{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,2,2]],"date-time":"2024-02-02T00:16:52Z","timestamp":1706833012640},"reference-count":57,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2016,9,13]],"date-time":"2016-09-13T00:00:00Z","timestamp":1473724800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2016,9,13]],"date-time":"2016-09-13T00:00:00Z","timestamp":1473724800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Bioinformatics"],"abstract":"<jats:title>Abstract<\/jats:title><jats:sec>\n                <jats:title>Background<\/jats:title>\n                <jats:p>Protein complexes are the key molecular entities to perform many essential biological functions. In recent years, high-throughput experimental techniques have generated a large amount of protein interaction data. As a consequence, computational analysis of such data for protein complex detection has received increased attention in the literature. However, most existing works focus on predicting protein complexes from a single type of data, either physical interaction data or co-complex interaction data. These two types of data provide compatible and complementary information, so it is necessary to integrate them to discover the underlying structures and obtain better performance in complex detection.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>In this study, we propose a novel multi-view clustering algorithm, called the Partially Shared Multi-View Clustering model (PSMVC), to carry out such an integrated analysis. Unlike traditional multi-view learning algorithms that focus on mining either consistent or complementary information embedded in the multi-view data, PSMVC can jointly explore the shared and specific information inherent in different views. In our experiments, we compare the complexes detected by PSMVC from single data source with those detected from multiple data sources. We observe that jointly analyzing multi-view data benefits the detection of protein complexes. Furthermore, extensive experiment results demonstrate that PSMVC performs much better than 16 state-of-the-art complex detection techniques, including ensemble clustering and data integration techniques.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusions<\/jats:title>\n                <jats:p>In this work, we demonstrate that when integrating multiple data sources, using partially shared multi-view clustering model can help to identify protein complexes which are not readily identifiable by conventional single-view-based methods and other integrative analysis methods. All the results and source codes are available on <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" ext-link-type=\"uri\" xlink:href=\"https:\/\/github.com\/Oyl-CityU\/PSMVC\">https:\/\/github.com\/Oyl-CityU\/PSMVC<\/jats:ext-link>.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1186\/s12859-016-1164-9","type":"journal-article","created":{"date-parts":[[2016,9,13]],"date-time":"2016-09-13T12:06:42Z","timestamp":1473768402000},"update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Protein complex detection based on partially shared multi-view clustering"],"prefix":"10.1186","volume":"17","author":[{"given":"Le","family":"Ou-Yang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiao-Fei","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dao-Qing","family":"Dai","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Meng-Yun","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuan","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhiyong","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hong","family":"Yan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2016,9,13]]},"reference":[{"issue":"1","key":"1164_CR1","doi-asserted-by":"publisher","first-page":"24","DOI":"10.1002\/pmic.201300230","volume":"14","author":"T Clancy","year":"2014","unstructured":"Clancy T, Hovig E. From proteomes to complexomes in the era of systems biology. Proteomics. 