{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T23:22:12Z","timestamp":1773271332402,"version":"3.50.1"},"reference-count":43,"publisher":"Oxford University Press (OUP)","issue":"22","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2009,11,15]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Motivation: The existing supervised methods for biological network inference work on each of the networks individually based only on intra-species information such as gene expression data. We believe that it will be more effective to use genomic data and cross-species evolutionary information from different species simultaneously, rather than to use the genomic data alone.<\/jats:p><jats:p>Results: We created a new semi-supervised learning method called Link Propagation for inferring biological networks of multiple species based on genome-wide data and evolutionary information. The new method was applied to simultaneous reconstruction of three metabolic networks of Caenorhabditis elegans, Helicobacter pylori and Saccharomyces cerevisiae, based on gene expression similarities and amino acid sequence similarities. The experimental results proved that the new simultaneous network inference method consistently improves the predictive performance over the individual network inferences, and it also outperforms in accuracy and speed other established methods such as the pairwise support vector machine.<\/jats:p><jats:p>Availability: The software and data are available at http:\/\/cbio.ensmp.fr\/\u223cyyamanishi\/LinkPropagation\/.<\/jats:p><jats:p>Contact: \u00a0kashima@mist.i.u-tokyo.ac.jp<\/jats:p><jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btp494","type":"journal-article","created":{"date-parts":[[2009,8,19]],"date-time":"2009-08-19T03:03:10Z","timestamp":1250650990000},"page":"2962-2968","source":"Crossref","is-referenced-by-count":17,"title":["Simultaneous inference of biological networks of multiple species from genome-wide data and evolutionary information: a semi-supervised approach"],"prefix":"10.1093","volume":"25","author":[{"given":"Hisashi","family":"Kashima","sequence":"first","affiliation":[{"name":"1 IBM Research, Tokyo Research Laboratory, 1623-14 Shimo-tsuruma, Yamato, Kanagawa, 242-8502 Japan, 2Mines ParisTech, Centre for Computational Biology, 35 rue Saint-Honore, F-77305 Fontainebleau Cedex, France, 3Institut Curie, 4INSERM, U900, F-75248, Paris, France, 5Ochanomizu University, Center for Informational Biology, 2-1-1 Ohtsuka, Bunkyo-ku, Tokyo 112-8610, 6Tokyo Institute of Technology, Department of Computer Science, 2-12-1, O-okayama, Meguro-ku, Tokyo 152-8552 and 7National Institute of Advanced Industrial Science and Technology, Computational Biology Research Center (AIST), 2-42 Aomi, Koto-ku, Tokyo 135-0064, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yoshihiro","family":"Yamanishi","sequence":"additional","affiliation":[{"name":"1 IBM Research, Tokyo Research Laboratory, 1623-14 Shimo-tsuruma, Yamato, Kanagawa, 242-8502 Japan, 2Mines ParisTech, Centre for Computational Biology, 35 rue Saint-Honore, F-77305 Fontainebleau Cedex, France, 3Institut Curie, 4INSERM, U900, F-75248, Paris, France, 5Ochanomizu University, Center for Informational Biology, 2-1-1 Ohtsuka, Bunkyo-ku, Tokyo 112-8610, 6Tokyo Institute of Technology, Department of Computer Science, 2-12-1, O-okayama, Meguro-ku, Tokyo 152-8552 and 7National Institute of Advanced Industrial Science and Technology, Computational Biology Research Center (AIST), 2-42 Aomi, Koto-ku, Tokyo 135-0064, Japan"},{"name":"1 IBM Research, Tokyo Research Laboratory, 1623-14 Shimo-tsuruma, Yamato, Kanagawa, 242-8502 Japan, 2Mines ParisTech, Centre for Computational Biology, 35 rue Saint-Honore, F-77305 Fontainebleau Cedex, France, 3Institut Curie, 4INSERM, U900, F-75248, Paris, France, 5Ochanomizu University, Center for Informational Biology, 2-1-1 Ohtsuka, Bunkyo-ku, Tokyo 112-8610, 6Tokyo Institute of