{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,22]],"date-time":"2026-02-22T05:41:25Z","timestamp":1771738885049,"version":"3.50.1"},"reference-count":48,"publisher":"Springer Science and Business Media LLC","issue":"S10","content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Bioinformatics"],"published-print":{"date-parts":[[2012,6]]},"abstract":"<jats:title>Abstract<\/jats:title>\n          <jats:sec>\n            <jats:title>Background<\/jats:title>\n            <jats:p>A wealth of clustering algorithms has been applied to gene co-expression experiments. These algorithms cover a broad range of approaches, from conventional techniques such as <jats:italic>k<\/jats:italic>-means and hierarchical clustering, to graphical approaches such as <jats:italic>k<\/jats:italic>-clique communities, weighted gene co-expression networks (WGCNA) and paraclique. Comparison of these methods to evaluate their relative effectiveness provides guidance to algorithm selection, development and implementation. Most prior work on comparative clustering evaluation has focused on parametric methods. Graph theoretical methods are recent additions to the tool set for the global analysis and decomposition of microarray co-expression matrices that have not generally been included in earlier methodological comparisons. In the present study, a variety of parametric and graph theoretical clustering algorithms are compared using well-characterized transcriptomic data at a genome scale from <jats:italic>Saccharomyces cerevisiae<\/jats:italic>.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Methods<\/jats:title>\n            <jats:p>For each clustering method under study, a variety of parameters were tested. Jaccard similarity was used to measure each cluster's agreement with every GO and KEGG annotation set, and the highest Jaccard score was assigned to the cluster. Clusters were grouped into small, medium, and large bins, and the Jaccard score of the top five scoring clusters in each bin were averaged and reported as the best average top 5 (BAT5) score for the particular method.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Results<\/jats:title>\n            <jats:p>Clusters produced by each method were evaluated based upon the positive match to known pathways. This produces a readily interpretable ranking of the relative effectiveness of clustering on the genes. Methods were also tested to determine whether they were able to identify clusters consistent with those identified by other clustering methods.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Conclusions<\/jats:title>\n            <jats:p>Validation of clusters against known gene classifications demonstrate that for this data, graph-based techniques outperform conventional clustering approaches, suggesting that further development and application of combinatorial strategies is warranted.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1186\/1471-2105-13-s10-s7","type":"journal-article","created":{"date-parts":[[2012,6,29]],"date-time":"2012-06-29T16:35:52Z","timestamp":1340987752000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":47,"title":["A systematic comparison of genome-scale clustering algorithms"],"prefix":"10.1186","volume":"13","author":[{"given":"Jeremy J","family":"Jay","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"John D","family":"Eblen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yun","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mikael","family":"Benson","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Andy D","family":"Perkins","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Arnold M","family":"Saxton","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Brynn H","family":"Voy","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Elissa J","family":"Chesler","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Michael A","family":"Langston","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2012,6,25]]},"reference":[{"issue":"11","key":"5212_CR1","doi-asserted-by":"publisher","first-page":"1370","DOI":"10.1109\/TKDE.2004.68","volume":"16","author":"DX Jiang","year":"2004","unstructured":"Jiang DX, Tang C, Zhang AD: Cluster analysis for gene expression data: A survey. IEEE Trans Knowl Data Eng. 2004, 16 (11): 1370-1386. 