{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,6]],"date-time":"2026-06-06T08:34:58Z","timestamp":1780734898748,"version":"3.54.1"},"reference-count":53,"publisher":"Springer Science and Business Media LLC","issue":"1","content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Bioinformatics"],"published-print":{"date-parts":[[2006,12]]},"abstract":"<jats:title>Abstract<\/jats:title>\n          <jats:sec>\n            <jats:title>Background<\/jats:title>\n            <jats:p>Microarray technology is generating huge amounts of data about the expression level of thousands of genes, or even whole genomes, across different experimental conditions. To extract biological knowledge, and to fully understand such datasets, it is essential to include external biological information about genes and gene products to the analysis of expression data. However, most of the current approaches to analyze microarray datasets are mainly focused on the analysis of experimental data, and external biological information is incorporated as a posterior process.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Results<\/jats:title>\n            <jats:p>In this study we present a method for the integrative analysis of microarray data based on the Association Rules Discovery data mining technique. The approach integrates gene annotations and expression data to discover intrinsic associations among both data sources based on co-occurrence patterns. We applied the proposed methodology to the analysis of gene expression datasets in which genes were annotated with metabolic pathways, transcriptional regulators and Gene Ontology categories. Automatically extracted associations revealed significant relationships among these gene attributes and expression patterns, where many of them are clearly supported by recently reported work.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Conclusion<\/jats:title>\n            <jats:p>The integration of external biological information and gene expression data can provide insights about the biological processes associated to gene expression programs. In this paper we show that the proposed methodology is able to integrate multiple gene annotations and expression data in the same analytic framework and extract meaningful associations among heterogeneous sources of data. An implementation of the method is included in the Eng<jats:italic>e<\/jats:italic> ne software package.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1186\/1471-2105-7-54","type":"journal-article","created":{"date-parts":[[2006,2,10]],"date-time":"2006-02-10T07:15:12Z","timestamp":1139555712000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":80,"title":["Integrated analysis of gene expression by association rules discovery"],"prefix":"10.1186","volume":"7","author":[{"given":"Pedro","family":"Carmona-Saez","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Monica","family":"Chagoyen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andres","family":"Rodriguez","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Oswaldo","family":"Trelles","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jose M","family":"Carazo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alberto","family":"Pascual-Montano","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2006,2,7]]},"reference":[{"key":"793_CR1","volume-title":"Annu Rev Biochem","author":"RB Stoughton","year":"2004","unstructured":"Stoughton RB: Applications of DNA Microarrays in Biology. Annu Rev Biochem 2004."