2014; 14(1):24\u201341.","journal-title":"Proteomics"},{"issue":"Suppl 1","key":"1164_CR2","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1186\/1471-2164-11-S1-S3","volume":"11","author":"X Li","year":"2010","unstructured":"Li X, Wu M, Kwoh CK, Ng SK. Computational approaches for detecting protein complexes from protein interaction networks: a survey. BMC Genomics. 2010; 11(Suppl 1):3.","journal-title":"BMC Genomics"},{"issue":"11","key":"1164_CR3","doi-asserted-by":"publisher","first-page":"2023","DOI":"10.1002\/prot.24365","volume":"81","author":"M Wu","year":"2013","unstructured":"Wu M, Xie Z, Li X, Kwoh CK, Zheng J. Identifying protein complexes from heterogeneous biological data. Proteins: Struct, Funct, Bioinformatics. 2013; 81(11):2023\u201333.","journal-title":"Proteins: Struct, Funct, Bioinformatics"},{"issue":"10","key":"1164_CR4","doi-asserted-by":"publisher","first-page":"1343","DOI":"10.1093\/bioinformatics\/btu034","volume":"30","author":"C Pizzuti","year":"2014","unstructured":"Pizzuti C, Rombo SE. Algorithms and tools for protein\u2013protein interaction networks clustering, with a special focus on population-based stochastic methods. Bioinformatics. 2014; 30(10):1343\u201352.","journal-title":"Bioinformatics"},{"issue":"8","key":"1164_CR5","doi-asserted-by":"publisher","first-page":"4569","DOI":"10.1073\/pnas.061034498","volume":"98","author":"T Ito","year":"2001","unstructured":"Ito T, Chiba T, Ozawa R, Yoshida M, Hattori M, Sakaki Y. A comprehensive two-hybrid analysis to explore the yeast protein interactome. Proc Nat Acad Sci. 2001; 98(8):4569\u201374.","journal-title":"Proc Nat Acad Sci"},{"issue":"3","key":"1164_CR6","doi-asserted-by":"publisher","first-page":"285","DOI":"10.1038\/nbt.2831","volume":"32","author":"SV Rajagopala","year":"2014","unstructured":"Rajagopala SV, Sikorski P, Kumar A, Mosca R, Vlasblom J, Arnold R, Franca-Koh J, Pakala SB, Phanse S, Ceol A, et al. The binary protein-protein interaction landscape of escherichia coli. Nat Biotechnol. 2014; 32(3):285\u201390.","journal-title":"Nat Biotechnol"},{"issue":"3","key":"1164_CR7","doi-asserted-by":"publisher","first-page":"439","DOI":"10.1074\/mcp.M600381-MCP200","volume":"6","author":"SR Collins","year":"2007","unstructured":"Collins SR, Kemmeren P, Zhao XC, Greenblatt JF, Spencer F, Holstege FC, Weissman JS, Krogan NJ. Toward a comprehensive atlas of the physical interactome of saccharomyces cerevisiae. Mol Cell Proteomics. 2007; 6(3):439\u201350.","journal-title":"Mol Cell Proteomics"},{"issue":"5","key":"1164_CR8","doi-asserted-by":"publisher","first-page":"1068","DOI":"10.1016\/j.cell.2012.08.011","volume":"150","author":"PC Havugimana","year":"2012","unstructured":"Havugimana PC, Hart GT, Nepusz T, Yang H, Turinsky AL, Li Z, Wang PI, Boutz DR, Fong V, Phanse S, et al. A census of human soluble protein complexes. Cell. 2012; 150(5):1068\u201381.","journal-title":"Cell"},{"issue":"1","key":"1164_CR9","doi-asserted-by":"publisher","first-page":"745","DOI":"10.1186\/s12864-015-1944-z","volume":"16","author":"XF Zhang","year":"2015","unstructured":"Zhang XF, Ou-Yang L, Hu X, Dai DQ. Identifying binary protein-protein interactions from affinity purification mass spectrometry data. BMC Genomics. 2015; 16(1):745.","journal-title":"BMC Genomics"},{"issue":"6868","key":"1164_CR10","doi-asserted-by":"publisher","first-page":"141","DOI":"10.1038\/415141a","volume":"415","author":"AC Gavin","year":"2002","unstructured":"Gavin AC, Bosche M, Krause R, Grandi P, Marzioch M, Bauer A, Schultz J, Rick JM, Michon AM, Cruciat CM, Remor M, Hofert C, Schelder M, Brajenovic M, Ruffner H, Merino A, Klein K, Hudak M, Dickson D, Rudi T, Gnau V, Bauch A, Bastuck S, Huhse B, Leutwein C, Heurtier MA, Copley RR, Edelmann A, Querfurth E, Rybin V, Drewes G, Raida M, Bouwmeester T, Bork P, Seraphin B, Kuster B, Neubauer G, Superti-Furga G. Functional organization of the yeast proteome by systematic analysis of protein complexes. Nature. 