'S POT.2' FS: single score feature selection applied to the problem of distinguishing long non-coding RNAs from protein coding transcripts (2018)
- Authors:
- Autor USP: CARVALHO, ANDRÉ CARLOS PONCE DE LEON FERREIRA DE - ICMC
- Unidade: ICMC
- DOI: 10.1007/978-3-030-01722-4_10
- Subjects: APRENDIZADO COMPUTACIONAL; BIOINFORMÁTICA
- Keywords: Feature selection; lncRNAs; PCTs Bioinformatics
- Language: Inglês
- Imprenta:
- Source:
- Título do periódico: Lecture Notes in Bioinformatics
- ISSN: 0302-9743
- Volume/Número/Paginação/Ano: v. 11228, p. 103-113, 2018
- Conference titles: Brazilian Symposium on Bioinformatics - BSB
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
-
ABNT
KÜMMEL, Bruno C et al. 'S POT.2' FS: single score feature selection applied to the problem of distinguishing long non-coding RNAs from protein coding transcripts. Lecture Notes in Bioinformatics. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-030-01722-4_10. Acesso em: 19 abr. 2024. , 2018 -
APA
Kümmel, B. C., Carvalho, A. C. P. de L. F. de, Brigido, M. M., Ralha, C. G., & Walter, M. E. M. T. (2018). 'S POT.2' FS: single score feature selection applied to the problem of distinguishing long non-coding RNAs from protein coding transcripts. Lecture Notes in Bioinformatics. Cham: Springer. doi:10.1007/978-3-030-01722-4_10 -
NLM
Kümmel BC, Carvalho ACP de LF de, Brigido MM, Ralha CG, Walter MEMT. 'S POT.2' FS: single score feature selection applied to the problem of distinguishing long non-coding RNAs from protein coding transcripts [Internet]. Lecture Notes in Bioinformatics. 2018 ; 11228 103-113.[citado 2024 abr. 19 ] Available from: https://doi.org/10.1007/978-3-030-01722-4_10 -
Vancouver
Kümmel BC, Carvalho ACP de LF de, Brigido MM, Ralha CG, Walter MEMT. 'S POT.2' FS: single score feature selection applied to the problem of distinguishing long non-coding RNAs from protein coding transcripts [Internet]. Lecture Notes in Bioinformatics. 2018 ; 11228 103-113.[citado 2024 abr. 19 ] Available from: https://doi.org/10.1007/978-3-030-01722-4_10 - Reduction strategies for hierarchical multi-label classification in protein function prediction
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Informações sobre o DOI: 10.1007/978-3-030-01722-4_10 (Fonte: oaDOI API)
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