},{"key":"793_CR2","first-page":"317","volume":"8","author":"H Shatkay","year":"2000","unstructured":"Shatkay H, Edwards S, Wilbur WJ, Boguski M: Genes, themes and microarrays: using information retrieval for large-scale gene analysis. Proc Int Conf Intell Syst Mol Biol 2000, 8: 317\u2013328.","journal-title":"Proc Int Conf Intell Syst Mol Biol"},{"key":"793_CR3","doi-asserted-by":"publisher","first-page":"340","DOI":"10.1016\/S0959-440X(00)00212-8","volume":"11","author":"RB Altman","year":"2001","unstructured":"Altman RB, Raychaudhuri S: Whole-genome expression analysis: challenges beyond clustering. Curr Opin Struct Biol 2001, 11: 340\u2013347.","journal-title":"Curr Opin Struct Biol"},{"key":"793_CR4","first-page":"93","volume":"8","author":"Y Cheng","year":"2000","unstructured":"Cheng Y, Church GM: Biclustering of expression data. Proc Int Conf Intell Syst Mol Biol 2000, 8: 93\u2013103.","journal-title":"Proc Int Conf Intell Syst Mol Biol"},{"key":"793_CR5","doi-asserted-by":"publisher","first-page":"1706","DOI":"10.1101\/gr.903503","volume":"13","author":"PM Kim","year":"2003","unstructured":"Kim PM, Tidor B: Subsystem identification through dimensionality reduction of large-scale gene expression data. Genome Res 2003, 13: 1706\u20131718.","journal-title":"Genome Res"},{"key":"793_CR6","doi-asserted-by":"publisher","first-page":"12079","DOI":"10.1073\/pnas.210134797","volume":"97","author":"G Getz","year":"2000","unstructured":"Getz G, Levine E, Domany E: Coupled two-way clustering analysis of gene microarray data. Proc Natl Acad Sci U S A 2000, 97: 12079\u201312084.","journal-title":"Proc Natl Acad Sci U S A"},{"key":"793_CR7","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/gb-2002-3-11-research0059","volume":"3","author":"AP Gasch","year":"2002","unstructured":"Gasch AP, Eisen MB: Exploring the conditional coregulation of yeast gene expression through fuzzy k-means clustering. Genome Biol 2002, 3: 1\u201322.","journal-title":"Genome Biol"},{"key":"793_CR8","doi-asserted-by":"publisher","first-page":"34","DOI":"10.1093\/bib\/6.1.34","volume":"6","author":"OG Troyanskaya","year":"2005","unstructured":"Troyanskaya OG: Putting microarrays in a context: integrated analysis of diverse biological data. Brief Bioinform 2005, 6: 34\u201343.","journal-title":"Brief Bioinform"},{"key":"793_CR9","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/gb-2002-3-12-research0067","volume":"3","author":"C Becquet","year":"2002","unstructured":"Becquet C, Blachon S, Jeudy B, Boulicaut JF, Gandrillon O: Strong-association-rule mining for large-scale gene-expression data analysis: a case study on human SAGE data. Genome Biol 2002, 3: 1\u201316.","journal-title":"Genome Biol"},{"key":"793_CR10","doi-asserted-by":"publisher","first-page":"79","DOI":"10.1093\/bioinformatics\/19.1.79","volume":"19","author":"C Creighton","year":"2003","unstructured":"Creighton C, Hanash S: Mining gene expression databases for association rules. Bioinformatics 2003, 19: 79\u201386.","journal-title":"Bioinformatics"},{"key":"793_CR11","first-page":"15","volume-title":"Proceedings of the First Virtual Conference on Genomics and Bioinformatics; 15 October 2001","author":"P Kotala","year":"2001","unstructured":"Kotala P, Perera A, Zhou JK, Mudivarthy S, Perrizo W, Deckard E: Gene expression profiling of DNA microarray data using peano count tree (p-trees). In Proceedings of the First Virtual Conference on Genomics and Bioinformatics; 15 October 2001. North Dakota State University, USA; 2001:15\u201316."},{"key":"793_CR12","doi-asserted-by":"crossref","first-page":"396","DOI":"10.1145\/775047.775104","volume-title":"Proceedings of the Eighth ACM SIGKDD International Conference on Data Mining and Knowledge Discovery; 23-26 July 2002;","author":"A Tuzhilin","year":"2002","unstructured":"Tuzhilin A, Adomavicius G: Handling very large numbers of association rules in the analysis of microarray data. In Proceedings of the Eighth ACM SIGKDD International Conference on Data Mining and Knowledge Discovery; 23\u201326 July 2002; . Edmonton, Canada; 2002:396\u2013404."