10.1109\/TKDE.2004.68.","journal-title":"IEEE Trans Knowl Data Eng"},{"issue":"6","key":"5212_CR2","doi-asserted-by":"publisher","first-page":"418","DOI":"10.1038\/35076576","volume":"2","author":"J Quackenbush","year":"2001","unstructured":"Quackenbush J: Computational analysis of microarray data. Nat Rev Genet. 2001, 2 (6): 418-427. 10.1038\/35076576.","journal-title":"Nat Rev Genet"},{"issue":"3","key":"5212_CR3","doi-asserted-by":"publisher","first-page":"283","DOI":"10.1016\/j.compbiomed.2007.11.001","volume":"38","author":"G Kerr","year":"2008","unstructured":"Kerr G, Ruskin HJ, Crane M, Doolan P: Techniques for clustering gene expression data. Comput Biol Med. 2008, 38 (3): 283-293. 10.1016\/j.compbiomed.2007.11.001.","journal-title":"Comput Biol Med"},{"issue":"1","key":"5212_CR4","doi-asserted-by":"publisher","first-page":"116","DOI":"10.1089\/omi.2006.0008","volume":"11","author":"T Laderas","year":"2007","unstructured":"Laderas T, Mcweeney S: Consensus framework for exploring microarray data using multiple clustering methods. Omics. 2007, 11 (1): 116-128. 10.1089\/omi.2006.0008.","journal-title":"Omics"},{"issue":"1","key":"5212_CR5","doi-asserted-by":"publisher","first-page":"187","DOI":"10.1186\/1471-2164-7-187","volume":"7","author":"CL Myers","year":"2006","unstructured":"Myers CL, Barrett DR, Hibbs MA, Huttenhower C, Troyanskaya OG: Finding function: evaluation methods for functional genomic data. BMC Genomics. 2006, 7 (1): 187-10.1186\/1471-2164-7-187.","journal-title":"BMC Genomics"},{"issue":"1","key":"5212_CR6","doi-asserted-by":"publisher","first-page":"462","DOI":"10.1186\/1471-2105-9-462","volume":"9","author":"R Giancarlo","year":"2008","unstructured":"Giancarlo R, Scaturro D, Utro F: Computational cluster validation for microarray data analysis: experimental assessment of Clest, Consensus Clustering, Figure of Merit, Gap Statistics and Model Explorer. BMC Bioinformatics. 2008, 9 (1): 462-10.1186\/1471-2105-9-462.","journal-title":"BMC Bioinformatics"},{"issue":"1","key":"5212_CR7","doi-asserted-by":"publisher","first-page":"497","DOI":"10.1186\/1471-2105-9-497","volume":"9","author":"MC de Souto","year":"2008","unstructured":"de Souto MC, Costa IG, de Araujo DS, Ludermir TB, Schliep A: Clustering cancer gene expression data: a comparative study. BMC Bioinformatics. 2008, 9 (1): 497-10.1186\/1471-2105-9-497.","journal-title":"BMC Bioinformatics"},{"issue":"3","key":"5212_CR8","doi-asserted-by":"publisher","first-page":"1742","DOI":"10.1016\/j.ejor.2005.03.039","volume":"174","author":"SA Mingoti","year":"2006","unstructured":"Mingoti SA, Lima JO: Comparing SOM neural network with Fuzzy c-means, K-means and traditional hierarchical clustering algorithms. Eur J Oper Res. 2006, 174 (3): 1742-1759. 10.1016\/j.ejor.2005.03.039.","journal-title":"Eur J Oper Res"},{"issue":"1","key":"5212_CR9","doi-asserted-by":"publisher","first-page":"397","DOI":"10.1186\/1471-2105-7-397","volume":"7","author":"S Datta","year":"2006","unstructured":"Datta S, Datta S: Methods for evaluating clustering algorithms for gene expression data using a reference set of functional classes. BMC Bioinformatics. 2006, 7 (1): 397-10.1186\/1471-2105-7-397.","journal-title":"BMC Bioinformatics"},{"issue":"1","key":"5212_CR10","doi-asserted-by":"publisher","first-page":"100","DOI":"10.2307\/2346830","volume":"28","author":"JA Hartigan","year":"1979","unstructured":"Hartigan JA, Wong MA: Algorithm AS 136: A K-Means Clustering Algorithm. Appl Stat. 1979, 28 (1): 100-108. 