Technology, Department of Computer Science, 2-12-1, O-okayama, Meguro-ku, Tokyo 152-8552 and 7National Institute of Advanced Industrial Science and Technology, Computational Biology Research Center (AIST), 2-42 Aomi, Koto-ku, Tokyo 135-0064, Japan"},{"name":"1 IBM Research, Tokyo Research Laboratory, 1623-14 Shimo-tsuruma, Yamato, Kanagawa, 242-8502 Japan, 2Mines ParisTech, Centre for Computational Biology, 35 rue Saint-Honore, F-77305 Fontainebleau Cedex, France, 3Institut Curie, 4INSERM, U900, F-75248, Paris, France, 5Ochanomizu University, Center for Informational Biology, 2-1-1 Ohtsuka, Bunkyo-ku, Tokyo 112-8610, 6Tokyo Institute of Technology, Department of Computer Science, 2-12-1, O-okayama, Meguro-ku, Tokyo 152-8552 and 7National Institute of Advanced Industrial Science and Technology, Computational Biology Research Center (AIST), 2-42 Aomi, Koto-ku, Tokyo 135-0064, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tsuyoshi","family":"Kato","sequence":"additional","affiliation":[{"name":"1 IBM Research, Tokyo Research Laboratory, 1623-14 Shimo-tsuruma, Yamato, Kanagawa, 242-8502 Japan, 2Mines ParisTech, Centre for Computational Biology, 35 rue Saint-Honore, F-77305 Fontainebleau Cedex, France, 3Institut Curie, 4INSERM, U900, F-75248, Paris, France, 5Ochanomizu University, Center for Informational Biology, 2-1-1 Ohtsuka, Bunkyo-ku, Tokyo 112-8610, 6Tokyo Institute of Technology, Department of Computer Science, 2-12-1, O-okayama, Meguro-ku, Tokyo 152-8552 and 7National Institute of Advanced Industrial Science and Technology, Computational Biology Research Center (AIST), 2-42 Aomi, Koto-ku, Tokyo 135-0064, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Masashi","family":"Sugiyama","sequence":"additional","affiliation":[{"name":"1 IBM Research, Tokyo Research Laboratory, 1623-14 Shimo-tsuruma, Yamato, Kanagawa, 242-8502 Japan, 2Mines ParisTech, Centre for Computational Biology, 35 rue Saint-Honore, F-77305 Fontainebleau Cedex, France, 3Institut Curie, 4INSERM, U900, F-75248, Paris, France, 5Ochanomizu University, Center for Informational Biology, 2-1-1 Ohtsuka, Bunkyo-ku, Tokyo 112-8610, 6Tokyo Institute of Technology, Department of Computer Science, 2-12-1, O-okayama, Meguro-ku, Tokyo 152-8552 and 7National Institute of Advanced Industrial Science and Technology, Computational Biology Research Center (AIST), 2-42 Aomi, Koto-ku, Tokyo 135-0064, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Koji","family":"Tsuda","sequence":"additional","affiliation":[{"name":"1 IBM Research, Tokyo Research Laboratory, 1623-14 Shimo-tsuruma, Yamato, Kanagawa, 242-8502 Japan, 2Mines ParisTech, Centre for Computational Biology, 35 rue Saint-Honore, F-77305 Fontainebleau Cedex, France, 3Institut Curie, 4INSERM, U900, F-75248, Paris, France, 5Ochanomizu University, Center for Informational Biology, 2-1-1 Ohtsuka, Bunkyo-ku, Tokyo 112-8610, 6Tokyo Institute of Technology, Department of Computer Science, 2-12-1, O-okayama, Meguro-ku, Tokyo 152-8552 and 7National Institute of Advanced Industrial Science and Technology, Computational Biology Research Center (AIST), 2-42 Aomi, Koto-ku, Tokyo 135-0064, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2009,8,17]]},"reference":[{"key":"2023013112155584800_B1","doi-asserted-by":"crossref","DOI":"10.1145\/1015330.1015394","article-title":"Unifying collaborative and content-based filtering","volume-title":"Proceedings of the 21st International Conference on Machine Learning (ICML).","author":"Basilico","year":"2004"},{"issue":"Suppl. 1","key":"2023013112155584800_B2","doi-asserted-by":"crossref","first-page":"i38","DOI":"10.1093\/bioinformatics\/bti1016","article-title":"Kernel methods for predicting protein-protein interactions","volume":"21","author":"Ben-Hur","year":"2005","journal-title":"Bioinformatics"},{"key":"2023013112155584800_B3","volume-title":"Pattern Recognition and Machine Learning","author":"Bishop","year":"2006"},{"issue":"Suppl. 