},{"issue":"Suppl 2","key":"793_CR13","doi-asserted-by":"publisher","first-page":"ii123","DOI":"10.1093\/bioinformatics\/bti1121","volume":"21","author":"E Georgii","year":"2005","unstructured":"Georgii E, Richter L, Ruckert U, Kramer S: Analyzing microarray data using quantitative association rules. Bioinformatics 2005, 21(Suppl 2):ii123-ii129.","journal-title":"Bioinformatics"},{"key":"793_CR14","first-page":"406","volume-title":"Proceedings of the Third European Conference on Principles of Data Mining and Knowledge Discovery; 15\u201318 September 1999","author":"J Li","year":"1999","unstructured":"Li J, Zhang X, Dong G, Ramamohanarao K, Sun Q: Efficient Mining of High Confidience Association Rules without Support Thresholds. In Proceedings of the Third European Conference on Principles of Data Mining and Knowledge Discovery; 15\u201318 September 1999. Prague, Czech Republic; 1999:406\u2013411."},{"key":"793_CR15","doi-asserted-by":"publisher","first-page":"680","DOI":"10.1126\/science.278.5338.680","volume":"278","author":"JL DeRisi","year":"1997","unstructured":"DeRisi JL, Iyer VR, Brown PO: Exploring the metabolic and genetic control of gene expression on a genomic scale. Science 1997, 278: 680\u2013686.","journal-title":"Science"},{"key":"793_CR16","doi-asserted-by":"publisher","first-page":"83","DOI":"10.1126\/science.283.5398.83","volume":"283","author":"VR Iyer","year":"1999","unstructured":"Iyer VR, Eisen MB, Ross DT, Schuler G, Moore T, Lee JC, Trent JM, Staudt LM, Hudson J Jr, Boguski MS, Lashkari D, Shalon D, Botstein D, Brown PO: The transcriptional program in the response of human fibroblasts to serum. Science 1999, 283: 83\u201387.","journal-title":"Science"},{"key":"793_CR17","doi-asserted-by":"publisher","first-page":"657","DOI":"10.1093\/bioinformatics\/btg028","volume":"19","author":"J Garcia de la Nava","year":"2003","unstructured":"Garcia de la Nava J, Santaella DF, Cuenca Alba J, Maria Carazo J, Trelles O, Pascual-Montano A: Engene: the processing and exploratory analysis of gene expression data. Bioinformatics 2003, 19: 657\u2013658.","journal-title":"Bioinformatics"},{"key":"793_CR18","unstructured":"Engene[http:\/\/www.engene.cnb.uam.es]"},{"key":"793_CR19","unstructured":"Web site for this work[http:\/\/www.cnb.uam.es\/~pcarmona\/assocrules]"},{"key":"793_CR20","doi-asserted-by":"publisher","first-page":"42","DOI":"10.1093\/nar\/30.1.42","volume":"30","author":"M Kanehisa","year":"2002","unstructured":"Kanehisa M, Goto S, Kawashima S, Nakaya A: The KEGG databases at GenomeNet. Nucleic Acids Res 2002, 30: 42\u201346.","journal-title":"Nucleic Acids Res"},{"key":"793_CR21","doi-asserted-by":"publisher","first-page":"799","DOI":"10.1126\/science.1075090","volume":"298","author":"TI Lee","year":"2002","unstructured":"Lee TI, Rinaldi NJ, Robert F, Odom DT, Bar-Joseph Z, Gerber GK, Hannett NM, Harbison CT, Thompson CM, Simon I, Zeitlinger J, Jennings EG, Murray HL, Gordon DB, Ren B, Wyrick JJ, Tagne JB, Volkert TL, Fraenkel E, Gifford DK, Young RA: Transcriptional regulatory networks in Saccharomyces cerevisiae. Science 2002, 298: 799\u2013804.","journal-title":"Science"},{"key":"793_CR22","doi-asserted-by":"crossref","first-page":"506","DOI":"10.1128\/mr.59.3.506-531.1995","volume":"59","author":"WH Mager","year":"1995","unstructured":"Mager WH, De Kruijff AJ: Stress-induced transcriptional activation. Microbiol Rev 1995, 59: 506\u2013531.","journal-title":"Microbiol Rev"},{"key":"793_CR23","doi-asserted-by":"publisher","first-page":"1337","DOI":"10.1038\/nbt890","volume":"21","author":"Z Bar-Joseph","year":"2003","unstructured":"Bar-Joseph Z, Gerber GK, Lee TI, Rinaldi NJ, Yoo JY, Robert F, Gordon DB, Fraenkel E, Jaakkola TS, Young RA, Gifford DK: Computational discovery of gene modules and regulatory networks. Nat Biotechnol 2003, 21: 1337\u20131342.","journal-title":"Nat Biotechnol"},{"key":"793_CR24","doi-asserted-by":"publisher","first-page":"51","DOI":"10.1016\/S0168-9525(99)01936-8","volume":"16","author":"RH Morse","year":"2000","unstructured":"Morse RH: RAP, RAP, open up! New wrinkles for RAP1 in yeast. Trends Genet 2000, 16: 51\u201353.","journal-title":"Trends