2002; 415(6868):141\u20137.","journal-title":"Nature"},{"issue":"7084","key":"1164_CR11","doi-asserted-by":"publisher","first-page":"631","DOI":"10.1038\/nature04532","volume":"440","author":"AC Gavin","year":"2006","unstructured":"Gavin AC, Aloy P, Grandi P, Krause R, Boesche M, Marzioch M, Rau C, Jensen LJ, Bastuck S, Dumpelfeld B, Edelmann A, Heurtier MA, Hoffman V, Hoefert C, Klein K, Hudak M, Michon AM, Schelder M, Schirle M, Remor M, Rudi T, Hooper S, Bauer A, Bouwmeester T, Casari G, Drewes G, Neubauer G, Rick JM, Kuster B, Bork P, Russell RB, Superti-Furga G. Proteome survey reveals modularity of the yeast cell machinery. Nature. 2006; 440(7084):631\u20136.","journal-title":"Nature"},{"key":"1164_CR12","doi-asserted-by":"crossref","unstructured":"Hu AL, Chan KC. Utilizing both topological and attribute information for protein complex identification in ppi networks. IEEE\/ACM Trans Comput Biol Bioinformatics (TCBB). 2013; 10(3):780\u201392.","DOI":"10.1109\/TCBB.2013.37"},{"key":"1164_CR13","doi-asserted-by":"publisher","first-page":"658","DOI":"10.1093\/bib\/bbu038","volume":"16","author":"B Teng","year":"2015","unstructured":"Teng B, Zhao C, Liu X, He Z. Network inference from ap-ms data: computational challenges and solutions. Brief Bioinformatics. 2015; 16:658\u201374.","journal-title":"Brief Bioinformatics"},{"issue":"1","key":"1164_CR14","doi-asserted-by":"publisher","first-page":"207","DOI":"10.1186\/1471-2105-7-207","volume":"7","author":"M Altaf-Ul-Amin","year":"2006","unstructured":"Altaf-Ul-Amin M, Shinbo Y, Mihara K, Kurokawa K, Kanaya S. Development and implementation of an algorithm for detection of protein complexes in large interaction networks. BMC Bioinformatics. 2006; 7(1):207.","journal-title":"BMC Bioinformatics"},{"issue":"1","key":"1164_CR15","doi-asserted-by":"publisher","first-page":"265","DOI":"10.1186\/1471-2105-8-265","volume":"8","author":"YR Cho","year":"2007","unstructured":"Cho YR, Hwang W, Ramanathan M, Zhang A. Semantic integration to identify overlapping functional modules in protein interaction networks. BMC Bioinformatics. 2007; 8(1):265.","journal-title":"BMC Bioinformatics"},{"issue":"1","key":"1164_CR16","doi-asserted-by":"publisher","first-page":"169","DOI":"10.1186\/1471-2105-10-169","volume":"10","author":"M Wu","year":"2009","unstructured":"Wu M, Li X, Kwoh CK, Ng SK. A core-attachment based method to detect protein complexes in ppi networks. BMC Bioinformatics. 2009; 10(1):169.","journal-title":"BMC Bioinformatics"},{"issue":"7","key":"1164_CR17","doi-asserted-by":"publisher","first-page":"933","DOI":"10.1093\/bioinformatics\/btp080","volume":"25","author":"E Georgii","year":"2009","unstructured":"Georgii E, Dietmann S, Uno T, Pagel P, Tsuda K. Enumeration of condition-dependent dense modules in protein interaction networks. Bioinformatics. 2009; 25(7):933\u201340.","journal-title":"Bioinformatics"},{"issue":"3","key":"1164_CR18","doi-asserted-by":"publisher","first-page":"607","DOI":"10.1109\/TCBB.2010.75","volume":"8","author":"J Wang","year":"2011","unstructured":"Wang J, Li M, Chen J, Pan Y. A fast hierarchical clustering algorithm for functional modules discovery in protein interaction networks. IEEE\/ACM Trans Comput Biol Bioinformatics (TCBB). 2011; 8(3):607\u201320.","journal-title":"IEEE\/ACM Trans Comput Biol Bioinformatics (TCBB)"},{"key":"1164_CR19","doi-asserted-by":"crossref","unstructured":"Zhang XF, Dai DQ, Li XX. Protein complexes discovery based on protein-protein interaction data via a regularized sparse generative network model. IEEE\/ACM Trans Comput Biol Bioinformatics (TCBB). 