{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,5]],"date-time":"2026-10-05T17:43:19Z","timestamp":1791222199558,"version":"4.1.0"},"reference-count":22,"publisher":"Oxford University Press (OUP)","issue":"16","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2008,8,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Motivation: Computational gene prioritization methods are useful to help identify susceptibility genes potentially being involved in genetic disease. Recently, text mining techniques have been applied to extract prior knowledge from text-based genomic information sources and this knowledge can be used to improve the prioritization process. However, the effect of various vocabularies, representations and ranking algorithms on text mining for gene prioritization is still an issue that requires systematic and comparative studies. Therefore, a benchmark study about the vocabularies, representations and ranking algorithms in gene prioritization by text mining is discussed in this article.<\/jats:p>\n               <jats:p>Results: We investigated 5 different domain vocabularies, 2 text representation schemes and 27 linear ranking algorithms for disease gene prioritization by text mining. We indexed 288 177 MEDLINE titles and abstracts with the TXTGate text profiling system and adapted the benchmark dataset of the Endeavour gene prioritization system that consists of 618 disease-causing genes. Textual gene profiles were created and their performance for prioritization were evaluated and discussed in a comparative manner. The results show that inverse document frequency-basedrepresentation of gene term vectors performs better than the term-frequency inverse document-frequency representation. The eVOC and MESH domain vocabularies perform better than Gene Ontology, Online Mendelian Inheritance in Man's and London Dysmorphology Database. The ranking algorithms based on 1-SVM, Standard Correlation and Ward linkage method provide the best performance.<\/jats:p>\n               <jats:p>Availability: The MATLAB code of the algorithm and benchmark datasets are available by request.<\/jats:p>\n               <jats:p>Contact: \u00a0shi.yu@esat.kuleuven.be<\/jats:p>\n               <jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btn291","type":"journal-article","created":{"date-parts":[[2008,8,9]],"date-time":"2008-08-09T13:08:02Z","timestamp":1218287282000},"page":"i119-i125","source":"Crossref","is-referenced-by-count":38,"title":["Comparison of vocabularies, representations and ranking algorithms for gene prioritization by text mining"],"prefix":"10.1093","volume":"24","author":[{"given":"Shi","family":"Yu","sequence":"first","affiliation":[{"name":"Bioinformatics group, SCD, Department of Electrical Engineering, Katholieke Universiteit Leuven, Kasteelpark Arenberg 10, B-3001 Heverlee, Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Steven","family":"Van Vooren","sequence":"additional","affiliation":[{"name":"Bioinformatics group, SCD, Department of Electrical Engineering, Katholieke Universiteit Leuven, Kasteelpark Arenberg 10, B-3001 Heverlee, Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Leon-Charles","family":"Tranchevent","sequence":"additional","affiliation":[{"name":"Bioinformatics group, SCD, Department of Electrical Engineering, Katholieke Universiteit Leuven, Kasteelpark Arenberg 10, B-3001 Heverlee, Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bart","family":"De Moor","sequence":"additional","affiliation":[{"name":"Bioinformatics group, SCD, Department of Electrical Engineering, Katholieke Universiteit Leuven, Kasteelpark Arenberg 10, B-3001 Heverlee, Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yves","family":"Moreau","sequence":"additional","affiliation":[{"name":"Bioinformatics group, SCD, Department of Electrical Engineering, Katholieke Universiteit Leuven, Kasteelpark Arenberg 10, B-3001 Heverlee, Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2008,8,9]]},"reference":[{"key":"2023020210500948400_B1","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1186\/1471-2105-6-55","article-title":"Speeding disease gene discovery by sequence based candidate prioritization","volume":"6","author":"Adie","year":"2005","journal-title":"BMC Bioinformatics"},{"key":"2023020210500948400_B2","doi-asserted-by":"crossref","first-page":"773","DOI":"10.1093\/bioinformatics\/btk031","article-title":"SUSPECTS: enabling fast and effective prioritization of positional candidates","volume":"22","author":"Adie","year":"2006","journal-title":"Bioinformatics"},{"key":"2023020210500948400_B3","doi-asserted-by":"crossref","first-page":"537","DOI":"10.1038\/nbt1203","article-title":"Gene prioritization through genomic data fusion","volume":"24","author":"Aerts","year":"2006","journal-title":"Nat. Biotechnol"},{"key":"2023020210500948400_B4","doi-asserted-by":"crossref","DOI":"10.1515\/9781400874668","volume-title":"Adaptive Control Processes: A Guided Tour.","author":"Bellman","year":"1961"},{"key":"2023020210500948400_B5","first-page":"125","article-title":"Kernel-based data fusion for gene prioritization","volume":"23","author":"De Bie","year":"2007","journal-title":"Proc. ISMB 2007"},{"key":"2023020210500948400_B6","unstructured":"Donoho\n              DL\n            \n          \n          High-dimensional data analysis: the curses and blessings of dimensionality\n          Neural Comput\n          2000\n          Aide-Memoire of a Lecture at AMS Conference