{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T23:09:40Z","timestamp":1775776180092,"version":"3.50.1"},"reference-count":36,"publisher":"Oxford University Press (OUP)","issue":"9","license":[{"start":{"date-parts":[[2016,10,2]],"date-time":"2016-10-02T00:00:00Z","timestamp":1475366400000},"content-version":"vor","delay-in-days":3126,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/2.0\/uk\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2008,5,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Motivation: Membrane transport proteins play a crucial role in the import and export of ions, small molecules or macromolecules across biological membranes. Currently, there are a limited number of published computational tools which enable the systematic discovery and categorization of transporters prior to costly experimental validation. To approach this problem, we utilized a nearest neighbor method which seamlessly integrates homologous search and topological analysis into a machine-learning framework.<\/jats:p>\n               <jats:p>Results: Our approach satisfactorily distinguished 484 transporter families in the Transporter Classification Database, a curated and representative database for transporters. A five-fold cross-validation on the database achieved a positive classification rate of 72.3% on average. Furthermore, this method successfully detected transporters in seven model and four non-model organisms, ranging from archaean to mammalian species. A preliminary literature-based validation has cross-validated 65.8% of our predictions on the 11 organisms, including 55.9% of our predictions overlapping with 83.6% of the predicted transporters in TransportDB.<\/jats:p>\n               <jats:p>Availability and Supplementary information: \u00a0http:\/\/bioinfo.noble.org\/manuscript-support\/transporter\/<\/jats:p>\n               <jats:p>Contact: \u00a0pzhao@noble.org<\/jats:p>","DOI":"10.1093\/bioinformatics\/btn099","type":"journal-article","created":{"date-parts":[[2008,3,13]],"date-time":"2008-03-13T00:13:54Z","timestamp":1205367234000},"page":"1129-1136","source":"Crossref","is-referenced-by-count":34,"title":["A nearest neighbor approach for automated transporter prediction and categorization from protein sequences"],"prefix":"10.1093","volume":"24","author":[{"given":"Haiquan","family":"Li","sequence":"first","affiliation":[{"name":"Bioinformatics Lab, Plant Biology Division, The Samuel Roberts Noble Foundation, Inc., 2510 Sam Noble Parkway, Ardmore, OK 73401, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xinbin","family":"Dai","sequence":"additional","affiliation":[{"name":"Bioinformatics Lab, Plant Biology Division, The Samuel Roberts Noble Foundation, Inc., 2510 Sam Noble Parkway, Ardmore, OK 73401, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xuechun","family":"Zhao","sequence":"additional","affiliation":[{"name":"Bioinformatics Lab, Plant Biology Division, The Samuel Roberts Noble Foundation, Inc., 2510 Sam Noble Parkway, Ardmore, OK 73401, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2008,3,12]]},"reference":[{"key":"2023020210003535200_B1","doi-asserted-by":"crossref","first-page":"403","DOI":"10.1016\/S0022-2836(05)80360-2","article-title":"Basic local alignment search tool","volume":"215","author":"Altschul","year":"1990","journal-title":"J. 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