HiXCorr: a portable high-speed X-Corr engine for high-resolution tandem mass spectrometry
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, Hyunwoo | - |
dc.contributor.author | Jo, Hosung | - |
dc.contributor.author | Park, Heejin | - |
dc.contributor.author | Paek, Eunok | - |
dc.date.accessioned | 2022-07-15T20:03:11Z | - |
dc.date.available | 2022-07-15T20:03:11Z | - |
dc.date.created | 2021-05-12 | - |
dc.date.issued | 2015-12 | - |
dc.identifier.issn | 1367-4803 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/155761 | - |
dc.description.abstract | Peptide identification is an important problem in proteomics. One of the most popular scoring schemes for peptide identification is X-Corr (cross-correlation). Since calculating X-Corr is computationally intensive, a lot of efforts have been made to develop fast X-Corr engines. However, the existing X-Corr engines are not suitable for high-resolution MS/MS spectrometry because they are either slow or require a specific type of CPU. We present a portable high-speed X-Corr engine for high-resolution tandem mass spectrometry by developing a novel algorithm for calculating X-Corr. The algorithm enables X-Corr calculation 1.25-49 times faster than previous algorithms for 0.01 Da fragment tolerance. Furthermore, our engine is easily portable to any machine with different types of CPU because it is developed in C language. Hence, our X-Corr engine will expedite peptide identification by high-resolution tandem mass spectrometry. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | OXFORD UNIV PRESS | - |
dc.title | HiXCorr: a portable high-speed X-Corr engine for high-resolution tandem mass spectrometry | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Park, Heejin | - |
dc.contributor.affiliatedAuthor | Paek, Eunok | - |
dc.identifier.doi | 10.1093/bioinformatics/btv490 | - |
dc.identifier.scopusid | 2-s2.0-84950271001 | - |
dc.identifier.wosid | 000366630400028 | - |
dc.identifier.bibliographicCitation | BIOINFORMATICS, v.31, no.24, pp.4026 - 4028 | - |
dc.relation.isPartOf | BIOINFORMATICS | - |
dc.citation.title | BIOINFORMATICS | - |
dc.citation.volume | 31 | - |
dc.citation.number | 24 | - |
dc.citation.startPage | 4026 | - |
dc.citation.endPage | 4028 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | Y | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Biochemistry & Molecular Biology | - |
dc.relation.journalResearchArea | Biotechnology & Applied Microbiology | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Mathematical & Computational Biology | - |
dc.relation.journalResearchArea | Mathematics | - |
dc.relation.journalWebOfScienceCategory | Biochemical Research Methods | - |
dc.relation.journalWebOfScienceCategory | Biotechnology & Applied Microbiology | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Interdisciplinary Applications | - |
dc.relation.journalWebOfScienceCategory | Mathematical & Computational Biology | - |
dc.relation.journalWebOfScienceCategory | Statistics & Probability | - |
dc.subject.keywordPlus | DATABASE | - |
dc.identifier.url | http://dx.doi.org/10.1093/bioinformatics/btv490 | - |
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