iTerm-PseKNC: a sequence-based tool for predicting bacterial transcriptional terminators

Author:

Feng Chao-Qin1,Zhang Zhao-Yue1,Zhu Xiao-Juan1,Lin Yan2,Chen Wei13,Tang Hua4,Lin Hao1

Affiliation:

1. Key Laboratory for Neuro-Information of Ministry of Education, School of Life Science and Technology, Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu, China

2. Key Laboratory for Animal Disease Resistance Nutrition of the Ministry of Education, Animal Nutrition Institute, Sichuan Agricultural University, Chengdu, China

3. Center for Genomics and Computational Biology, School of Life Sciences, North China University of Science and Technology, Tangshan, China

4. Department of Pathophysiology, Southwest Medical University, Luzhou, China

Funder

National Nature Scientific Foundation of China

Fundamental Research Funds for the Central Universities of China

Natural Science Foundation for Distinguished Young Scholar of Hebei Province

Program for the Top Young Innovative Talents of Higher Learning Institutions of Hebei Province

Science Strength Promotion Programme of UESTC

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

Reference80 articles.

1. Fitting a mixture model by expectation maximization to discover motifs in biopolymers;Bailey;Proc. Int. Conf. Intell. Syst. Mol. Biol,1994

2. Terminators of transcription with RNA polymerase from Escherichia coli: what they look like and how to find them;Brendel;J. Biomol. Struct. Dyn,1986

3. A computer algorithm for testing potential prokaryotic terminators;Brendel;Nucleic Acids Res,1984

4. Sequence-dependent bending propensity of DNA as revealed by DNase I: parameters for trinucleotides;Brukner;EMBO J,1995

5. A tutorial on support vector machines for pattern recognition;Burges;Data Min. Knowl. Discov,1998

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