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Application of learning to rank in bioinformatics tasks.
- Source :
- Briefings in Bioinformatics; Sep2021, Vol. 22 Issue 5, p1-11, 11p
- Publication Year :
- 2021
-
Abstract
- 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. [ABSTRACT FROM AUTHOR]
- Subjects :
- BIOINFORMATICS
TASKS
ALGORITHMS
Subjects
Details
- Language :
- English
- ISSN :
- 14675463
- Volume :
- 22
- Issue :
- 5
- Database :
- Complementary Index
- Journal :
- Briefings in Bioinformatics
- Publication Type :
- Academic Journal
- Accession number :
- 152975131
- Full Text :
- https://doi.org/10.1093/bib/bbaa394