title: Predicting β-turns in protein using kernel logistic regression.
abstract: A β-turn is a secondary protein structure type that plays a significant role in protein configuration and function. On average 25% of amino acids in protein structures are located in β-turns. It is very important to develope an accurate and efficient method for β-turns prediction. Most of the current successful β-turns prediction methods use support vector machines (SVMs) or neural networks (NNs). The kernel logistic regression (KLR) is a powerful classification technique that has been applied successfully in many classification problems. However, it is often not found in β-turns classification, mainly because it is computationally expensive. In this paper, we used KLR to obtain sparse β-turns prediction in short evolution time. Secondary structure information and position-specific scoring matrices (PSSMs) are utilized as input features. We achieved Q total of 80.7% and MCC of 50% on BT426 dataset. These results show that KLR method with the right algorithm can yield performance equivalent to or even better than NNs and SVMs in β-turns prediction. In addition, KLR yields probabilistic outcome and has a well-defined extension to multiclass case.
authors.affiliation: School of Information Science and Engineering, Central South University, Changsha 410083, China.
authors.forename: Murtada Khalafallah
authors.initials: MK
authors.lastname: Elbashir
authors.forename: Yu
authors.initials: Y
authors.lastname: Sheng
authors.forename: Jianxin
authors.initials: J
authors.lastname: Wang
authors.forename: Fangxiang
authors.initials: F
authors.lastname: Wu
authors.forename: Min
authors.initials: M
authors.lastname: Li
mesh_terms: D019295:Computational Biology / Q000379:methods; D030562:Databases, Protein; D016015:Logistic Models; D016571:Neural Networks, Computer; D011336:Probability; D017433:Protein Structure, Secondary; D011506:Proteins / Q000737:chemistry*; D015203:Reproducibility of Results; D012984:Software; D060388:Support Vector Machine
chemical_list: D011506:Proteins