14-12-2025
جامعة الملك عبدالعزيز
KING ABDULAZIZ UNIVERSITY
Center of Excellence In Genomic Medicine Research
Document Details
Document Type
:
Article In Journal
Document Title
:
iRSpot-EL: identify recombination spots with an ensemble learning approach
iRSpot-EL: identify recombination spots with an ensemble learning approach
Document Language
:
English
Abstract
:
Motivation: Coexisting in a DNA system, meiosis and recombination are two indispensible aspects for cell reproduction and growth. With the avalanche of genome sequences emerging in the postgenomic age, it is an urgent challenge to acquire the information of DNA recombination spots because it can timely provide very useful insights into the mechanism of meiotic recombination and the process of genome evolution. Results: To address such a challenge, we have developed a predictor, called iRSpot-EL, by fusing different modes of pseudo K-tuple nucleotide composition and mode of dinucleotide-based autocross covariance into an ensemble classifier of clustering approach. Five-fold cross tests on a widely used benchmark dataset have indicated that the new predictor remarkably outperforms its existing counterparts. Particularly, far beyond their reach, the new predictor can be easily used to conduct the genome-wide analysis and the results obtained are quite consistent with the experimental map. Availability and Implementation: For the convenience of most experimental scientists, a userfriendly web-server for iRSpot-EL has been established at http://bioinformatics.hitsz.edu.cn/iRSpot- EL/, by which users can easily obtain their desired results without the need to go through the complicated mathematical equations involved.
ISSN
:
1367-4803
Journal Name
:
Bioinformatics
Volume
:
33
Issue Number
:
1
Publishing Year
:
1438 AH
2017 AD
Article Type
:
Article
Added Date
:
Sunday, May 28, 2017
Researchers
Researcher Name (Arabic)
Researcher Name (English)
Researcher Type
Dr Grade
Email
Liu Bin
Bin, Liu
Investigator
Doctorate
Wang Shanyi
Shanyi, Wang
Researcher
Doctorate
Long Ren
Ren, Long
Researcher
Doctorate
Chou Kuo-Chen
Kuo-Chen, Chou
Researcher
Doctorate
Files
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Type
Description
40793.pdf
pdf
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