10.2307\/2346830.","journal-title":"Appl Stat"},{"issue":"4","key":"5212_CR11","doi-asserted-by":"publisher","first-page":"825","DOI":"10.1177\/001316446602600402","volume":"26","author":"LL McQuitty","year":"1966","unstructured":"McQuitty LL: Similarity Analysis by Reciprocal Pairs for Discrete and Continuous Data. Educ Psychol Meas. 1966, 26 (4): 825-831. 10.1177\/001316446602600402.","journal-title":"Educ Psychol Meas"},{"issue":"301","key":"5212_CR12","doi-asserted-by":"publisher","first-page":"236","DOI":"10.1080\/01621459.1963.10500845","volume":"58","author":"JH Ward","year":"1963","unstructured":"Ward JH: Hierarchical Grouping to Optimize an Objective Function. J Am Stat Assoc. 1963, 58 (301): 236-244. 10.1080\/01621459.1963.10500845.","journal-title":"J Am Stat Assoc"},{"issue":"7043","key":"5212_CR13","doi-asserted-by":"publisher","first-page":"814","DOI":"10.1038\/nature03607","volume":"435","author":"G Palla","year":"2005","unstructured":"Palla G, Derenyi I, Farkas I, Vicsek T: Uncovering the overlapping community structure of complex networks in nature and society. Nature. 2005, 435 (7043): 814-818. 10.1038\/nature03607.","journal-title":"Nature"},{"key":"5212_CR14","doi-asserted-by":"crossref","unstructured":"Zhang B, Horvath S: A general framework for weighted gene co-expression network analysis. Stat Appl Genet Mol. 2005, 4 (1):","DOI":"10.2202\/1544-6115.1128"},{"issue":"1","key":"5212_CR15","doi-asserted-by":"publisher","first-page":"250","DOI":"10.1186\/1471-2105-8-250","volume":"8","author":"C Huttenhower","year":"2007","unstructured":"Huttenhower C, Flamholz AI, Landis JN, Sahi S, Myers CL, Olszewski KL, Hibbs MA, Siemers NO, Troyanskaya OG, Coller HA: Nearest Neighbor Networks: clustering expression data based on gene neighborhoods. BMC Bioinformatics. 2007, 8 (1): 250-10.1186\/1471-2105-8-250.","journal-title":"BMC Bioinformatics"},{"issue":"3-4","key":"5212_CR16","doi-asserted-by":"publisher","first-page":"281","DOI":"10.1089\/106652799318274","volume":"6","author":"A Ben-Dor","year":"1999","unstructured":"Ben-Dor A, Shamir R, Yakhini Z: Clustering gene expression patterns. J Comp Biol. 1999, 6 (3-4): 281-297. 10.1089\/106652799318274.","journal-title":"J Comp Biol"},{"issue":"14","key":"5212_CR17","doi-asserted-by":"publisher","first-page":"1787","DOI":"10.1093\/bioinformatics\/btg232","volume":"19","author":"R Sharan","year":"2003","unstructured":"Sharan R, Maron-Katz A, Shamir R: CLICK and EXPANDER: a system for clustering and visualizing gene expression data. Bioinformatics. 2003, 19 (14): 1787-1799. 10.1093\/bioinformatics\/btg232.","journal-title":"Bioinformatics"},{"key":"5212_CR18","volume-title":"International Conference on Research Trends in Science and Technology","author":"FN Abu-Khzam","year":"2005","unstructured":"Abu-Khzam FN, Baldwin NE, Langston MA, Samatova NF: On the Relative Efficiency of Maximal Clique Enumeration Algorithms, with Applications to High-Throughput Computational Biology. International Conference on Research Trends in Science and Technology. 2005, Beirut, Lebanon"},{"issue":"9","key":"5212_CR19","doi-asserted-by":"publisher","first-page":"575","DOI":"10.1145\/362342.362367","volume":"16","author":"C Bron","year":"1973","unstructured":"Bron C, Kerbosch K: Algorithm 457: Finding All Cliques of an Undirected Graph. Commun ACM. 1973, 16 (9): 575-577. 10.1145\/362342.362367.","journal-title":"Commun ACM"},{"key":"5212_CR20","first-page":"12","volume-title":"Supercomputing","author":"Y Zhang","year":"2005","unstructured":"Zhang Y, Abu-Khzam FN, Baldwin NE, Chesler EJ, Langston MA, Samatova NF: Genome-Scale Computational Approaches to memory-Intensive Applications in Systems Biology. Supercomputing. 2005, Seattle, Washington, 12."