Comparative Analysis of Different Evaluation Functions for Protein Structure Prediction Under the HP Model

作     者：Mario Garza-Fabre Eduardo Rodriguez-Tello Gregorio Toscano-Pulido 

作者机构：Information Technology Laboratory CINVESTAV-Tamaulipas Km.5.5 Carretera Ciudad Victoria-Soto La Marina 87130 Ciudad Victoria Tamaulipas México 

出 版 物：《Journal of Computer Science & Technology》 (计算机科学技术学报（英文版）)

年 卷 期：2013年第28卷第5期

页      面：868-889页

核心收录：

学科分类：0710[理学-生物学] 071010[理学-生物化学与分子生物学] 081704[工学-应用化学] 07[理学] 08[工学] 0817[工学-化学工程与技术] 0835[工学-软件工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：partially supported by the National Council of Science and Technology of México (CO NACyT) under Grant Nos. 105060 and 99276 

主　　题：evaluation function protein structure prediction metaheuristics combinatorial optimization bioinformatics 

摘      要：The HP model for protein structure prediction abstracts the fact that hydrophobicity is a dominant force in the protein folding process. This challenging combinatorial optimization problem has been widely addressed through metaheuristics. The evaluation function is a key component for the success of metaheuristics; the poor discrimination of the conventional evaluation function of the HP model has motivated the proposal of alternative formulations for this component. This comparative analysis inquires into the effectiveness of seven different evaluation functions for the HP model. The degree of discrimination provided by each of the studied functions, their capability to preserve a rank ordering among potential solutions which is consistent with the original objective of the HP model, as well as their effect on the performance of local search methods are analyzed. The obtained results indicate that studying alternative evaluation schemes for the HP model represents a highly valuable direction which merits more attention.