Genet"},{"key":"793_CR25","doi-asserted-by":"publisher","first-page":"2905","DOI":"10.1128\/MCB.14.5.2905","volume":"14","author":"S Hermann-Le Denmat","year":"1994","unstructured":"Hermann-Le Denmat S, Werner M, Sentenac A, Thuriaux P: Suppression of yeast RNA polymerase III mutations by FHL1, a gene coding for a fork head protein involved in rRNA processing. Mol Cell Biol 1994, 14: 2905\u20132913.","journal-title":"Mol Cell Biol"},{"key":"793_CR26","doi-asserted-by":"publisher","first-page":"1054","DOI":"10.1038\/nature03175","volume":"432","author":"JT Wade","year":"2004","unstructured":"Wade JT, Hall DB, Struhl K: The transcription factor Ifh1 is a key regulator of yeast ribosomal protein genes. Nature 2004, 432: 1054\u20131058.","journal-title":"Nature"},{"key":"793_CR27","doi-asserted-by":"publisher","first-page":"1058","DOI":"10.1038\/nature03200","volume":"432","author":"SB Schawalder","year":"2004","unstructured":"Schawalder SB, Kabani M, Howald I, Choudhury U, Werner M, Shore D: Growth-regulated recruitment of the essential yeast ribosomal protein gene activator Ifh1. Nature 2004, 432: 1058\u20131061.","journal-title":"Nature"},{"key":"793_CR28","first-page":"901","volume":"119","author":"T Powers","year":"2004","unstructured":"Powers T: Ribosome biogenesis: giant steps for a giant problem. Cell 2004, 119: 901\u2013902.","journal-title":"Cell"},{"key":"793_CR29","doi-asserted-by":"publisher","first-page":"969","DOI":"10.1016\/j.cell.2004.11.047","volume":"119","author":"DE Martin","year":"2004","unstructured":"Martin DE, Soulard A, Hall MN: TOR regulates ribosomal protein gene expression via PKA and the Forkhead transcription factor FHL1. Cell 2004, 119: 969\u2013979.","journal-title":"Cell"},{"key":"793_CR30","doi-asserted-by":"publisher","first-page":"14315","DOI":"10.1073\/pnas.0405353101","volume":"101","author":"RM Marion","year":"2004","unstructured":"Marion RM, Regev A, Segal E, Barash Y, Koller D, Friedman N, O'Shea EK: Sfp1 is a stress- and nutrient-sensitive regulator of ribosomal protein gene expression. Proc Natl Acad Sci U S A 2004, 101: 14315\u201314322.","journal-title":"Proc Natl Acad Sci U S A"},{"key":"793_CR31","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, Harris MA, Hill DP, Issel-Tarver L, Kasarskis A, Lewis S, Matese JC, Richardson JE, Ringwald M, Rubin GM, Sherlock G: Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet 2000, 25: 25\u201329.","journal-title":"Nat Genet"},{"key":"793_CR32","doi-asserted-by":"publisher","first-page":"E7","DOI":"10.1371\/journal.pbio.0020007","volume":"2","author":"HY Chang","year":"2004","unstructured":"Chang HY, Sneddon JB, Alizadeh AA, Sood R, West RB, Montgomery K, Chi JT, van de Rijn M, Botstein D, Brown PO: Gene expression signature of fibroblast serum response predicts human cancer progression: similarities between tumors and wounds. PLoS Biol 2004, 2: E7.","journal-title":"PLoS Biol"},{"key":"793_CR33","doi-asserted-by":"publisher","first-page":"891","DOI":"10.1172\/JCI0216500","volume":"110","author":"FR Maxfield","year":"2002","unstructured":"Maxfield FR, Wustner D: Intracellular cholesterol transport. J Clin Invest 2002, 110: 891\u2013898.","journal-title":"J Clin Invest"},{"key":"793_CR34","doi-asserted-by":"publisher","first-page":"142","DOI":"10.1111\/j.1749-6632.1996.tb18614.x","volume":"804","author":"SK Krisans","year":"1996","unstructured":"Krisans SK: Cell compartmentalization of cholesterol biosynthesis. Ann N Y Acad Sci 1996, 804: 142\u2013164.","journal-title":"Ann N Y Acad Sci"},{"key":"793_CR35","doi-asserted-by":"publisher","first-page":"100","DOI":"10.1186\/1471-2105-5-100","volume":"5","author":"R Breitling","year":"2004","unstructured":"Breitling R, Amtmann A, Herzyk P: Graph-based iterative Group Analysis enhances microarray interpretation. BMC Bioinformatics 2004, 5: 100.","journal-title":"BMC Bioinformatics"},{"key":"793_CR36","doi-asserted-by":"publisher","first-page":"1121","DOI":"10.1101\/gr.226602","volume":"12","author":"P