Feature importance analysis of non-coding DNA/RNA sequences based on machine learning approaches (2021)
- Authors:
- Almeida, Breno Lívio Silva de
- Queiroz, Alvaro Pedroso - Universidade Tecnológica Federal do Paraná (UTFPR)
- Santos, Anderson Paulo Avila
- Bonidia, Robson Parmezan
- Rocha, Ulisses Nunes da
- Sanches, Danilo Sipoli - Universidade Tecnológica Federal do Paraná (UTFPR)
- Carvalho, André Carlos Ponce de Leon Ferreira de
- USP affiliated authors: CARVALHO, ANDRÉ CARLOS PONCE DE LEON FERREIRA DE - ICMC ; ALMEIDA, BRENO LIVIO SILVA DE - EESC E ICMC ; SANTOS, ANDERSON PAULO AVILA - ICMC ; BONIDIA, ROBSON PARMEZAN - ICMC
- Unidades: ICMC; EESC E ICMC
- DOI: 10.1007/978-3-030-91814-9_8
- Subjects: APRENDIZADO COMPUTACIONAL; BIOINFORMÁTICA
- Keywords: Small RNA; Feature extraction; Feature importance; MathFeature
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título do periódico: Lecture Notes in Bioinformatics
- ISSN: 0302-9743
- Volume/Número/Paginação/Ano: v. 13063, p. 81-92, 2021
- 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
ALMEIDA, Breno Lívio Silva de et al. Feature importance analysis of non-coding DNA/RNA sequences based on machine learning approaches. Lecture Notes in Bioinformatics. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-030-91814-9_8. Acesso em: 28 abr. 2024. , 2021 -
APA
Almeida, B. L. S. de, Queiroz, A. P., Santos, A. P. A., Bonidia, R. P., Rocha, U. N. da, Sanches, D. S., & Carvalho, A. C. P. de L. F. de. (2021). Feature importance analysis of non-coding DNA/RNA sequences based on machine learning approaches. Lecture Notes in Bioinformatics. Cham: Springer. doi:10.1007/978-3-030-91814-9_8 -
NLM
Almeida BLS de, Queiroz AP, Santos APA, Bonidia RP, Rocha UN da, Sanches DS, Carvalho ACP de LF de. Feature importance analysis of non-coding DNA/RNA sequences based on machine learning approaches [Internet]. Lecture Notes in Bioinformatics. 2021 ; 13063 81-92.[citado 2024 abr. 28 ] Available from: https://doi.org/10.1007/978-3-030-91814-9_8 -
Vancouver
Almeida BLS de, Queiroz AP, Santos APA, Bonidia RP, Rocha UN da, Sanches DS, Carvalho ACP de LF de. Feature importance analysis of non-coding DNA/RNA sequences based on machine learning approaches [Internet]. Lecture Notes in Bioinformatics. 2021 ; 13063 81-92.[citado 2024 abr. 28 ] Available from: https://doi.org/10.1007/978-3-030-91814-9_8 - BioDeepfuse: a hybrid deep learning approach with integrated feature extraction techniques for enhanced non-coding RNA classification
- BioAutoML: automated feature engineering and metalearning to predict noncoding RNAs in bacteria
- Information theory for biological sequence classification: a novel feature extraction technique based on Tsallis entropy
- MathFeature: feature extraction package for DNA, RNA and protein sequences based on mathematical
- Feature extraction approaches for biological sequences: a comparative study of mathematical features
- A novel decomposing model with evolutionary algorithms for feature selection in long non-coding RNAs
- The AnimalAssociatedMetagenomeDB reveals a bias towards livestock and developed countries and blind spots in functional-potential studies of animal-associated microbiomes
- MarineMetagenomeDB: a public repository for curated and standardized metadata for marine metagenomes
- CRISPRloci: comprehensive and accurate annotation of CRISPR-Cas systems
- BioAutoML: Democratizing Machine Learning in Life Sciences
Informações sobre o DOI: 10.1007/978-3-030-91814-9_8 (Fonte: oaDOI API)
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