2","key":"2023013112155584800_B4","doi-asserted-by":"crossref","first-page":"i57","DOI":"10.1093\/bioinformatics\/btm204","article-title":"Supervised reconstruction of biological networks with local models","volume":"23","author":"Bleakley","year":"2007","journal-title":"Bioinformatics"},{"key":"2023013112155584800_B5","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1186\/1752-0509-1-20","article-title":"A search engine to identify pathway genes from expression data on multiple organisms","volume":"1","author":"Chen","year":"2007","journal-title":"BMC Syst. Biol."},{"key":"2023013112155584800_B6","doi-asserted-by":"crossref","first-page":"i38","DOI":"10.1093\/bioinformatics\/bti1016","article-title":"Comparison of human protein-protein interaction maps","volume":"21","author":"Futschik","year":"2005","journal-title":"Bioinformatics"},{"key":"2023013112155584800_B7","volume-title":"Matrix computations","author":"Golub","year":"1996","edition":"3rd"},{"key":"2023013112155584800_B8","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1016\/S0097-8485(96)80004-0","article-title":"Use of receiver operating characteristic (ROC) analysis to evaluate sequence matching","volume":"20","author":"Gribskov","year":"1996","journal-title":"Comput. Chem."},{"key":"2023013112155584800_B9","doi-asserted-by":"crossref","first-page":"2023","DOI":"10.1093\/bioinformatics\/btn383","article-title":"Robust and efficient identification of biomarkers by classifying features on graphs","volume":"24","author":"Hwang","year":"2008","journal-title":"Bioinformatics"},{"key":"2023013112155584800_B10","article-title":"Online learning of approximate maximum p-norm margin classifiers with biases","volume-title":"Proceedings of the 21st Annual Conference on Learning Theory (COLT).","author":"Ishibashi","year":"2008"},{"key":"2023013112155584800_B11","doi-asserted-by":"crossref","first-page":"2149","DOI":"10.1093\/bioinformatics\/btn409","article-title":"Protein-ligand interaction prediction: an improved chemogenomics approach","volume":"24","author":"Jacob","year":"2008","journal-title":"Bioinformatics"},{"key":"2023013112155584800_B12","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1089\/cmb.2006.13.145","article-title":"Towards an integrated protein-protein interaction network: a relational markov network approach","volume":"13","author":"Jaimovich","year":"2006","journal-title":"J. Comput. Biol."},{"key":"2023013112155584800_B13","volume-title":"Learning to Classify Text Using Support Vector Machines: Methods, Theory and Algorithms.","author":"Joachims","year":"2003"},{"key":"2023013112155584800_B14","doi-asserted-by":"crossref","first-page":"594","DOI":"10.1093\/bioinformatics\/btm630","article-title":"NetworkBLAST: comparative analysis of protein networks","volume":"24","author":"Kalaev","year":"2008","journal-title":"Bioinformatics"},{"key":"2023013112155584800_B15","doi-asserted-by":"crossref","first-page":"D480","DOI":"10.1093\/nar\/gkm882","article-title":"KEGG for linking genomes to life and the environment","volume":"36","author":"Kanehisa","year":"2008","journal-title":"Nucleic Acids Res."},{"key":"2023013112155584800_B16","first-page":"1099","article-title":"Link Propagation: a fast semi-supervised learning algorithm for link prediction","volume-title":"Proceedings of the 2009 SIAM Conference on Data Mining (SDM)","author":"Kashima","year":"2009"},{"key":"2023013112155584800_B17","doi-asserted-by":"crossref","first-page":"2488","DOI":"10.1093\/bioinformatics\/bti339","article-title":"Selective integration of multiple biological data for supervised network inference","volume":"21","author":"Kato","year":"2005","journal-title":"Bioinformatics"},{"key":"2023013112155584800_B18","doi-asserted-by":"crossref","first-page":"449","DOI":"10.1093\/bioinformatics\/bth930","article-title":"Filling gaps in a metabolic network using expression information","volume":"20","author":"Kharchenko","year":"2004","journal-title":"Bioinformatics"},{"key":"2023013112155584800_B19","doi-asserted-by":"crossref","DOI":"10.1137\/1.9780898717907","volume-title":"Matrix Analysis for Scientists and Engineers.","author":"Laub","year":"2005"},{"key":"2023013112155584800_B20","doi-asserted-by":"crossref","first-page":"2120","DOI":"10.1101\/gr.205301","article-title":"Identification of potential interaction networks using sequence based searches for conserved protein-protein interactions or \u2018interlogs\u2019","volume":"11","author":"Matthews","year":"2001","journal-title":"Genome Res."