A novel binary k-mer approach for classification of coding and non-coding RNAs across diverse species.

Periwal, Neha; Sharma, Priya; Arora, Pooja; Pandey, Saurabh; Kaur, Baljeet; Sood, Vikas

Periwal, Neha; Sharma, Priya; Arora, Pooja; Pandey, Saurabh; Kaur, Baljeet; Sood, Vikas.

Afiliação

Periwal N; Department of Biochemistry, School of Chemical and Life Sciences, Jamia Hamdard, Delhi, 110062, India.
Sharma P; Department of Biochemistry, School of Chemical and Life Sciences, Jamia Hamdard, Delhi, 110062, India.
Arora P; Department of Zoology, Hansraj College, University of Delhi, Delhi, 110007, India.
Pandey S; Department of Biochemistry, School of Chemical and Life Sciences, Jamia Hamdard, Delhi, 110062, India.
Kaur B; Department of Computer Science, Hansraj College, University of Delhi, Delhi, 110007, India. Electronic address: baljeetkaur26@hotmail.com.
Sood V; Department of Biochemistry, School of Chemical and Life Sciences, Jamia Hamdard, Delhi, 110062, India. Electronic address: v.sood@jamiahamdard.ac.in.

Biochimie ; 199: 112-122, 2022 Aug.

Article em En | MEDLINE | ID: mdl-35476940

Assuntos

Caenorhabditis elegans; Drosophila melanogaster; Animais; Caenorhabditis elegans/genética; Drosophila melanogaster/genética; RNA não Traduzido/genética

Palavras-chave

Binary k-mer; CDS; Machine learning; k-nearest neighbour; ncRNA

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Caenorhabditis elegans / Drosophila melanogaster Tipo de estudo: Prognostic_studies Limite: Animals Idioma: En Revista: Biochimie Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Índia

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