VPrimer: A method of designing and updating primer and probe with high variant coverage for RNA virus detection
DC Field | Value | Language |
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dc.contributor.author | Jeon, Hajin | - |
dc.contributor.author | Bae, Jeongmin | - |
dc.contributor.author | Kim, Hyerin | - |
dc.contributor.author | Kim, Min-Soo | - |
dc.date.accessioned | 2023-08-16T09:28:58Z | - |
dc.date.available | 2023-08-16T09:28:58Z | - |
dc.date.created | 2022-01-11 | - |
dc.date.issued | 2023-01 | - |
dc.identifier.issn | 1545-5963 | - |
dc.identifier.uri | http://scholarworks.bwise.kr/kbri/handle/2023.sw.kbri/169 | - |
dc.description.abstract | Fatal infectious diseases caused by RNA viruses, such as COVID-19, have emerged around the world. RT-PCR is widely employed for virus detection, and its accuracy depends on the primers and probes since RT-PCR can detect a virus only when the primers and probes bind to the target gene of the virus. Most of primer design methods are for a single host and so require a great deal of effort to design for RNA virus detection, including homology tests among the host and all the viruses for the host using BLAST-like tools. Furthermore, they do not consider variant sequences, which are very common in viruses. In this study, we describe VPrimer, a method of designing high-quality primer-probe sets for RNA viruses. VPrimer can find primer-probe sets that cover more than 95% of the variants of a target virus but do not cover any sequences of other viruses or the host. With VPrimer, we found 381,698,582 primer-probe sets for 3,104 RNA viruses. Multiplex PCR assays using the top 2 primer-probe sets suggested by VPrimer usually cover 100% of variants. To address the rapid changes in viral genomes, VPrimer finds the best and up-to-date primer-probe sets incrementally against the most recently reported variants. | - |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | - |
dc.title | VPrimer: A method of designing and updating primer and probe with high variant coverage for RNA virus detection | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Kim, Hyerin | - |
dc.identifier.doi | 10.1109/TCBB.2021.3138145 | - |
dc.identifier.scopusid | 2-s2.0-85122108010 | - |
dc.identifier.wosid | 001013148200039 | - |
dc.identifier.bibliographicCitation | IEEE/ACM Transactions on Computational Biology and Bioinformatics, v.20, no.1, pp.775 - 784 | - |
dc.relation.isPartOf | IEEE/ACM Transactions on Computational Biology and Bioinformatics | - |
dc.citation.title | IEEE/ACM Transactions on Computational Biology and Bioinformatics | - |
dc.citation.volume | 20 | - |
dc.citation.number | 1 | - |
dc.citation.startPage | 775 | - |
dc.citation.endPage | 784 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Biochemistry & Molecular Biology | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Mathematics | - |
dc.relation.journalWebOfScienceCategory | Biochemical Research Methods | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Interdisciplinary Applications | - |
dc.relation.journalWebOfScienceCategory | Mathematics, Interdisciplinary Applications | - |
dc.relation.journalWebOfScienceCategory | Statistics & Probability | - |
dc.subject.keywordPlus | MULTIPLE SEQUENCE ALIGNMENT | - |
dc.subject.keywordPlus | SENSITIVITY | - |
dc.subject.keywordPlus | PCR | - |
dc.subject.keywordAuthor | Algorithm design and analysis | - |
dc.subject.keywordAuthor | bioinformatics | - |
dc.subject.keywordAuthor | database | - |
dc.subject.keywordAuthor | genomics | - |
dc.subject.keywordAuthor | molecular biology | - |
dc.subject.keywordAuthor | polymerase chain reaction (PCR) | - |
dc.subject.keywordAuthor | primer design | - |
dc.subject.keywordAuthor | probe | - |
dc.subject.keywordAuthor | server | - |
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