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نوع الوثيقة : مقال في مجلة دورية 
عنوان الوثيقة :
iRSpot-EL: identify recombination spots with an ensemble learning approach
iRSpot-EL: identify recombination spots with an ensemble learning approach
 
لغة الوثيقة : الانجليزية 
المستخلص : 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. 
ردمد : 1367-4803 
اسم الدورية : Bioinformatics 
المجلد : 33 
العدد : 1 
سنة النشر : 1438 هـ
2017 م 
نوع المقالة : مقالة علمية 
تاريخ الاضافة على الموقع : Sunday, May 28, 2017 

الباحثون

اسم الباحث (عربي)اسم الباحث (انجليزي)نوع الباحثالمرتبة العلميةالبريد الالكتروني
Liu BinBin, Liu باحث رئيسيدكتوراه 
Wang ShanyiShanyi, Wang باحثدكتوراه 
Long RenRen, Long باحثدكتوراه 
Chou Kuo-ChenKuo-Chen, Chou باحثدكتوراه 

الملفات

اسم الملفالنوعالوصف
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