Matches in SemOpenAlex for { <https://semopenalex.org/work/W2020250138> ?p ?o ?g. }
Showing items 1 to 86 of
86
with 100 items per page.
- W2020250138 abstract "Identification of organisms using their genetic sequences is a popular problem in molecular biology and is used in fields such as metagenomics, molecular phylogenetics and DNA Barcoding. These applications depend on searching large sequence databases for individual matching sequences (e.g., with BLAST) and comparing sequences using multiple sequence alignment (e.g., via Clustal), both of which are computationally expensive and require extensive server resources. We propose a novel method for sequence comparison, analysis, and classification which avoids the need to align sequences at the base level or search a database for similarity. Instead, our method uses alignment-free methods to find probabilistic quasi-alignments for longer (typically 100 base pairs) segments. Clustering is then used to create compact models that can be used to analyze a set of sequences and to score and classify unknown sequences against these models. In this paper we expand prior work in two ways. We show how quasi-alignments can be expanded into larger quasi-aligned sections and we develop a method to classify short sequence fragments. The latter is especially useful when working with Next-Generation Sequencing (NGS) techniques that generate output in the form of relatively short reads. We have conducted extensive experiments using fragments from bacterial 16S rRNA sequences obtained from the Greengenes project and our results show that the new quasi-alignment based approach can provide excellent results as well as overcome some of the restrictions of by the widely used Ribosomal Database Project (RDP) classifier." @default.
- W2020250138 created "2016-06-24" @default.
- W2020250138 creator A5027377977 @default.
- W2020250138 creator A5086729558 @default.
- W2020250138 date "2013-09-22" @default.
- W2020250138 modified "2023-10-16" @default.
- W2020250138 title "Genomic Sequence Fragment Identification using Quasi-Alignment" @default.
- W2020250138 cites W1556991626 @default.
- W2020250138 cites W1999731909 @default.
- W2020250138 cites W2043481183 @default.
- W2020250138 cites W2098386120 @default.
- W2020250138 cites W2099901798 @default.
- W2020250138 cites W2100539938 @default.
- W2020250138 cites W2106882534 @default.
- W2020250138 cites W2111775329 @default.
- W2020250138 cites W2161536174 @default.
- W2020250138 cites W2171963266 @default.
- W2020250138 cites W2320723632 @default.
- W2020250138 cites W4233192208 @default.
- W2020250138 doi "https://doi.org/10.1145/2506583.2506647" @default.
- W2020250138 hasPublicationYear "2013" @default.
- W2020250138 type Work @default.
- W2020250138 sameAs 2020250138 @default.
- W2020250138 citedByCount "0" @default.
- W2020250138 crossrefType "proceedings-article" @default.
- W2020250138 hasAuthorship W2020250138A5027377977 @default.
- W2020250138 hasAuthorship W2020250138A5086729558 @default.
- W2020250138 hasConcept C104317684 @default.
- W2020250138 hasConcept C116834253 @default.
- W2020250138 hasConcept C124101348 @default.
- W2020250138 hasConcept C15151743 @default.
- W2020250138 hasConcept C154945302 @default.
- W2020250138 hasConcept C167625842 @default.
- W2020250138 hasConcept C180384323 @default.
- W2020250138 hasConcept C2778112365 @default.
- W2020250138 hasConcept C41008148 @default.
- W2020250138 hasConcept C45484198 @default.
- W2020250138 hasConcept C49937458 @default.
- W2020250138 hasConcept C51679486 @default.
- W2020250138 hasConcept C54355233 @default.
- W2020250138 hasConcept C552990157 @default.
- W2020250138 hasConcept C59822182 @default.
- W2020250138 hasConcept C70721500 @default.
- W2020250138 hasConcept C72802188 @default.
- W2020250138 hasConcept C73555534 @default.
- W2020250138 hasConcept C86803240 @default.
- W2020250138 hasConcept C88031987 @default.
- W2020250138 hasConcept C95623464 @default.
- W2020250138 hasConceptScore W2020250138C104317684 @default.
- W2020250138 hasConceptScore W2020250138C116834253 @default.
- W2020250138 hasConceptScore W2020250138C124101348 @default.
- W2020250138 hasConceptScore W2020250138C15151743 @default.
- W2020250138 hasConceptScore W2020250138C154945302 @default.
- W2020250138 hasConceptScore W2020250138C167625842 @default.
- W2020250138 hasConceptScore W2020250138C180384323 @default.
- W2020250138 hasConceptScore W2020250138C2778112365 @default.
- W2020250138 hasConceptScore W2020250138C41008148 @default.
- W2020250138 hasConceptScore W2020250138C45484198 @default.
- W2020250138 hasConceptScore W2020250138C49937458 @default.
- W2020250138 hasConceptScore W2020250138C51679486 @default.
- W2020250138 hasConceptScore W2020250138C54355233 @default.
- W2020250138 hasConceptScore W2020250138C552990157 @default.
- W2020250138 hasConceptScore W2020250138C59822182 @default.
- W2020250138 hasConceptScore W2020250138C70721500 @default.
- W2020250138 hasConceptScore W2020250138C72802188 @default.
- W2020250138 hasConceptScore W2020250138C73555534 @default.
- W2020250138 hasConceptScore W2020250138C86803240 @default.
- W2020250138 hasConceptScore W2020250138C88031987 @default.
- W2020250138 hasConceptScore W2020250138C95623464 @default.
- W2020250138 hasLocation W20202501381 @default.
- W2020250138 hasOpenAccess W2020250138 @default.
- W2020250138 hasPrimaryLocation W20202501381 @default.
- W2020250138 hasRelatedWork W2012129103 @default.
- W2020250138 hasRelatedWork W2051319991 @default.
- W2020250138 hasRelatedWork W2095439426 @default.
- W2020250138 hasRelatedWork W2105862765 @default.
- W2020250138 hasRelatedWork W2130740364 @default.
- W2020250138 hasRelatedWork W2350395044 @default.
- W2020250138 hasRelatedWork W2389094034 @default.
- W2020250138 hasRelatedWork W2596471045 @default.
- W2020250138 hasRelatedWork W3210186669 @default.
- W2020250138 hasRelatedWork W88386512 @default.
- W2020250138 isParatext "false" @default.
- W2020250138 isRetracted "false" @default.
- W2020250138 magId "2020250138" @default.
- W2020250138 workType "article" @default.