Grosu","year":"2002","unstructured":"Grosu P, Townsend JP, Hartl DL, Cavalieri D: Pathway Processor: a tool for integrating whole-genome expression results into metabolic networks. Genome Res 2002, 12: 1121\u20131126.","journal-title":"Genome Res"},{"key":"793_CR37","doi-asserted-by":"publisher","first-page":"8961","DOI":"10.1073\/pnas.0502674102","volume":"102","author":"KH Pan","year":"2005","unstructured":"Pan KH, Lih CJ, Cohen SN: Effects of threshold choice on biological conclusions reached during analysis of gene expression by DNA microarrays. Proc Natl Acad Sci U S A 2005, 102: 8961\u20138965.","journal-title":"Proc Natl Acad Sci U S A"},{"key":"793_CR38","doi-asserted-by":"publisher","first-page":"2711","DOI":"10.1093\/bioinformatics\/bth312","volume":"20","author":"L Ji","year":"2004","unstructured":"Ji L, Tan KL: Mining gene expression data for positive and negative co-regulated gene clusters. Bioinformatics 2004, 20: 2711\u20132718.","journal-title":"Bioinformatics"},{"key":"793_CR39","doi-asserted-by":"publisher","first-page":"265","DOI":"10.1145\/253260.253327","volume-title":"Proceedings of the ACM SIGMOD Conference; 13\u201315 May 1997","author":"S Brin","year":"1997","unstructured":"Brin S, Motwani R, Silverstein C: Beyond Market Baskets: Generalizing Association Rules to Correlations. In Proceedings of the ACM SIGMOD Conference; 13\u201315 May 1997. Tucson, Arizona, USA; 1997:265\u2013276."},{"issue":"Suppl 1","key":"793_CR40","doi-asserted-by":"publisher","first-page":"i255","DOI":"10.1093\/bioinformatics\/btg1036","volume":"19","author":"A Schliep","year":"2003","unstructured":"Schliep A, Schonhuth A, Steinhoff C: Using hidden Markov models to analyze gene expression time course data. Bioinformatics 2003, 19(Suppl 1):i255\u2013263.","journal-title":"Bioinformatics"},{"key":"793_CR41","first-page":"207","volume-title":"Proceedings of the ACM SIGMOD international conference on Management of data","author":"R Agrawal","year":"1993","unstructured":"Agrawal R, Imielinski T, Swami A: Mining Association Rules between Sets of Items in Large Databases. In Proceedings of the ACM SIGMOD international conference on Management of data. Washington, D.C; 1993:207\u2013216."},{"key":"793_CR42","volume-title":"Proceedings of the IEEE ICDM Workshop on Frequent Itemset Mining Implementations; 19 November 2003","author":"C Borgelt","year":"2003","unstructured":"Borgelt C: Efficient Implementations of Apriori and Eclat. In Proceedings of the IEEE ICDM Workshop on Frequent Itemset Mining Implementations; 19 November 2003. Florida, USA; 2003."},{"key":"793_CR43","doi-asserted-by":"publisher","first-page":"962","DOI":"10.1109\/69.553164","volume":"8","author":"R Agrawal","year":"1996","unstructured":"Agrawal R, Shafer JC: Parallel Mining of Association Rules. IEEE Transactions on Knowledge and Data Engineering 1996, 8: 962\u2013969.","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"key":"793_CR44","doi-asserted-by":"publisher","first-page":"175","DOI":"10.1145\/223784.223813","volume-title":"Proccedings of the ACM SIGMOD International Conference on Management of Data; May 1995; San Jose, CA, USA","author":"JS Park","year":"1995","unstructured":"Park JS, Chen M, Yu PS: An effective hash-based algorithm for mining association rules. Proccedings of the ACM SIGMOD International Conference on Management of Data; May 1995; San Jose, CA, USA 1995, 175\u2013186."},{"key":"793_CR45","doi-asserted-by":"publisher","first-page":"493","DOI":"10.1002\/asi.20138","volume":"56","author":"A Rodr\u00edguez","year":"2005","unstructured":"Rodr\u00edguez A, Carazo JM, Trelles O: Mining Association Rules from Biological Databases. Journal of the American Society for Information Science and Technology Special issue in Bioinformatics 2005, 56: 493\u2013504.","journal-title":"Journal of the American Society for Information Science and Technology Special issue in Bioinformatics"},{"key":"793_CR46","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1145\/312129.312216","volume-title":"Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining; 15\u201318 August 1999","author":"B Liu","year":"1999","unstructured":"Liu B, Hsu W, Ma Y: Pruning and summarizing the discovered associations. In Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining; 15\u201318 August 1999. San Diego, California, USA; 1999:125\u2013134."