},{"key":"5212_CR21","first-page":"150","volume-title":"RECOMB Satellite Workshop on Systems Biology and Regulatory Genomics","author":"EJ Chesler","year":"2005","unstructured":"Chesler EJ, Langston MA: Combinatorial Genetic Regulatory Network Analysis Tools for High Throughput Transcriptomic Data. RECOMB Satellite Workshop on Systems Biology and Regulatory Genomics. 2005, San Diego, California, 150-165."},{"issue":"6","key":"5212_CR22","doi-asserted-by":"publisher","first-page":"2907","DOI":"10.1073\/pnas.96.6.2907","volume":"96","author":"P Tamayo","year":"1999","unstructured":"Tamayo P, Slonim D, Mesirov J, Zhu Q, Kitareewan S, Dmitrovsky E, Lander ES, Golub TR: Interpreting patterns of gene expression with self-organizing maps: methods and application to hematopoietic differentiation. Proc Natl Acad Sci USA. 1999, 96 (6): 2907-2912. 10.1073\/pnas.96.6.2907.","journal-title":"Proc Natl Acad Sci USA"},{"issue":"11","key":"5212_CR23","doi-asserted-by":"publisher","first-page":"1106","DOI":"10.1101\/gr.9.11.1106","volume":"9","author":"LJ Heyer","year":"1999","unstructured":"Heyer LJ, Kruglyak S, Yooseph S: Exploring expression data: identification and analysis of coexpressed genes. Genome Res. 1999, 9 (11): 1106-1115. 10.1101\/gr.9.11.1106.","journal-title":"Genome Res"},{"issue":"2","key":"5212_CR24","doi-asserted-by":"publisher","first-page":"159","DOI":"10.1007\/BF02294245","volume":"50","author":"G Milligan","year":"1985","unstructured":"Milligan G, Cooper M: An Examination of Procedures for Determining the Number of Clusters in a Data Set. Psychometrika. 1985, 50 (2): 159-179. 10.1007\/BF02294245.","journal-title":"Psychometrika"},{"issue":"19","key":"5212_CR25","doi-asserted-by":"publisher","first-page":"2405","DOI":"10.1093\/bioinformatics\/btl406","volume":"22","author":"A Thalamuthu","year":"2006","unstructured":"Thalamuthu A, Mukhopadhyay I, Zheng XJ, Tseng GC: Evaluation and comparison of gene clustering methods in microarray analysis. Bioinformatics. 2006, 22 (19): 2405-2412. 10.1093\/bioinformatics\/btl406.","journal-title":"Bioinformatics"},{"issue":"15","key":"5212_CR26","doi-asserted-by":"publisher","first-page":"3201","DOI":"10.1093\/bioinformatics\/bti517","volume":"21","author":"J Handl","year":"2005","unstructured":"Handl J, Knowles J, Kell DB: Computational Clustering Validation in Postgenomic Data Analysis. Bioinformatics. 2005, 21 (15): 3201-3212. 10.1093\/bioinformatics\/bti517.","journal-title":"Bioinformatics"},{"issue":"4","key":"5212_CR27","doi-asserted-by":"publisher","first-page":"309","DOI":"10.1093\/bioinformatics\/17.4.309","volume":"17","author":"KY Yeung","year":"2001","unstructured":"Yeung KY, Haynor DR, Ruzzo WL: Validating clustering for gene expression data. Bioinformatics. 2001, 17 (4): 309-318. 10.1093\/bioinformatics\/17.4.309.","journal-title":"Bioinformatics"},{"issue":"1","key":"5212_CR28","doi-asserted-by":"publisher","first-page":"288","DOI":"10.1186\/1471-2105-9-288","volume":"9","author":"J Yao","year":"2008","unstructured":"Yao J, Chang C, Salmi ML, Hung YS, Loraine A, Roux SJ: Genome-scale cluster analysis of replicated microarrays using shrinkage correlation coefficient. BMC Bioinformatics. 2008, 9 (1): 288-10.1186\/1471-2105-9-288.","journal-title":"BMC Bioinformatics"},{"issue":"1","key":"5212_CR29","doi-asserted-by":"publisher","first-page":"193","DOI":"10.1007\/BF01908075","volume":"2","author":"L Hubert","year":"1985","unstructured":"Hubert L, Arabie P: Comparing Partitions. Journal of Classification. 1985, 2 (1): 193-218. 10.1007\/BF01908075.","journal-title":"Journal of Classification"},{"issue":"1","key":"5212_CR30","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: Gene Ontology: tool for the unification of biology. Nat Genet. 2000, 25 (1): 25-29. 10.1038\/75556.","journal-title":"Nat Genet"},{"issue":"383","key":"5212_CR31","first-page":"569","volume":"78","author":"DL Wallace","year":"1983","unstructured":"Wallace DL: A Method for Comparing Two hierarchical Clusterings: Comment. J Am Stat Assoc. 