模拟退火算法在生物网络研究中的应用

Application of simulated annealing algorithm to biological networks research

生物网络的功能模块识别是当前生物信息学和系统生物研究领域的一个重要研究主题。首先介绍了模拟退火算法的基本原理,分析了聚集系数和模块性等与生物网络功能模块识别相关的一些基本概念,随后阐述了模拟退火算法在生物网络功能模块识别方面的应用。最后,通过新陈代谢网络和蛋白交互网络这2种具体生物网络的模块划分实例,证实了模拟退火算法在生物网络功能模块研究方面的高效性。

Identification of functional modules in biological networks is one of the most important topics in current bioinformatics and systems biology. After the introduction of the basic for simulated annealing algorithm （SAA）, we analyze some basic concepts about identification of functional modules in biological networks, e.g., clustering coefficient, modularity, and then expatiate the application of simulated annealing algorithm to identification of functional modules in biological networks. At last, by the example from two kinds of biological networks, we affirm the high efficient of simulated annealing algorithm in identification of fimctional modules in biological networks.