title: Inferring Association between Compound and Pathway with an Improved Ensemble Learning Method.
abstract: Emergence of compound molecular data coupled to pathway information offers the possibility of using machine learning methods for compound-pathway associations' inference. To provide insights into the global relationship between compounds and their affected pathways, a improved Rotation Forest ensemble learning method called RGRF (Relief & GBSSL - Rotation Forest) was proposed to predict their potential associations. The main characteristic of the RGRF lies in using the Relief algorithm for feature extraction and regarding the Graph-Based Semi-Supervised Learning method as classifier. By incorporating the chemical structure information, drug mode of action information and genomic space information, our method can achieve a better precision and flexibility on compound-pathway prediction. Moreover, several new compound-pathway associations that having the potential for further clinical investigation have been identified by database searching. In the end, a prediction tool was developed using RGRF algorithm, which can predict the interactions between pathways and all of the compounds in cMap database.
authors.affiliation: Shanghai Key Laboratory of Multidimensional Information Processing, East China Normal University, Shanghai 200241, China.|Department of Computer Science and Technology, East China Normal University, Shanghai 200241, China.
authors.forename: Meiyue
authors.initials: M
authors.lastname: Song
authors.affiliation: East China Normal University, Dept. of Computer Science & Technology, 500 Dong Chuan Road, Shanghai 200241, China;, Tel: +86-21-54345188;. zrjiang@cs.ecnu.edu.cn.|Shanghai Key Laboratory of Multidimensional Information Processing, East China Normal University, Shanghai 200241, China. zrjiang@cs.ecnu.edu.cn.|Department of Computer Science and Technology, East China Normal University, Shanghai 200241, China. zrjiang@cs.ecnu.edu.cn.
authors.forename: Zhenran
authors.initials: Z
authors.lastname: Jiang
mesh_terms: D000465:Algorithms; D000970:Antineoplastic Agents / Q000737:chemistry / Q000493:pharmacokinetics / Q000494:pharmacology; D030541:Databases, Genetic; D055808:Drug Discovery / Q000379:methods*; D006801:Humans; D061986:MCF-7 Cells; D015394:Molecular Structure; D020411:Oligonucleotide Array Sequence Analysis
chemical_list: D000970:Antineoplastic Agents
keywords: Compound-pathway interaction; Ensemble Learning; RGRF method; Rotation forest