},{"key":"2023013112155584800_B21","doi-asserted-by":"crossref","first-page":"W182","DOI":"10.1093\/nar\/gkm321","article-title":"KAAS: an automatic genome annotation and pathway reconstruction server","volume":"35","author":"Moriya","year":"2007","journal-title":"Nucleic Acids Res."},{"issue":"Suppl. 1","key":"2023013112155584800_B22","doi-asserted-by":"crossref","first-page":"S4","DOI":"10.1186\/gb-2008-9-s1-s4","article-title":"GeneMANIA: a real-time multiple association network integration algorithm for predicting gene function","volume":"9","author":"Mostafavi","year":"2008","journal-title":"Genome Biol."},{"key":"2023013112155584800_B23","doi-asserted-by":"crossref","first-page":"2004","DOI":"10.1093\/bioinformatics\/btm266","article-title":"Statistical prediction of protein chemical interactions based on chemical structure and mass spectrometry data","volume":"23","author":"Nagamine","year":"2007","journal-title":"Bioinformatics"},{"key":"2023013112155584800_B24","doi-asserted-by":"crossref","first-page":"2896","DOI":"10.1073\/pnas.96.6.2896","article-title":"The use of gene clusters to infer functional coupling","volume":"96","author":"Overbeek","year":"1999","journal-title":"Proc. Natl Acad. Sci. USA"},{"key":"2023013112155584800_B25","first-page":"322","article-title":"Using feature conjunctions across examples for learning pairwise classifiers","volume-title":"Proceedings of the 15th European Conference on Machine Learning (ECML)","author":"Oyama","year":"2004"},{"key":"2023013112155584800_B26","doi-asserted-by":"crossref","first-page":"4285","DOI":"10.1073\/pnas.96.8.4285","article-title":"Assigning protein functions by comparative genome analysis: protein phylogenetic profiles","volume":"96","author":"Pellegrini","year":"1999","journal-title":"Proc. Natl Acad. Sci. USA"},{"issue":"Suppl. 10","key":"2023013112155584800_B27","doi-asserted-by":"crossref","first-page":"S6","DOI":"10.1186\/1471-2105-8-S10-S6","article-title":"A mixture of feature experts approach for protein-protein interaction prediction","volume":"8","author":"Qi","year":"2007","journal-title":"BMC Bioinformatics"},{"key":"2023013112155584800_B28","doi-asserted-by":"crossref","first-page":"951","DOI":"10.1038\/nbt1103","article-title":"A probabilistic model of the human protein-protein interaction network","volume":"23","author":"Rhodes","year":"2005","journal-title":"Nat. Biotechnol."},{"key":"2023013112155584800_B29","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1016\/0022-2836(81)90087-5","article-title":"Identification of common molecular subsequences","volume":"147","author":"Smith","year":"1981","journal-title":"J. Mol. Biol."},{"key":"2023013112155584800_B30","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1126\/science.1087447","article-title":"A gene-coexpression network for global discovery of conserved genetic modules","volume":"302","author":"Stuart","year":"2003","journal-title":"Science"},{"key":"2023013112155584800_B31","doi-asserted-by":"crossref","first-page":"1295","DOI":"10.1142\/S0219720005001569","article-title":"Utilizing evolutionary information and gene expression data for estimating gene networks with bayesian network models","volume":"3","author":"Tamada","year":"2005","journal-title":"J. Bioinform. Comput. Biol."},{"issue":"Suppl. 