1983, 78 (383): 569-576.","journal-title":"J Am Stat Assoc"},{"issue":"9","key":"5212_CR32","doi-asserted-by":"publisher","first-page":"1464","DOI":"10.1093\/bioinformatics\/bth088","volume":"20","author":"T Beissbarth","year":"2004","unstructured":"Beissbarth T, Speed TP: GOstat: find statistically overrepresented Gene Ontologies within a group of genes. Bioinformatics. 2004, 20 (9): 1464-1465. 10.1093\/bioinformatics\/bth088.","journal-title":"Bioinformatics"},{"issue":"5","key":"5212_CR33","doi-asserted-by":"publisher","first-page":"P3","DOI":"10.1186\/gb-2003-4-5-p3","volume":"4","author":"G Dennis","year":"2003","unstructured":"Dennis G, Sherman BT, Hosack DA, Yang J, Gao W, Lane HC, Lempicki RA: DAVID: Database for Annotation, Visualization, and Integrated Discovery. Genome Biol. 2003, 4 (5): P3-10.1186\/gb-2003-4-5-p3.","journal-title":"Genome Biol"},{"issue":"18","key":"5212_CR34","doi-asserted-by":"publisher","first-page":"3587","DOI":"10.1093\/bioinformatics\/bti565","volume":"21","author":"P Khatri","year":"2005","unstructured":"Khatri P, Draghici S: Ontological analysis of gene expression data: current tools, limitations, and open problems. Bioinformatics. 2005, 21 (18): 3587-3595. 10.1093\/bioinformatics\/bti565.","journal-title":"Bioinformatics"},{"issue":"5287","key":"5212_CR35","doi-asserted-by":"publisher","first-page":"546","DOI":"10.1126\/science.274.5287.546","volume":"274","author":"A Goffeau","year":"1996","unstructured":"Goffeau A, Barrell B, Bussey H, David R, Dujon B, Feldmann H, Galibert F, Hoheisel J, Jacq C, Johnston M: Life with 6000 Genes. Science. 1996, 274 (5287): 546-567. 10.1126\/science.274.5287.546.","journal-title":"Science"},{"issue":"10","key":"5212_CR36","doi-asserted-by":"publisher","first-page":"2987","DOI":"10.1091\/mbc.12.10.2987","volume":"12","author":"AP Gasch","year":"2001","unstructured":"Gasch AP, Huang MX, Metzner S, Botstein D, Elledge SJ, Brown PO: Genomic expression responses to DNA-damaging agents and the regulatory role of the yeast ATR homolog Mec1p. Mol Biol Cell. 2001, 12 (10): 2987-3003.","journal-title":"Mol Biol Cell"},{"issue":"2","key":"5212_CR37","doi-asserted-by":"crossref","first-page":"374","DOI":"10.2144\/03342mt01","volume":"34","author":"AI Saeed","year":"2003","unstructured":"Saeed AI, Sharov V, White J, Li J, Liang W, Bhagabati N, Braisted J, Klapa M, Currier T, Thiagarajan M: TM4: a free, open-source system for microarray data management and analysis. Biotechniques. 2003, 34 (2): 374-378.","journal-title":"Biotechniques"},{"key":"5212_CR38","volume-title":"R: A Language and Environment for Statistical Computing","author":"R Development Core Team","year":"2011","unstructured":"R Development Core Team: R: A Language and Environment for Statistical Computing. 2011"},{"issue":"8","key":"5212_CR39","doi-asserted-by":"publisher","first-page":"1021","DOI":"10.1093\/bioinformatics\/btl039","volume":"22","author":"B Adamcsek","year":"2006","unstructured":"Adamcsek B, Palla G, Farkas IJ, Derenyi I, Vicsek T: CFinder: locating clique and overlapping modules in biological networks. Bioinformatics. 2006, 22 (8): 1021-1023. 10.1093\/bioinformatics\/btl039.","journal-title":"Bioinformatics"},{"key":"5212_CR40","doi-asserted-by":"publisher","first-page":"D480","DOI":"10.1093\/nar\/gkm882","volume":"36","author":"M Kanehisa","year":"2008","unstructured":"Kanehisa M, Araki M, Goto S, Hattori M, Hirakawa M, Itoh M, Katayama T, Kawashima S, Okuda S, Tokimatsu T: KEGG for linking genomes to life and the environment. Nucleic Acids Res. 2008, 36: D480-D484.","journal-title":"Nucleic Acids Res"},{"issue":"1","key":"5212_CR41","doi-asserted-by":"publisher","first-page":"235","DOI":"10.1093\/nar\/28.1.235","volume":"28","author":"HM Berman","year":"2000","unstructured":"Berman HM, Westbrook J, Feng Z, Gilliland G, Bhat TN, Weissig H, Shindyalov IN, Bourne PE: The Protein Data Bank. Nucleic Acids Res. 2000, 28 (1): 235-242. 