Prediction and Identification of Krüppel-Like Transcription Factors by Machine Learning Method.

Journal: Combinatorial chemistry & high throughput screening
Published Date: Jan 1, 2017

Abstract

AIM AND OBJECTIVE: The Krüppel-like factors (KLFs) are a family of containing Zn finger(ZF) motif transcription factors with 18 members in human genome, among them, KLF18 is predicted by bioinformatics. KLFs possess various physiological function involving in a number of cancers and other diseases. Here we perform a binary-class classification of KLFs and non-KLFs by machine learning methods.

Authors

  • Zhijun Liao
    Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, Fujian 350122, China.
  • Xinrui Wang
    State Key Laboratory for Medical Genomics, Shanghai Institute of Hematology, Rui-Jin Hospital affiliated to School of Medicine, Shanghai Jiao Tong University, Shanghai 200025, China.
  • Xingyong Chen
    Department of Neurology, Fujian Provincial Hospital, Fujian Medical University Shengli Clinical College, Fuzhou. China.
  • Quan Zou

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