Micale Giovanni, Pulvirenti Alfredo, Giugno Rosalba, Ferro Alfredo
Department of Computer Science, University of Pisa, Pisa, Italy.
Department of Clinical and Molecular Biomedicine, University of Catania, Catania, Italy.
PLoS One. 2014 Jun 9;9(6):e98750. doi: 10.1371/journal.pone.0098750. eCollection 2014.
The analysis of structure and dynamics of biological networks plays a central role in understanding the intrinsic complexity of biological systems. Biological networks have been considered a suitable formalism to extend evolutionary and comparative biology. In this paper we present GASOLINE, an algorithm for multiple local network alignment based on statistical iterative sampling in connection to a greedy strategy. GASOLINE overcomes the limits of current approaches by producing biologically significant alignments within a feasible running time, even for very large input instances. The method has been extensively tested on a database of real and synthetic biological networks. A comprehensive comparison with state-of-the art algorithms clearly shows that GASOLINE yields the best results in terms of both reliability of alignments and running time on real biological networks and results comparable in terms of quality of alignments on synthetic networks. GASOLINE has been developed in Java, and is available, along with all the computed alignments, at the following URL: http://ferrolab.dmi.unict.it/gasoline/gasoline.html.
生物网络的结构与动力学分析在理解生物系统的内在复杂性方面起着核心作用。生物网络被认为是扩展进化生物学和比较生物学的一种合适形式。在本文中，我们介绍了GASOLINE，这是一种基于统计迭代采样并结合贪心策略的多重局部网络比对算法。GASOLINE克服了当前方法的局限性，即使对于非常大的输入实例，也能在可行的运行时间内产生具有生物学意义的比对。该方法已在真实和合成生物网络数据库上进行了广泛测试。与现有算法的全面比较清楚地表明，GASOLINE在真实生物网络上的比对可靠性和运行时间方面都产生了最佳结果，在合成网络上的比对质量方面也产生了可比的结果。GASOLINE是用Java开发的，可通过以下网址获取，同时还提供所有计算出的比对结果：http://ferrolab.dmi.unict.it/gasoline/gasoline.html。
