Predicts new sequence-based m6A site. TargetM6A starts by encoding each target RNA sequence into a fixed-length feature vector. It obtains an optimized feature subset by applying the incremental feature selection (IFS) algorithm to the original feature space. The tool was tested on stringent jack-knife tests and independent validation tests on benchmark datasets. The results show that it achieves high prediction performance.
School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China; Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai, China; School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China
TargetM6A funding source(s)
Supported by the National Natural Science Foundation of China (Nos. 61373062 and 61222306), the Natural Science Foundation of Jiangsu (No. BK20141403), the China Postdoctoral Science Foundation (Nos. 2014T70526 and 2013M530260), the Fundamental Research Funds for the Central Universities (No. 30916011327), the Science and Technology Commission of Shanghai Municipality (No. 16JC1404300), and "The Six Top Talents" of Jiangsu Province (No. 2013-XXRJ-022).