Santana Roberto, Larrañaga Pedro, Lozano Jose A
Department of Computer Science and Artificial Intelligence, University of the Basque Country, CP-20080, Donostia-San Sebastián, Spain.
Artif Intell Med. 2007 Jan;39(1):49-63. doi: 10.1016/j.artmed.2006.04.004. Epub 2006 Jul 18.
This paper presents an algorithm for the solution of the side chain placement problem.
The algorithm combines the application of the Goldstein elimination criterion with the univariate marginal distribution algorithm (UMDA), which stochastically searches the space of possible solutions. The suitability of the algorithm to address the problem is investigated using a set of 425 proteins.
For a number of difficult instances where inference algorithms do not converge, it has been shown that UMDA is able to find better structures.
The results obtained show that the algorithm can achieve better structures than those obtained with other state-of-the-art methods like inference-based techniques. Additionally, a theoretical and empirical analysis of the computational cost of the algorithm introduced has been presented.
本文提出一种用于解决侧链放置问题的算法。
该算法将戈尔茨坦消除准则的应用与单变量边际分布算法（UMDA）相结合，UMDA随机搜索可能解的空间。使用一组425种蛋白质研究该算法解决此问题的适用性。
对于一些推理算法无法收敛的困难实例，已表明UMDA能够找到更好的结构。
所得结果表明，该算法能比基于推理技术等其他现有先进方法获得更好的结构。此外，还对所引入算法的计算成本进行了理论和实证分析。