on Math Challenges of the 21st Century\n          Available at.http:\/\/wwwstat.stanford.edu\/~donoho\/Lectures\/AMS2000\/AMS2000.html"},{"key":"2023020210500948400_B7","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1111\/j.0824-7935.2004.t01-1-00228.x","article-title":"Amultiple resampling method for learning from imbalanced data sets","volume":"20","author":"Estabrooks","year":"2004","journal-title":"Comput. Int"},{"key":"2023020210500948400_B8","doi-asserted-by":"crossref","first-page":"1011","DOI":"10.1086\/504300","article-title":"Reconstruction of a functional human gene network, with an application for prioritizing positional candidate genes","volume":"78","author":"Franke","year":"2006","journal-title":"Am. J. Hum. Genet"},{"key":"2023020210500948400_B9","doi-asserted-by":"crossref","first-page":"110","DOI":"10.1093\/bioinformatics\/18.suppl_2.S110","article-title":"A similarity-based method for genome-wide prediction of disease-relevant human genes","volume":"18","author":"Freudenberg","year":"2002","journal-title":"Bioinformatics"},{"key":"2023020210500948400_B10","doi-asserted-by":"crossref","first-page":"1132","DOI":"10.1093\/bioinformatics\/btm001","article-title":"Acomputational system to select candidate genes for complex human traits","volume":"23","author":"Gaulton","year":"2007","journal-title":"Bioinformatics"},{"key":"2023020210500948400_B11","unstructured":"Glenisson\n              P\n            \n          \n          Integrating scientific literature with large scale gene expression analysis\n          Ph.D thesis, K.U.Leuven\n          2004"},{"key":"2023020210500948400_B12","doi-asserted-by":"crossref","first-page":"R43","DOI":"10.1186\/gb-2004-5-6-r43","article-title":"TXTGate: profiling gene groups with text-based information","volume":"5","author":"Glenisson","year":"2004","journal-title":"Genome Biol"},{"key":"2023020210500948400_B13","doi-asserted-by":"crossref","first-page":"3108","DOI":"10.1093\/nar\/gkh605","article-title":"Genome-wide indentification of genes likely to be involved in human genetic disease","volume":"32","author":"Lopez-Bigas","year":"2004","journal-title":"Nucleic Acids Res"},{"key":"2023020210500948400_B14","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1186\/1471-2156-6-45","article-title":"G2D: a tool for mining genes associated with disease","volume":"6","author":"Perez-Iratxeta","year":"2005","journal-title":"BMC Genet"},{"key":"2023020210500948400_B15","doi-asserted-by":"crossref","first-page":"130","DOI":"10.1108\/eb046814","article-title":"An algorithm for suffix stripping","volume":"14","author":"Porter","year":"1980","journal-title":"Program"},{"key":"2023020210500948400_B16","doi-asserted-by":"crossref","first-page":"847","DOI":"10.1038\/35015718","article-title":"Searching for genetic determinants in the new millennium","volume":"405","author":"Risch","year":"2000","journal-title":"Nature"},{"key":"2023020210500948400_B17","doi-asserted-by":"crossref","first-page":"1443","DOI":"10.1162\/089976601750264965","article-title":"Estimating the support of a high-dimensional distribution","volume":"13","author":"Scholkopf","year":"2001","journal-title":"Neural Comput"},{"key":"2023020210500948400_B18","unstructured":"Tax\n              DMJ\n            \n          \n          One-class classification: concept-learning in the absence of counterexamples\n          Ph.D thesis\n          2002\n          Delft University of Technology"},{"key":"2023020210500948400_B19","doi-asserted-by":"crossref","first-page":"1191","DOI":"10.1016\/S0167-8655(99)00087-2","article-title":"Support vector domain description","volume":"20","author":"Tax","year":"1999","journal-title":"Pattern Recogn.Lett"},{"key":"2023020210500948400_B20","doi-asserted-by":"crossref","first-page":"1544","DOI":"10.1093\/nar\/gki296","article-title":"Integration of text- and data-mining using ontologies successfully selects disease gene candidates","volume":"33","author":"Tiffin","year":"2005","journal-title":"Nucleic Acids Res"},{"key":"2023020210500948400_B21","doi-asserted-by":"crossref","first-page":"R75","DOI":"10.1186\/gb-2003-4-11-r75","article-title":"POCUS: mining genomic sequence annotation to predict disease genes","volume":"4","author":"Turner","year":"2003","journal-title":"Genome Biol"},{"key":"2023020210500948400_B22","doi-asserted-by":"crossref","first-page":"758","DOI":"10.1093\/nar\/gki435","article-title":"GeneSeeker: extraction and integration of human diseaserelated information from web-based genetic databases","volume":"33","author":"Van Driel","year":"2005","journal-title":"Nucleic Acids Res"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/24\/16\/i119\/49051763\/bioinformatics_24_16_i119.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/24\/16\/i119\/49051763\/bioinformatics_24_16_i119.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,2,2]],"date-time":"2023-02-02T12:47:42Z","timestamp":1675342062000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/24\/16\/i119\/201087"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2008,8,9]]},"references-count":22,"journal-issue":{"issue":"16","published-print":{"date-parts":[[2008,8,15]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btn291","relation":{},"ISSN":["1367-4811","1367-4803"],"issn-type":[{"value":"1367-4811","type":"electronic"},{"value":"1367-4803","type":"print"}],"subject":[],"published-other":{"date-parts":[[2008,8,15]]},"published":{"date-parts":[[2008,8,9]]}}}