期刊论文

Yu, Bin

英文

Artificial Intelligence in Medicine

0933-3657

2019

98

Jul.

35-47

10.1016/j.artmed.2019.07.005

The authors sincerely thank the anonymous reviewers for their many valuable comments that have improved this manuscript. This work was supported by the National Natural Science Foundation of China (Nos. 61863010 and 11771188 ), the Key Research and Development Program of Shandong Province of China ( 2019GGX101001 ), the Natural Science Foundation of Shandong Province of China (No. ZR2018MC007 ), the Project of Shandong Province Higher Educational Science and Technology Program (No. J17KA159 ), the Scientific Research Fund of Hunan Provincial Key Laboratory of Mathematical Modeling and Analysis in Engineering (No. 2018MMAEZD10 ), the Key Laboratory Open Foundation of Shandong Province , the College Students’ Innovative Practice Training Program of Chinese Academy of Sciences , and the College Students’ Innovative Entrepreneurial Training Program (No. 201710426046 ).

本校为其他机构

Discovering and accurately locating drug targets is of great significance for the research and development of new drugs. As a different approach to traditional drug development, the machine learning algorithm is used to predict the drug target by mining the data. Because of its advantages of short time and low cost, it has received more and more attention in recent years. In this paper, we propose a novel method for predicting druggable proteins. Firstly, the features of the protein sequence are extracted by combining Chou's pseudo amino acid c...