title: Constraint programming based biomarker optimization.
abstract: Efficient and intuitive characterization of biological big data is becoming a major challenge for modern bio-OMIC based scientists. Interactive visualization and exploration of big data is proven to be one of the successful solutions. Most of the existing feature selection algorithms do not allow the interactive inputs from users in the optimizing process of feature selection. This study investigates this question as fixing a few user-input features in the finally selected feature subset and formulates these user-input features as constraints for a programming model. The proposed algorithm, fsCoP (feature selection based on constrained programming), performs well similar to or much better than the existing feature selection algorithms, even with the constraints from both literature and the existing algorithms. An fsCoP biomarker may be intriguing for further wet lab validation, since it satisfies both the classification optimization function and the biomedical knowledge. fsCoP may also be used for the interactive exploration of bio-OMIC big data by interactively adding user-defined constraints for modeling.
authors.affiliation: Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong 518055, China ; Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences, Beijing 100049, China.
authors.forename: Manli
authors.identifier: 0000-0002-3071-187X
authors.initials: M
authors.lastname: Zhou
authors.affiliation: Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong 518055, China ; School of Science, Hubei University of Technology, Wuhan, Hubei 430068, China.
authors.forename: Youxi
authors.identifier: 0000-0001-6926-9663
authors.initials: Y
authors.lastname: Luo
authors.affiliation: Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong 518055, China.
authors.forename: Guoquan
authors.initials: G
authors.lastname: Sun
authors.affiliation: Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong 518055, China.
authors.forename: Guoqin
authors.initials: G
authors.lastname: Mai
authors.affiliation: Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong 518055, China.
authors.forename: Fengfeng
authors.identifier: 0000-0002-8108-6007
authors.initials: F
authors.lastname: Zhou
mesh_terms: D000465:Algorithms; D015415:Biomarkers; D006801:Humans; D008957:Models, Genetic; D011381:Programming Languages
chemical_list: D015415:Biomarkers