%0 Journal Article %1 Shlomi2008Networkbased %A Shlomi, Tomer %A Cabili, Moran N. %A Herrgard, Markus J. %A Palsson, Bernhard Ø. %A Ruppin, Eytan %B Nat Biotech %C 1 School of Computer Science, Tel-Aviv University, Tel-Aviv 69978, Israel. 2 These authors contributed equally to this work. %D 2008 %I Nature Publishing Group %J Nature biotechnology %K human metabolic-networks reconstruction transcriptional-regulation %N 9 %P 1003--1010 %R 10.1038/nbt.1487 %T Network-based prediction of human tissue-specific metabolism. %U http://dx.doi.org/10.1038/nbt.1487 %V 26 %X Direct in vivo investigation of mammalian metabolism is complicated by the distinct metabolic functions of different tissues. We present a computational method that successfully describes the tissue specificity of human metabolism on a large scale. By integrating tissue-specific gene- and protein-expression data with an existing comprehensive reconstruction of the global human metabolic network, we predict tissue-specific metabolic activity in ten human tissues. This reveals a central role for post-transcriptional regulation in shaping tissue-specific metabolic activity profiles. The predicted tissue specificity of genes responsible for metabolic diseases and tissue-specific differences in metabolite exchange with biofluids extend markedly beyond tissue-specific differences manifest in enzyme-expression data, and are validated by large-scale mining of tissue-specificity data. Our results establish a computational basis for the genome-wide study of normal and abnormal human metabolism in a tissue-specific manner.

@article{Shlomi2008Networkbased, abstract = {Direct in vivo investigation of mammalian metabolism is complicated by the distinct metabolic functions of different tissues. We present a computational method that successfully describes the tissue specificity of human metabolism on a large scale. By integrating tissue-specific gene- and protein-expression data with an existing comprehensive reconstruction of the global human metabolic network, we predict tissue-specific metabolic activity in ten human tissues. This reveals a central role for post-transcriptional regulation in shaping tissue-specific metabolic activity profiles. The predicted tissue specificity of genes responsible for metabolic diseases and tissue-specific differences in metabolite exchange with biofluids extend markedly beyond tissue-specific differences manifest in enzyme-expression data, and are validated by large-scale mining of tissue-specificity data. Our results establish a computational basis for the genome-wide study of normal and abnormal human metabolism in a tissue-specific manner.}, added-at = {2018-12-02T16:09:07.000+0100}, address = {[1] School of Computer Science, Tel-Aviv University, Tel-Aviv 69978, Israel. [2] These authors contributed equally to this work.}, author = {Shlomi, Tomer and Cabili, Moran N. and Herrg\r{a}rd, Markus J. and Palsson, Bernhard {\O}. and Ruppin, Eytan}, biburl = {https://www.bibsonomy.org/bibtex/24433aafc0924d5fb432e1cd67ab066cb/karthikraman}, booktitle = {Nat Biotech}, citeulike-article-id = {3196658}, citeulike-linkout-0 = {http://dx.doi.org/10.1038/nbt.1487}, citeulike-linkout-1 = {http://dx.doi.org/10.1038/nbt.1487}, citeulike-linkout-2 = {http://view.ncbi.nlm.nih.gov/pubmed/18711341}, citeulike-linkout-3 = {http://www.hubmed.org/display.cgi?uids=18711341}, day = 17, doi = {10.1038/nbt.1487}, interhash = {f0c2811d3a287ab70f33aba9c4239f56}, intrahash = {4433aafc0924d5fb432e1cd67ab066cb}, issn = {1546-1696}, journal = {Nature biotechnology}, keywords = {human metabolic-networks reconstruction transcriptional-regulation}, month = sep, number = 9, pages = {1003--1010}, pmid = {18711341}, posted-at = {2010-12-03 10:48:11}, priority = {2}, publisher = {Nature Publishing Group}, timestamp = {2018-12-02T16:09:07.000+0100}, title = {Network-based prediction of human tissue-specific metabolism.}, url = {http://dx.doi.org/10.1038/nbt.1487}, volume = 26, year = 2008 }