2012; 9(3):857\u201370.","DOI":"10.1109\/TCBB.2012.20"},{"issue":"1","key":"1164_CR20","doi-asserted-by":"publisher","first-page":"84","DOI":"10.1093\/bioinformatics\/btr621","volume":"28","author":"E Becker","year":"2012","unstructured":"Becker E, Robisson B, Chapple CE, Gu\u00e9noche A, Brun C. Multifunctional proteins revealed by overlapping clustering in protein interaction network. Bioinformatics. 2012; 28(1):84\u201390.","journal-title":"Bioinformatics"},{"issue":"8","key":"1164_CR21","doi-asserted-by":"publisher","first-page":"43092","DOI":"10.1371\/journal.pone.0043092","volume":"7","author":"XF Zhang","year":"2012","unstructured":"Zhang XF, Dai DQ, Ou-Yang L, Wu MY. Exploring overlapping functional units with various structure in protein interaction networks. PLoS ONE. 2012; 7(8):43092.","journal-title":"PLoS ONE"},{"issue":"1","key":"1164_CR22","doi-asserted-by":"publisher","first-page":"335","DOI":"10.1186\/1471-2105-15-335","volume":"15","author":"L Ou-Yang","year":"2014","unstructured":"Ou-Yang L, Dai DQ, Li XL, Wu M, Zhang XF, Yang P. Detecting temporal protein complexes from dynamic protein-protein interaction networks. BMC Bioinformatics. 2014; 15(1):335.","journal-title":"BMC Bioinformatics"},{"issue":"Suppl 2","key":"1164_CR23","doi-asserted-by":"publisher","first-page":"4","DOI":"10.1186\/1471-2164-16-S2-S4","volume":"16","author":"Y Zhang","year":"2015","unstructured":"Zhang Y, Lin H, Yang Z, Wang J. Integrating experimental and literature protein-protein interaction data for protein complex prediction. BMC Genomics. 2015; 16(Suppl 2):4.","journal-title":"BMC Genomics"},{"issue":"1","key":"1164_CR24","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s13062-015-0067-4","volume":"10","author":"CH Yong","year":"2015","unstructured":"Yong CH, Wong L. Prediction of problematic complexes from ppi networks: sparse, embedded, and small complexes. Biol Direct. 2015; 10(1):1\u201314.","journal-title":"Biol Direct"},{"issue":"15","key":"1164_CR25","doi-asserted-by":"publisher","first-page":"1891","DOI":"10.1093\/bioinformatics\/btp311","volume":"25","author":"G Liu","year":"2009","unstructured":"Liu G, Wong L, Chua HN. Complex discovery from weighted ppi networks. Bioinformatics. 2009; 25(15):1891\u20137.","journal-title":"Bioinformatics"},{"issue":"8","key":"1164_CR26","doi-asserted-by":"publisher","first-page":"1105","DOI":"10.1093\/bioinformatics\/btq078","volume":"26","author":"P Jiang","year":"2010","unstructured":"Jiang P, Singh M. Spici: a fast clustering algorithm for large biological networks. Bioinformatics. 2010; 26(8):1105\u201311.","journal-title":"Bioinformatics"},{"issue":"5","key":"1164_CR27","doi-asserted-by":"publisher","first-page":"471","DOI":"10.1038\/nmeth.1938","volume":"9","author":"T Nepusz","year":"2012","unstructured":"Nepusz T, Yu H, Paccanaro A. Detecting overlapping protein complexes in protein-protein interaction networks. Nat Methods. 2012; 9(5):471\u20132.","journal-title":"Nat Methods"},{"issue":"5","key":"1164_CR28","doi-asserted-by":"publisher","first-page":"62158","DOI":"10.1371\/journal.pone.0062158","volume":"8","author":"L Ou-Yang","year":"2013","unstructured":"Ou-Yang L, Dai DQ, Zhang XF. Protein complex detection via weighted ensemble clustering based on bayesian nonnegative matrix factorization. PLoS ONE. 2013; 8(5):62158.","journal-title":"PLoS ONE"},{"issue":"9","key":"1164_CR29","doi-asserted-by":"publisher","first-page":"1027","DOI":"10.1089\/cmb.2010.0293","volume":"19","author":"M Wu","year":"2012","unstructured":"Wu M, Li X-L, Kwoh CK, Ng SK, Wong L. Discovery of protein complexes with core-attachment structures from tandem affinity purification (tap) data. J Comput Biol. 2012; 19(9):1027\u201342.","journal-title":"J Comput Biol"},{"issue":"1","key":"1164_CR30","doi-asserted-by":"publisher","first-page":"111","DOI":"10.1093\/bioinformatics\/btq652","volume":"27","author":"G Geva","year":"2011","unstructured":"Geva G, Sharan R. Identification of protein complexes from co-immunoprecipitation data. Bioinformatics. 