Organizers:
Fuxi Zhu
Software Engineering Department, Wuhan College, Wuhan, China
Email: fxzhu@whu.edu.com.cn

Lida Zhu
Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan, China
Email: fxzhu@whu.edu.com.cn
Scope:
Review Reports and Decision on "Predicting potential Drug-Target Interactions with Multilabel learning and ensemble learning" In recent years, there have been many studies in machine-learning models for DTIs prediction. In practical application, it can not completely replace the traditional methods. 1 In this paper, by using the machine-learning models for DTIs prediction, provide a novel tool for identifying drug targets and make a step closer to applications. 2 The proposed MLKNN and the ensemble method are promising tools for predicting DTIs. Decision Paper ID: 601 Paper Title: Predicting potential Drug-Target Interactions with Multi-label learning and ensemble learning This paper can be accepted and published in conference papers for reference by researchers in related fields.