10.1093\/nar\/28.1.235.","journal-title":"Nucleic Acids Res"},{"key":"5212_CR42","doi-asserted-by":"publisher","first-page":"D245","DOI":"10.1093\/nar\/gkm977","volume":"36","author":"N Hulo","year":"2008","unstructured":"Hulo N, Bairoch A, Bulliard V, Cerutti L, Cuche BA, de Castro E, Lachaize C, Langendijk-Genevaux PS, Sigrist CJA: The 20 years of PROSITE. Nucleic Acids Res. 2008, 36: D245-D249.","journal-title":"Nucleic Acids Res"},{"key":"5212_CR43","doi-asserted-by":"publisher","first-page":"D224","DOI":"10.1093\/nar\/gkl841","volume":"35","author":"NJ Mulder","year":"2007","unstructured":"Mulder NJ, Apweiler R, Attwood TK, Bairoch A, Bateman A, Binns D, Bork P, Buillard V, Cerutti L, Copley R: New developments in the InterPro database. Nucleic Acids Res. 2007, 35: D224-D228. 10.1093\/nar\/gkl841.","journal-title":"Nucleic Acids Res"},{"key":"5212_CR44","doi-asserted-by":"publisher","first-page":"D281","DOI":"10.1093\/nar\/gkm960","volume":"36","author":"RD Finn","year":"2008","unstructured":"Finn RD, Tate J, Mistry J, Coggill PC, Sammut SJ, Hotz HR, Ceric G, Forslund K, Eddy SR, Sonnhammer ELL: The Pfam protein families database. Nucleic Acids Res. 2008, 36: D281-D288. 10.1093\/nar\/gkn226.","journal-title":"Nucleic Acids Res"},{"issue":"5","key":"5212_CR45","doi-asserted-by":"publisher","first-page":"873","DOI":"10.1016\/j.jmva.2006.11.013","volume":"98","author":"M Meila","year":"2006","unstructured":"Meila M: Comparison clusterings-an information based distance. Journal of Multivariate Analysis. 2006, 98 (5): 873-895.","journal-title":"Journal of Multivariate Analysis"},{"issue":"22","key":"5212_CR46","doi-asserted-by":"publisher","first-page":"12182","DOI":"10.1073\/pnas.220392197","volume":"97","author":"AJ Butte","year":"2000","unstructured":"Butte AJ, Tamayo P, Slonim D, Golub TR, Kohane IS: Discovering functional relationships between RNA expression and chemotherapeutic susceptibility using relevance networks. P Natl Acad Sci USA. 2000, 97 (22): 12182-12186. 10.1073\/pnas.220392197.","journal-title":"P Natl Acad Sci USA"},{"issue":"3","key":"5212_CR47","doi-asserted-by":"publisher","first-page":"269","DOI":"10.1007\/s00453-006-1214-1","volume":"45","author":"FN Abu-Khzam","year":"2006","unstructured":"Abu-Khzam FN, Langston MA, Shanbhag P, Symons CT: Scalable Parallel Algorithms for PFT Problems. Algorithmica. 2006, 45 (3): 269-284. 10.1007\/s00453-006-1214-1.","journal-title":"Algorithmica"},{"key":"5212_CR48","doi-asserted-by":"publisher","first-page":"13","DOI":"10.1007\/11847250_2","volume-title":"International Workshop on Parameterized and Exact Computation","author":"F Dehne","year":"2006","unstructured":"Dehne F, Langston M, Luo X, Pitre S, Shaw P, Zhang Y: The Cluster Editing Problem: Implementations and Experiments. International Workshop on Parameterized and Exact Computation. 2006, Zurich, Switzerland, 13-24."}],"container-title":["BMC Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/1471-2105-13-S10-S7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,9,1]],"date-time":"2021-09-01T19:11:02Z","timestamp":1630523462000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcbioinformatics.biomedcentral.com\/articles\/10.1186\/1471-2105-13-S10-S7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2012,6]]},"references-count":48,"journal-issue":{"issue":"S10","published-print":{"date-parts":[[2012,6]]}},"alternative-id":["5212"],"URL":"https:\/\/doi.org\/10.1186\/1471-2105-13-s10-s7","relation":{},"ISSN":["1471-2105"],"issn-type":[{"value":"1471-2105","type":"electronic"}],"subject":[],"published":{"date-parts":[[2012,6]]},"assertion":[{"value":"25 June 2012","order":1,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}],"article-number":"S7"}}