Application of learning to rank in bioinformatics tasks.
Brief Bioinform
; 22(5)2021 09 02.
Article
em En
| MEDLINE
| ID: mdl-33454758
Over the past decades, learning to rank (LTR) algorithms have been gradually applied to bioinformatics. Such methods have shown significant advantages in multiple research tasks in this field. Therefore, it is necessary to summarize and discuss the application of these algorithms so that these algorithms are convenient and contribute to bioinformatics. In this paper, the characteristics of LTR algorithms and their strengths over other types of algorithms are analyzed based on the application of multiple perspectives in bioinformatics. Finally, the paper further discusses the shortcomings of the LTR algorithms, the methods and means to better use the algorithms and some open problems that currently exist.
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Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Algoritmos
/
Software
/
DNA
/
Proteínas
/
Drogas em Investigação
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Biologia Computacional
Limite:
Humans
Idioma:
En
Ano de publicação:
2021
Tipo de documento:
Article