2011; 27(1):111\u20137.","journal-title":"Bioinformatics"},{"issue":"13","key":"1164_CR31","doi-asserted-by":"publisher","first-page":"159","DOI":"10.1093\/bioinformatics\/btr212","volume":"27","author":"Z Xie","year":"2011","unstructured":"Xie Z, Kwoh CK, Li XL, Wu M. Construction of co-complex score matrix for protein complex prediction from ap-ms data. Bioinformatics. 2011; 27(13):159\u201366.","journal-title":"Bioinformatics"},{"issue":"14","key":"1164_CR32","doi-asserted-by":"publisher","first-page":"1873","DOI":"10.1093\/bioinformatics\/bts283","volume":"28","author":"J Das","year":"2012","unstructured":"Das J, Mohammed J, Yu H. Genome-scale analysis of interaction dynamics reveals organization of biological networks. Bioinformatics. 2012; 28(14):1873\u20138.","journal-title":"Bioinformatics"},{"key":"1164_CR33","volume-title":"Proceedings of the Fourth IEEE International Conference on Data Mining","author":"S Bickel","year":"2004","unstructured":"Bickel S, Scheffer T. Multi-view clustering. In: Proceedings of the Fourth IEEE International Conference on Data Mining. Brighton: IEEE: 2004. p. 19\u201326. Computer Society."},{"issue":"Suppl 2","key":"1164_CR34","doi-asserted-by":"publisher","first-page":"13","DOI":"10.1186\/1752-0509-6-S2-S13","volume":"6","author":"CH Yong","year":"2012","unstructured":"Yong CH, Liu G, Chua HN, Wong L. Supervised maximum-likelihood weighting of composite protein networks for complex prediction. BMC Syst Biol. 2012; 6(Suppl 2):13.","journal-title":"BMC Syst Biol"},{"issue":"Suppl 5","key":"1164_CR35","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1186\/1752-0509-8-S5-S3","volume":"8","author":"CH Yong","year":"2014","unstructured":"Yong CH, Maruyama O, Wong L. Discovery of small protein complexes from ppi networks with size-specific supervised weighting. BMC Syst Biol. 2014; 8(Suppl 5):3.","journal-title":"BMC Syst Biol"},{"key":"1164_CR36","doi-asserted-by":"crossref","unstructured":"Ou-Yang L, Dai DQ, Zhang XF. Detecting protein complexes from signed protein-protein interaction networks. IEEE\/ACM Trans Comput Biol Bioinformatics (TCBB). 2015; 12(6):1333\u20131344.","DOI":"10.1109\/TCBB.2015.2401014"},{"issue":"6","key":"1164_CR37","doi-asserted-by":"publisher","first-page":"1233","DOI":"10.1109\/TNNLS.2015.2402203","volume":"26","author":"J Liu","year":"2015","unstructured":"Liu J, Jiang Y, Li Z, Zhou ZH, Lu H. Partially shared latent factor learning with multiview data. IEEE Trans Neural Netw Learn Syst. 2015; 26(6):1233\u201346.","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"issue":"7084","key":"1164_CR38","doi-asserted-by":"publisher","first-page":"637","DOI":"10.1038\/nature04670","volume":"440","author":"NJ Krogan","year":"2006","unstructured":"Krogan NJ, Cagney G, Yu H, Zhong G, Guo X, Ignatchenko A, Li J, Pu S, Datta N, Tikuisis AP, Punna T, Peregr\u00edn-Alvarez JM, Shales M, Zhang X, Davey M, Robinson MD, Paccanaro A, Bray JE, Sheung A, Beattie B, Richards DP, Canadien V, Lalev A, Mena F, Wong P, Starostine A, Canete J, Vlasblom MM, Wu S, Orsi C, Collins SR, Chandran S, Haw R, Rilstone JJ, Gandi K, Thompson NJ, Musso G, St Onge P, Ghanny S, Lam MHY, Butland G, Altaf-Ul AM, Kanaya S, Shilatifard A, O\u2019Shea E, Weissman JS, Ingles CJ, Hughes TR, Parkinson J, Gerstein M, Wodak SJ, Emili A, Greenblatt JF. Global landscape of protein complexes in the yeast saccharomyces cerevisiae. Nature. 