{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,4,3]],"date-time":"2022-04-03T15:51:37Z","timestamp":1649001097155},"reference-count":20,"publisher":"World Scientific Pub Co Pte Lt","issue":"02","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Bioinform. Comput. Biol."],"published-print":{"date-parts":[[2006,4]]},"abstract":"<jats:p> The polymerase chain reaction (PCR) is a fundamental tool of molecular biology. Quantitative PCR is the gold-standard methodology for determination of DNA copy numbers, quantitating transcription, and numerous other applications. A major barrier to large-scale application of PCR for quantitative genomic analyses is the current requirement for manual validation of individual PCRs to ensure generation of a single product. This typically requires visual inspection either of gel electrophoreses or temperature dissociation (\"melting\") curves of individual PCRs \u2014 a time-consuming and costly process. <\/jats:p><jats:p> Here we describe a robust computational solution to this fundamental problem. Using a training set of 10 080 reactions comprising multiple quantitative PCRs from each of 1728 unique human genomic amplicons, we developed a support vector machine classifier capable of discriminating single-product PCRs with better than 99% accuracy. This approach has broad utility, and eliminates a major bottleneck to widespread application of PCR for high-throughput genomic applications. <\/jats:p>","DOI":"10.1142\/s0219720006001989","type":"journal-article","created":{"date-parts":[[2006,7,10]],"date-time":"2006-07-10T03:00:12Z","timestamp":1152500412000},"page":"299-315","source":"Crossref","is-referenced-by-count":0,"title":["AUTOMATED VALIDATION OF POLYMERASE CHAIN REACTION AMPLICON MELTING CURVES"],"prefix":"10.1142","volume":"04","author":[{"given":"TOBIAS P.","family":"MANN","sequence":"first","affiliation":[{"name":"Department of Genome Sciences, University of Washington, Seattle, WA, USA"}]},{"given":"RICHARD","family":"HUMBERT","sequence":"additional","affiliation":[{"name":"Department of Genome Sciences, University of Washington, Seattle, WA, USA"}]},{"given":"JOHN A.","family":"STAMATOYANNOPOLOUS","sequence":"additional","affiliation":[{"name":"Department of Genome Sciences, University of Washington, Seattle, WA, USA"}]},{"given":"WILLIAM STAFFORD","family":"NOBLE","sequence":"additional","affiliation":[{"name":"Department of Genome Sciences, University of Washington, Seattle, WA, USA"}]}],"member":"219","published-online":{"date-parts":[[2011,11,21]]},"reference":[{"key":"rf1","doi-asserted-by":"publisher","DOI":"10.1038\/nrg798"},{"key":"rf2","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511801389"},{"key":"rf3","doi-asserted-by":"publisher","DOI":"10.1038\/nmeth721"},{"key":"rf4","volume-title":"Pattern Classification","author":"Duda R. 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