caution. Although it is possible that more meaningful hypotheses could be formulated by integrating the data from various functional genomic and proteomic projects, it has yet to be seen to what extent the data can be correlated and how such integration can be achieved. We developed a 'transcriptome-interactome correlation mapping' strategy to compare the interactions between proteins encoded by genes that belong to common expression-profiling clusters with those between proteins encoded by genes that belong to different clusters. Using this strategy with currently available data sets for Saccharomyces cerevisiae, we provide the first global evidence that genes with similar expression profiles are more likely to encode interacting proteins. We show how this correlation between transcriptome and interactome data can be used to improve the quality of hypotheses based on the information from both approaches. The strategy described here may help to integrate other functional genomic and proteomic data, both in yeast and in higher organisms.}, address = {Dana-Farber Cancer Institute and Department of Genetics, Harvard Medical School, Boston, Massachusetts 02115, USA.}, author = {Ge, H. and Liu, Z. and Church, G. M. and Vidal, M.}, citeulike-article-id = {309439}, citeulike-linkout-0 = {http://dx.doi.org/10.1038/ng776}, citeulike-linkout-1 = {http://dx.doi.org/10.1038/ng776}, citeulike-linkout-2 = {http://view.ncbi.nlm.nih.gov/pubmed/11694880}, citeulike-linkout-3 = {http://www.hubmed.org/display.cgi?uids=11694880}, doi = {10.1038/ng776}, issn = {1061-4036}, journal = {Nature genetics}, keywords = {biological\_networks, proje}, month = {December}, number = {4}, pages = {482--486}, posted-at = {2006-08-22 21:13:44}, priority = {2}, title = {Correlation between transcriptome and interactome mapping data from Saccharomyces cerevisiae.}, url = {http://dx.doi.org/10.1038/ng776}, volume = {29}, year = {2001} }

TY - JOUR ID - citeulike:309439 L3 - citeulike-article-id:309439 N2 - Genomic and proteomic approaches can provide hypotheses concerning function for the large number of genes predicted from genome sequences. Because of the artificial nature of the assays, however, the information from these high-throughput approaches should be considered with caution. Although it is possible that more meaningful hypotheses could be formulated by integrating the data from various functional genomic and proteomic projects, it has yet to be seen to what extent the data can be correlated and how such integration can be achieved. We developed a 'transcriptome-interactome correlation mapping' strategy to compare the interactions between proteins encoded by genes that belong to common expression-profiling clusters with those between proteins encoded by genes that belong to different clusters. Using this strategy with currently available data sets for Saccharomyces cerevisiae, we provide the first global evidence that genes with similar expression profiles are more likely to encode interacting proteins. We show how this correlation between transcriptome and interactome data can be used to improve the quality of hypotheses based on the information from both approaches. The strategy described here may help to integrate other functional genomic and proteomic data, both in yeast and in higher organisms. IS - 4 JF - Nature genetics SN - 1061-4036 AD - Dana-Farber Cancer Institute and Department of Genetics, Harvard Medical School, Boston, Massachusetts 02115, USA. EP - 486 TI - Correlation between transcriptome and interactome mapping data from Saccharomyces cerevisiae. VL - 29 SP - 482 KW - biological_networks KW - proje AU - Ge, H AU - Liu, Z AU - Church, GM AU - Vidal, M PY - 2001/12// UR - http://dx.doi.org/10.1038/ng776 ER -