},{"key":"793_CR47","doi-asserted-by":"publisher","first-page":"3710","DOI":"10.1093\/bioinformatics\/bth456","volume":"20","author":"EI Boyle","year":"2004","unstructured":"Boyle EI, Weng S, Gollub J, Jin H, Botstein D, Cherry JM, Sherlock G: GO::TermFinder \u2013 open source software for accessing Gene Ontology information and finding significantly enriched Gene Ontology terms associated with a list of genes. Bioinformatics 2004, 20: 3710\u20133715.","journal-title":"Bioinformatics"},{"key":"793_CR48","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4757-3235-1","volume-title":"Permutation Tests: A Practical Guide to Resampling Methods for Testing Hypotheses","author":"PI Good","year":"2000","unstructured":"Good PI: Permutation Tests: A Practical Guide to Resampling Methods for Testing Hypotheses. New York: Springer-Verlag; 2000."},{"key":"793_CR49","first-page":"140","volume-title":"Proceedings of the Fourteenth Workshop On Information Technologies And Systems 11\u201312 December 2004","author":"H Zhang","year":"2004","unstructured":"Zhang H, Padmanabhan B: Using Randomization to Determine a False Discovery Rate for Rule Discovery. Proceedings of the Fourteenth Workshop On Information Technologies And Systems 11\u201312 December 2004 2004, 140\u2013145."},{"key":"793_CR50","doi-asserted-by":"publisher","first-page":"431","DOI":"10.1101\/gr.10.4.431","volume":"10","author":"J Aach","year":"2000","unstructured":"Aach J, Rindone W, Church GM: Systematic management and analysis of yeast gene expression data. Genome Res 2000, 10: 431\u2013445.","journal-title":"Genome Res"},{"key":"793_CR51","doi-asserted-by":"publisher","first-page":"520","DOI":"10.1093\/bioinformatics\/17.6.520","volume":"17","author":"O Troyanskaya","year":"2001","unstructured":"Troyanskaya O, Cantor M, Sherlock G, Brown P, Hastie T, Tibshirani R, Botstein D, Altman RB: Missing value estimation methods for DNA microarrays. Bioinformatics 2001, 17: 520\u2013525.","journal-title":"Bioinformatics"},{"key":"793_CR52","unstructured":"Serum database[http:\/\/genome-www.stanford.edu\/serum]"},{"key":"793_CR53","doi-asserted-by":"publisher","first-page":"W449","DOI":"10.1093\/nar\/gkh409","volume":"32","author":"P Khatri","year":"2004","unstructured":"Khatri P, Bhavsar P, Bawa G, Draghici S: Onto-Tools: an ensemble of web-accessible, ontology-based tools for the functional design and interpretation of high-throughput gene expression experiments. Nucleic Acids Res 2004, 32: W449\u2013456.","journal-title":"Nucleic Acids Res"}],"container-title":["BMC Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/1471-2105-7-54.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,9,1]],"date-time":"2021-09-01T10:58:32Z","timestamp":1630493912000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcbioinformatics.biomedcentral.com\/articles\/10.1186\/1471-2105-7-54"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2006,2,7]]},"references-count":53,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2006,12]]}},"alternative-id":["793"],"URL":"https:\/\/doi.org\/10.1186\/1471-2105-7-54","relation":{},"ISSN":["1471-2105"],"issn-type":[{"value":"1471-2105","type":"electronic"}],"subject":[],"published":{"date-parts":[[2006,2,7]]},"assertion":[{"value":"29 April 2005","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 February 2006","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 February 2006","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}],"article-number":"54"}}