LMTRDA: Using logistic model tree to predict MiRNA-disease associations by fusing multi-source information of sequences and similarities

• Lei Wang ,

  Roles Methodology, Writing – original draft

  ¶‡ These authors share first authorship on this work.

  Affiliation Xinjiang Technical Institute of Physics and Chemistry, Chinese Academy of Science, Urumqi, China

  ⨯
• Zhu-Hong You ,

  Roles Data curation, Methodology, Writing – review & editing

  * E-mail: zhuhongyou@ms.xjb.ac.cn (ZHY); xingchen@amss.ac.cn (XC)

  ¶‡ These authors share first authorship on this work.

  Affiliation Xinjiang Technical Institute of Physics and Chemistry, Chinese Academy of Science, Urumqi, China

  http://orcid.org/0000-0003-1266-2696

  ⨯
• Xing Chen ,

  Roles Methodology

  * E-mail: zhuhongyou@ms.xjb.ac.cn (ZHY); xingchen@amss.ac.cn (XC)

  Affiliation School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, China

  http://orcid.org/0000-0001-9028-5342

  ⨯
• Yang-Ming Li,

  Roles Data curation, Formal analysis

  Affiliation Department of Electrical Computer and Telecommunications Engineering Technology, Rochester Institute of Technology, Rochester, United States of America

  ⨯
• Ya-Nan Dong,

  Roles Methodology

  Affiliation Xiangya School of Public Health, Central South University, Changsha, China

  ⨯
• Li-Ping Li,

  Roles Conceptualization, Writing – original draft

  Affiliation Xinjiang Technical Institute of Physics and Chemistry, Chinese Academy of Science, Urumqi, China

  ⨯
• Kai Zheng

  Roles Methodology, Writing – review & editing

  Affiliation Xinjiang Technical Institute of Physics and Chemistry, Chinese Academy of Science, Urumqi, China

  ⨯