EDLMFC: an ensemble deep learning framework with multi-scale features combination for ncRNA-protein interaction prediction.

Journal: BMC bioinformatics
Published Date: Mar 19, 2021

Abstract

BACKGROUND: Non-coding RNA (ncRNA) and protein interactions play essential roles in various physiological and pathological processes. The experimental methods used for predicting ncRNA-protein interactions are time-consuming and labor-intensive. Therefore, there is an increasing demand for computational methods to accurately and efficiently predict ncRNA-protein interactions.

Authors

  • Jingjing Wang
    Department of Radiology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong Province, China; School of Medicine, South China University of Technology, Guangzhou, Guangdong Province, China.
  • Yanpeng Zhao
    b Department of Orthopaedics , Chinese PLA General Hospital , Beijing , China.
  • Weikang Gong
    College of Life Science and Bioengineering, Beijing University of Technology, Intelligent Physiological Measurement and Clinical Translation, Beijing International Base for Scientific and Technological Cooperation, Beijing, 100124, China.
  • Yang Liu
    Department of Computer Science, Hong Kong Baptist University, Hong Kong, China.
  • Mei Wang
    Natural Products Utilization Research Unit, Agricultural Research Service, U.S. Department of Agriculture, Oxford, MS, 38677, USA.
  • Xiaoqian Huang
    Department of Biomedical Engineering, Faculty of Environment and Life, Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, Beijing University of Technology, Beijing, 100124, China.
  • Jianjun Tan
    College of Life Science and Bio-engineering, Beijing University of Technology, Beijing, 100124, China. Electronic address: tanjianjun@bjut.edu.cn.

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