title: Margin based ontology sparse vector learning algorithm and applied in biology science.
abstract: In biology field, the ontology application relates to a large amount of genetic information and chemical information of molecular structure, which makes knowledge of ontology concepts convey much information. Therefore, in mathematical notation, the dimension of vector which corresponds to the ontology concept is often very large, and thus improves the higher requirements of ontology algorithm. Under this background, we consider the designing of ontology sparse vector algorithm and application in biology. In this paper, using knowledge of marginal likelihood and marginal distribution, the optimized strategy of marginal based ontology sparse vector learning algorithm is presented. Finally, the new algorithm is applied to gene ontology and plant ontology to verify its efficiency.
authors.affiliation: School of Information Science and Technology, Yunnan Normal University, Kunming 650500, China.
authors.forename: Wei
authors.initials: W
authors.lastname: Gao
authors.affiliation: Department of Mathematics, COMSATS Institute of Information Technology, Attock, Pakistan.
authors.forename: Abdul
authors.initials: A
authors.lastname: Qudair Baig
authors.affiliation: Department of Mathematics, COMSATS Institute of Information Technology, Attock, Pakistan.
authors.forename: Haidar
authors.initials: H
authors.lastname: Ali
authors.affiliation: Department of Mathematics, COMSATS Institute of Information Technology, Attock, Pakistan.
authors.forename: Wasim
authors.initials: W
authors.lastname: Sajjad
authors.affiliation: Department of Applied Mathematics, Iran University of Science and Technology, Narmak, 16844 Tehran, Iran.
authors.forename: Mohammad
authors.initials: M
authors.lastname: Reza Farahani
keywords: Margin; Ontology; Similarity measure; Sparse vector