Feature extraction approaches for biological sequences: A comparative study of mathematical features

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Autor(es): dc.contributorUniversidade de São Paulo (USP)-
Autor(es): dc.contributorThe Federal University of Technology - Paraná (UTFPR)-
Autor(es): dc.contributorUniversidade Estadual de Londrina (UEL)-
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorUniversidade Federal do Paraná (UFPR)-
Autor(es): dc.creatorBonidia, Robson P.-
Autor(es): dc.creatorSampaio, Lucas D.H.-
Autor(es): dc.creatorDomingues, Douglas S.-
Autor(es): dc.creatorPaschoal, Alexandre R.-
Autor(es): dc.creatorLopes, Fabrício M.-
Autor(es): dc.creatorde Carvalho, André C.P.L.F.-
Autor(es): dc.creatorSanches, Danilo S.-
Data de aceite: dc.date.accessioned2025-08-21T18:24:08Z-
Data de disponibilização: dc.date.available2025-08-21T18:24:08Z-
Data de envio: dc.date.issued2022-04-28-
Data de envio: dc.date.issued2022-04-28-
Data de envio: dc.date.issued2020-12-31-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1093/bib/bbab011-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/222520-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/222520-
Descrição: dc.descriptionAs consequence of the various genomic sequencing projects, an increasing volume of biological sequence data is being produced. Although machine learning algorithms have been successfully applied to a large number of genomic sequence-related problems, the results are largely affected by the type and number of features extracted. This effect has motivated new algorithms and pipeline proposals, mainly involving feature extraction problems, in which extracting significant discriminatory information from a biological set is challenging. Considering this, our work proposes a new study of feature extraction approaches based on mathematical features (numerical mapping with Fourier, entropy and complex networks). As a case study, we analyze long non-coding RNA sequences. Moreover, we separated this work into three studies. First, we assessed our proposal with the most addressed problem in our review, e.g. lncRNA and mRNA; second, we also validate the mathematical features in different classification problems, to predict the class of lncRNA, e.g. circular RNAs sequences; third, we analyze its robustness in scenarios with imbalanced data. The experimental results demonstrated three main contributions: first, an in-depth study of several mathematical features; second, a new feature extraction pipeline; and third, its high performance and robustness for distinct RNA sequence classification.-
Descrição: dc.descriptionUniversidade Federal do Paraná-
Descrição: dc.descriptionPró-Reitoria de Pesquisa, Universidade Federal do Rio Grande do Sul-
Descrição: dc.descriptionCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)-
Descrição: dc.descriptionInstitute of Mathematics and Computer Sciences University of São Paulo - USP-
Descrição: dc.descriptionThe Federal University of Technology - Paraná (UTFPR)-
Descrição: dc.descriptionThe State University of Londrina-
Descrição: dc.descriptionPolytechnic School The University of São Paulo-
Descrição: dc.descriptionThe São Paulo State University-
Descrição: dc.descriptionThe University of São Paulo-
Descrição: dc.descriptionThe Federal University of Paraná (UFPR)-
Descrição: dc.descriptionThe University of São Paulo (USP)-
Descrição: dc.descriptionThe Department of Computer Science University of São Paulo-
Descrição: dc.descriptionThe São Paulo State University-
Descrição: dc.descriptionPró-Reitoria de Pesquisa, Universidade Federal do Rio Grande do Sul: 88887.144045/2017-00-
Descrição: dc.descriptionCAPES: PROEX-11919694/D-
Idioma: dc.languageen-
Relação: dc.relationBriefings in Bioinformatics-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectBiological sequences-
Palavras-chave: dc.subjectComplex networks-
Palavras-chave: dc.subjectEntropy-
Palavras-chave: dc.subjectFeature extraction-
Palavras-chave: dc.subjectFourier-
Palavras-chave: dc.subjectNumerical mapping-
Título: dc.titleFeature extraction approaches for biological sequences: A comparative study of mathematical features-
Tipo de arquivo: dc.typevídeo-
Aparece nas coleções:Repositório Institucional - Unesp

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