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Application of learning to rank in bioinformatics tasks.

Authors :
Ru, Xiaoqing
Ye, Xiucai
Sakurai, Tetsuya
Zou, Quan
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

Subjects :
BIOINFORMATICS
TASKS
ALGORITHMS

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