A sequence-based predictor for identifying translation initiation site in human genes using pseudo trinucleotide composition. It was observed by the rigorous cross-validation test on the benchmark dataset that the overall success rate achieved by the new predictor in identifying translation initiation site (TIS) locations was over 97%.
Department of Physics, School of Sciences, Center for Genomics and Computational Biology, Hebei United University, Tangshan, China; Gordon Life Science Institute, Boston, MA, USA; School of Public Health, Hebei United University, Tangshan, China; Key Laboratory for Neuro-Information of Ministry of Education, Center of Bioinformatics, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China; Center of Excellence in Genomic Medicine Research (CEGMR), King Abdulaziz University, Jeddah, Saudi Arabia
iTIS-PseTNC funding source(s)
This work was supported by the National Nature Scientific Foundation of China (Nos. 61100092 and 61202256), the Nature Scientific Foundation of Hebei Province (No. C2013209105), and Science and Technology Department of Hebei Province (No. 132777133).