title: Prediction of midbody, centrosome and kinetochore proteins based on gene ontology information.
abstract: In the process of cell division, a great deal of proteins is assembled into three distinct organelles, namely midbody, centrosome and kinetochore. Knowing the localization of microkit (midbody, centrosome and kinetochore) proteins will facilitate drug target discovery and provide novel insights into understanding their functions. In this study, a support vector machine (SVM) model, MicekiPred, was presented to predict the localization of microkit proteins based on gene ontology (GO) information. A total accuracy of 77.51% was achieved using the jackknife cross-validation. This result shows that the model will be an effective complementary tool for future experimental study. The prediction model and dataset used in this article can be freely downloaded from http://cobi.uestc.edu.cn/people/hlin/tools/MicekiPred/.
authors.affiliation: Department of Physics, School of Basic Medical Sciences, North China Coal Medical University, Tangshan 063000, China. chenwei_imu@yahoo.com.cn
authors.forename: Wei
authors.initials: W
authors.lastname: Chen
authors.forename: Hao
authors.initials: H
authors.lastname: Lin
mesh_terms: D001185:Artificial Intelligence; D018797:Cell Cycle Proteins / Q000737:chemistry / Q000235:genetics / Q000378:metabolism*; D002455:Cell Division / Q000235:genetics*; D018385:Centrosome; D018386:Kinetochores; D020539:Sequence Analysis, Protein / Q000379:methods*
chemical_list: D018797:Cell Cycle Proteins