{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,7]],"date-time":"2026-04-07T16:12:16Z","timestamp":1775578336495,"version":"3.50.1"},"reference-count":76,"publisher":"Oxford University Press (OUP)","issue":"3","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016,2,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Motivation: Enhancers are of short regulatory DNA elements. They can be bound with proteins (activators) to activate transcription of a gene, and hence play a critical role in promoting gene transcription in eukaryotes. With the avalanche of DNA sequences generated in the post-genomic age, it is a challenging task to develop computational methods for timely identifying enhancers from extremely complicated DNA sequences. Although some efforts have been made in this regard, they were limited at only identifying whether a query DNA element being of an enhancer or not. According to the distinct levels of biological activities and regulatory effects on target genes, however, enhancers should be further classified into strong and weak ones in strength.<\/jats:p>\n               <jats:p>Results: In view of this, a two-layer predictor called \u2018iEnhancer-2L\u2019 was proposed by formulating DNA elements with the \u2018pseudo k-tuple nucleotide composition\u2019, into which the six DNA local parameters were incorporated. To the best of our knowledge, it is the first computational predictor ever established for identifying not only enhancers, but also their strength. Rigorous cross-validation tests have indicated that iEnhancer-2L holds very high potential to become a useful tool for genome analysis.<\/jats:p>\n               <jats:p>Availability and implementation: For the convenience of most experimental scientists, a web server for the two-layer predictor was established at http:\/\/bioinformatics.hitsz.edu.cn\/iEnhancer-2L\/, by which users can easily get their desired results without the need to go through the mathematical details.<\/jats:p>\n               <jats:p>Contact: \u00a0bliu@gordonlifescience.org, bliu@insun.hit.edu.cn, xlan@stanford.edu, kcchou@gordonlifescience.org<\/jats:p>\n               <jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btv604","type":"journal-article","created":{"date-parts":[[2015,10,18]],"date-time":"2015-10-18T01:38:30Z","timestamp":1445132310000},"page":"362-369","source":"Crossref","is-referenced-by-count":337,"title":["iEnhancer-2L: a two-layer predictor for identifying enhancers and their strength by pseudo <i>k<\/i>-tuple nucleotide composition"],"prefix":"10.1093","volume":"32","author":[{"given":"Bin","family":"Liu","sequence":"first","affiliation":[{"name":"1 School of Computer Science and Technology,"},{"name":"2 Key Laboratory of Network Oriented Intelligent Computation, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, Guangdong 518055, China,"},{"name":"3 Computational Biology, Gordon Life Science Institute, Belmont, MA 02478, USA,"}]},{"given":"Longyun","family":"Fang","sequence":"additional","affiliation":[{"name":"1 School of Computer Science and Technology,"}]},{"given":"Ren","family":"Long","sequence":"additional","affiliation":[{"name":"1 School of Computer Science and Technology,"}]},{"given":"Xun","family":"Lan","sequence":"additional","affiliation":[{"name":"4 Department of Genetics, Stanford University, Stanford, CA 94305, USA and"}]},{"given":"Kuo-Chen","family":"Chou","sequence":"additional","affiliation":[{"name":"3 Computational Biology, Gordon Life Science Institute, Belmont, MA 02478, USA,"},{"name":"5 Center of Excellence in Genomic Medicine Research (CEGMR), King Abdulaziz University, Jeddah 21589, Saudi Arabia"}]}],"member":"286","published-online":{"date-parts":[[2015,10,17]]},"reference":[{"key":"2023020110305296700_btv604-B1","doi-asserted-by":"crossref","first-page":"456","DOI":"10.1101\/gr.112656.110","article-title":"High-resolution genome-wide in\u00a0vivo footprinting of diverse transcription factors in human cells","volume":"21","author":"Boyle","year":"2011","journal-title":"Genome Res."},{"key":"2023020110305296700_btv604-B2","doi-asserted-by":"crossref","first-page":"1812","DOI":"10.1002\/j.1460-2075.1995.tb07169.x","article-title":"Sequence-dependent bending propensity of DNA as revealed by DNase I: parameters for trinucleotides","volume":"14","author":"Brukner","year":"1995","journal-title":"EMBO J."},{"key":"2023020110305296700_btv604-B3","doi-asserted-by":"crossref","first-page":"3257","DOI":"10.1016\/S0006-3495(03)70050-2","article-title":"Support vector machines for predicting membrane protein types by using functional domain composition","volume":"84","author":"Cai","year":"2003","journal-title":"Biophys. 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