2006; 440(7084):637\u201343.","journal-title":"Nature"},{"key":"1164_CR39","doi-asserted-by":"publisher","DOI":"10.1007\/978-0-387-84858-7","volume-title":"The Elements of Statistical Learning: Data Mining, Inference, and Prediction","author":"TJ Hastie","year":"2009","unstructured":"Hastie TJ, Tibshirani RJ, Friedman JH. The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Berlin: Springer; 2009."},{"key":"1164_CR40","volume-title":"Order Restricted Statistical Inference","author":"T Robertson","year":"1988","unstructured":"Robertson T, Wright F, Dykstra RL, Robertson T. Order Restricted Statistical Inference. New York: Wiley; 1988."},{"key":"1164_CR41","volume-title":"Advances in Neural Information Processing Systems, vol. 13","author":"DD Lee","year":"2001","unstructured":"Lee DD, Seung HS. Algorithms for Non-negative Matrix Factorization. In: Advances in Neural Information Processing Systems, vol. 13. British Columbia: Vancouver: 2001. p. 556\u2013562."},{"key":"1164_CR42","unstructured":"Chen Y, Kawadia V, Urgaonkar R. Detecting overlapping temporal community structure in time-evolving networks. 2013. arXiv preprint arXiv:1303.7226."},{"issue":"3","key":"1164_CR43","doi-asserted-by":"publisher","first-page":"825","DOI":"10.1093\/nar\/gkn1005","volume":"37","author":"S Pu","year":"2009","unstructured":"Pu S, Wong J, Turner B, Cho E, Wodak SJ. Up-to-date catalogues of yeast protein complexes. Nucleic Acids Res. 2009; 37(3):825\u201331.","journal-title":"Nucleic Acids Res"},{"issue":"suppl 1","key":"1164_CR44","doi-asserted-by":"publisher","first-page":"41","DOI":"10.1093\/nar\/gkh092","volume":"32","author":"HW Mewes","year":"2004","unstructured":"Mewes HW, Amid C, Arnold R, Frishman D, G\u00fcldener U, Mannhaupt G, M\u00fcnsterk\u00f6tter M, Pagel P, Strack N, St\u00fcmpflen V, Warfsmann J, Ruepp A. Mips: analysis and annotation of proteins from whole genomes. Nucleic Acids Res. 2004; 32(suppl 1):41\u20134.","journal-title":"Nucleic Acids Res"},{"issue":"1","key":"1164_CR45","doi-asserted-by":"publisher","first-page":"73","DOI":"10.1093\/nar\/26.1.73","volume":"26","author":"JM Cherry","year":"1998","unstructured":"Cherry JM, Adler C, Ball C, Chervitz SA, Dwight SS, Hester ET, Jia Y, Juvik G, Roe T, Schroeder M, et al. Sgd: Saccharomyces genome database. Nucleic Acids Res. 1998; 26(1):73\u20139.","journal-title":"Nucleic Acids Res"},{"issue":"1","key":"1164_CR46","doi-asserted-by":"publisher","first-page":"25","DOI":"10.1038\/75556","volume":"25","author":"M Ashburner","year":"2000","unstructured":"Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, Davis AP, Dolinski K, Dwight SS, Eppig JT, et al. Gene ontology: tool for the unification of biology. Nat Genet. 2000; 25(1):25\u20139.","journal-title":"Nat Genet"},{"issue":"1","key":"1164_CR47","doi-asserted-by":"publisher","first-page":"2","DOI":"10.1186\/1471-2105-4-2","volume":"4","author":"GD Bader","year":"2003","unstructured":"Bader GD, Hogue CW. An automated method for finding molecular complexes in large protein interaction networks. BMC Bioinformatics. 2003; 4(1):2.","journal-title":"BMC Bioinformatics"},{"issue":"1","key":"1164_CR48","doi-asserted-by":"publisher","first-page":"192","DOI":"10.1186\/1471-2105-12-192","volume":"12","author":"K Rhrissorrakrai","year":"2011","unstructured":"Rhrissorrakrai K, Gunsalus KC. Mine: module identification in networks. BMC Bioinformatics. 2011; 12(1):192.","journal-title":"BMC Bioinformatics"},{"issue":"7307","key":"1164_CR49","doi-asserted-by":"publisher","first-page":"761","DOI":"10.1038\/nature09182","volume":"466","author":"YY Ahn","year":"2010","unstructured":"Ahn YY, Bagrow JP, Lehmann S. Link communities reveal multiscale complexity in networks. Nature. 2010; 466(7307):761\u20134.","journal-title":"Nature"},{"key":"1164_CR50","unstructured":"Pizzuti C, Rombo SE. Multi-functional protein clustering in ppi networks. In: Bioinformatics Research and Development: Second International Conference, BIRD 2008, Vienna, Austria, July 7-9, 2008 Proceedings, vol. 13: 2008. p. 318. Springer Science & Business Media."