2","key":"2023013112155584800_B32","article-title":"Fast protein classification with multiple networks","volume":"21","author":"Tsuda","year":"2005","journal-title":"Bioinformatics"},{"key":"2023013112155584800_B33","article-title":"Supervised graph inference","volume-title":"Advances in Neural Information Processing Systems 15.","author":"Vert","year":"2005"},{"issue":"Suppl. 10","key":"2023013112155584800_B34","doi-asserted-by":"crossref","first-page":"S8","DOI":"10.1186\/1471-2105-8-S10-S8","article-title":"A new pairwise kernel for biological network inference with support vector machines","volume":"8","author":"Vert","year":"2007","journal-title":"BMC Bioinformatics"},{"key":"2023013112155584800_B35","doi-asserted-by":"crossref","DOI":"10.7551\/mitpress\/7503.003.0186","article-title":"Fast computation of graph kernels","volume-title":"Advances in Neural Information Processing Systems 19.","author":"Vishwanathan","year":"2007"},{"key":"2023013112155584800_B36","doi-asserted-by":"crossref","first-page":"116","DOI":"10.1126\/science.287.5450.116","article-title":"Protein interaction mapping in C.elegans using proteins involved in vulval development","volume":"287","author":"Walhout","year":"2000","journal-title":"Science"},{"key":"2023013112155584800_B37","doi-asserted-by":"crossref","first-page":"6559","DOI":"10.1073\/pnas.0308067101","article-title":"Protein ranking: from local to global structure in the protein similarity network","volume":"101","author":"Weston","year":"2004","journal-title":"Proc. Natl Acad. Sci. USA"},{"key":"2023013112155584800_B38","article-title":"Supervised bipartite graph inference","volume-title":"Advances in Neural Information Processing Systems 21.","author":"Yamanishi","year":"2009"},{"issue":"Suppl. 1","key":"2023013112155584800_B39","doi-asserted-by":"crossref","first-page":"i363","DOI":"10.1093\/bioinformatics\/bth910","article-title":"Protein network inference from multiple genomic data: a supervised approach","volume":"20","author":"Yamanishi","year":"2004","journal-title":"Bioinformatics"},{"key":"2023013112155584800_B40","doi-asserted-by":"crossref","first-page":"i468","DOI":"10.1093\/bioinformatics\/bti1012","article-title":"Supervised enzyme network inference from the integration of genomic data and chemical information","volume":"21","author":"Yamanishi","year":"2005","journal-title":"Bioinformatics"},{"key":"2023013112155584800_B41","doi-asserted-by":"crossref","first-page":"i232","DOI":"10.1093\/bioinformatics\/btn162","article-title":"Prediction of drug-target interaction networks from the integration of chemical and genomic spaces","volume":"24","author":"Yamanishi","year":"2008","journal-title":"Bioinformatics"},{"key":"2023013112155584800_B42","first-page":"321","article-title":"Learning with local and global consistency","volume-title":"Advances in Neural Information Processing Systems 16","author":"Zhou","year":"2004"},{"key":"2023013112155584800_B43","article-title":"Semi-supervised learning using Gaussian fields and harmonic functions","volume-title":"Proceedings of the 20th International Conference on Machine Learning (ICML).","author":"Zhu","year":"2003"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/25\/22\/2962\/48998166\/bioinformatics_25_22_2962.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/25\/22\/2962\/48998166\/bioinformatics_25_22_2962.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,15]],"date-time":"2024-03-15T23:05:31Z","timestamp":1710543931000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/25\/22\/2962\/179150"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2009,8,17]]},"references-count":43,"journal-issue":{"issue":"22","published-print":{"date-parts":[[2009,11,15]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btp494","relation":{},"ISSN":["1367-4811","1367-4803"],"issn-type":[{"value":"1367-4811","type":"electronic"},{"value":"1367-4803","type":"print"}],"subject":[],"published-other":{"date-parts":[[2009,11,15]]},"published":{"date-parts":[[2009,8,17]]}}}