{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,21]],"date-time":"2026-04-21T22:49:08Z","timestamp":1776811748968,"version":"3.51.2"},"reference-count":43,"publisher":"European Society of Computational Methods in Sciences and Engineering","issue":"5","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JCM"],"published-print":{"date-parts":[[2023,10,6]]},"abstract":"<jats:p>Meiotic recombination has a crucial role in the biological process involving double-strand DNA breaks. Recombination hotspots are regions with a size varying from 1 to 2\u00a0kb, which is closely related to the double-strand breaks. With the increasement of both sperm data and population data, it has been demonstrated that computational methods can help us to identify the recombination spots with the advantages of time-saving and cost-saving compared to experimental verification approaches. To obtain better identification performance and investigate the potential role of various DNA sequence-derived features in building computational models, we designed a computational model by extracting features including the position-specific trinucleotide propensity (PSTNP) information, the electron-ion interaction potential (EIIP) values, nucleotide composition (NC) and dinucleotide composition (DNC). Finally, the supporting vector machine (SVM) model was trained by using the 172-dimensional features selected by\u00a0means of the F-score feature ranking mode, and the accuracy of the predictor reached 98.24% in the jackknife test, which elucidates this model is a potential way for identifying recombination spots.<\/jats:p>","DOI":"10.3233\/jcm-226872","type":"journal-article","created":{"date-parts":[[2023,6,20]],"date-time":"2023-06-20T11:27:29Z","timestamp":1687260449000},"page":"2485-2496","source":"Crossref","is-referenced-by-count":1,"title":["An improved predictor for identifying recombination spots based on support vector machine"],"prefix":"10.66113","volume":"23","author":[{"given":"Linghua","family":"Kong","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xueda","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"55691","reference":[{"issue":"5","key":"10.3233\/JCM-226872_ref1","doi-asserted-by":"crossref","first-page":"360","DOI":"10.1038\/35072078","article-title":"Meiotic recombination hot spots and cold spots","volume":"2","author":"Petes","year":"2001","journal-title":"Nature Reviews Genetics."},{"issue":"1","key":"10.3233\/JCM-226872_ref2","doi-asserted-by":"crossref","first-page":"423","DOI":"10.1146\/annurev.ge.29.120195.002231","article-title":"Meiotic recombination hotspots","volume":"29","author":"Lichten","year":"1995","journal-title":"Annual Review of Genetics."},{"issue":"10","key":"10.3233\/JCM-226872_ref3","doi-asserted-by":"crossref","first-page":"e29711","DOI":"10.1371\/journal.pone.0029711","article-title":"Analysis of biological features associated with meiotic recombination hot and cold spots in Saccharomyces cerevisiae","volume":"6","author":"Hansen","year":"2011","journal-title":"Plos One."},{"issue":"suppl_2","key":"10.3233\/JCM-226872_ref4","doi-asserted-by":"crossref","first-page":"W47","DOI":"10.1093\/nar\/gkm217","article-title":"RF-DYMHC: detecting the yeast meiotic recombination hotspots and coldspots by random forest model using gapped dinucleotide composition features","volume":"35","author":"Jiang","year":"2007","journal-title":"Nucleic Acids Research."},{"key":"10.3233\/JCM-226872_ref5","doi-asserted-by":"crossref","unstructured":"Gerton JL, DeRisi J, Shroff R, Lichten M, Brown PO, Petes TD. Global mapping of meiotic recombination hotspots and coldspots in the yeast Saccharomyces cerevisiae. 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