},{"key":"1164_CR51","volume-title":"Proceedings of the 8th International Conference on Intelligent Data Engineering and Automated Learning","author":"C Pizzuti","year":"2007","unstructured":"Pizzuti C, Rombo SE. Pincoc: a co-clustering based approach to analyze protein-protein interaction networks. In: Proceedings of the 8th International Conference on Intelligent Data Engineering and Automated Learning. Birmingham: Springer-Verlag: 2007. p. 821\u2013830."},{"key":"1164_CR52","doi-asserted-by":"crossref","unstructured":"Pizzuti C, Rombo SE. A coclustering approach for mining large protein-protein interaction networks. IEEE\/ACM Trans Comput Biol Bioinformatics (TCBB). 2012; 9(3):717\u201330.","DOI":"10.1109\/TCBB.2011.158"},{"issue":"8","key":"1164_CR53","doi-asserted-by":"publisher","first-page":"971","DOI":"10.1089\/cmb.2009.0023","volume":"16","author":"CC Friedel","year":"2009","unstructured":"Friedel CC, Krumsiek J, Zimmer R. Bootstrapping the interactome: unsupervised identification of protein complexes in yeast. J Comput Biol. 2009; 16(8):971\u201387.","journal-title":"J Comput Biol"},{"issue":"1","key":"1164_CR54","doi-asserted-by":"publisher","first-page":"236","DOI":"10.1186\/1471-2105-8-236","volume":"8","author":"GT Hart","year":"2007","unstructured":"Hart GT, Lee I, Marcotte EM. A high-accuracy consensus map of yeast protein complexes reveals modular nature of gene essentiality. BMC Bioinformatics. 2007; 8(1):236.","journal-title":"BMC Bioinformatics"},{"issue":"6","key":"1164_CR55","doi-asserted-by":"publisher","first-page":"944","DOI":"10.1002\/pmic.200600636","volume":"7","author":"S Pu","year":"2007","unstructured":"Pu S, Vlasblom J, Emili A, Greenblatt J, Wodak SJ. Identifying functional modules in the physical interactome of saccharomyces cerevisiae. Proteomics. 2007; 7(6):944\u201360.","journal-title":"Proteomics"},{"issue":"13","key":"1164_CR56","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1093\/bioinformatics\/btm212","volume":"23","author":"S Asur","year":"2007","unstructured":"Asur S, Ucar D, Parthasarathy S. An ensemble framework for clustering protein\u2013protein interaction networks. Bioinformatics. 2007; 23(13):29\u201340.","journal-title":"Bioinformatics"},{"issue":"15","key":"1164_CR57","doi-asserted-by":"publisher","first-page":"1722","DOI":"10.1093\/bioinformatics\/btn286","volume":"24","author":"D Greene","year":"2008","unstructured":"Greene D, Cagney G, Krogan N, Cunningham P. Ensemble non-negative matrix factorization methods for clustering protein-protein interactions. Bioinformatics. 2008; 24(15):1722\u20138.","journal-title":"Bioinformatics"}],"container-title":["BMC Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12859-016-1164-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s12859-016-1164-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12859-016-1164-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,2,1]],"date-time":"2024-02-01T18:01:04Z","timestamp":1706810464000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcbioinformatics.biomedcentral.com\/articles\/10.1186\/s12859-016-1164-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,9,13]]},"references-count":57,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2016,12]]}},"alternative-id":["1164"],"URL":"https:\/\/doi.org\/10.1186\/s12859-016-1164-9","relation":{},"ISSN":["1471-2105"],"issn-type":[{"value":"1471-2105","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,9,13]]},"assertion":[{"value":"11 December 2015","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"23 July 2016","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 September 2016","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}],"article-number":"371"}}