IEEE/ACM Trans Comput Biol Bioinform. 2018 Jan-Feb;15(1):330-336. doi: 10.1109/TCBB.2016.2613098. Epub 2016 Sep 26.
Network Alignment over graph-structured data has received considerable attention in many recent applications. Global network alignment tries to uniquely find the best mapping for a node in one network to only one node in another network. The mapping is performed according to some matching criteria that depend on the nature of data. In molecular biology, functional orthologs, protein complexes, and evolutionary conserved pathways are some examples of information uncovered by global network alignment. Current techniques for global network alignment suffer from several drawbacks, e.g., poor performance and high memory requirements. We address these problems by proposing IBNAL, Indexes-Based Network ALigner, for better alignment quality and faster results. To accelerate the alignment step, IBNAL makes use of a novel clique-based index and is able to align large networks in seconds. IBNAL produces a higher topological quality alignment and comparable biological match in alignment relative to other state-of-the-art aligners even though topological fit is primarily used to match nodes. IBNAL's results confirm and give another evidence that homology information is more likely to be encoded in network topology than sequence information.
网络结构数据的网络对齐在许多近期应用中受到了广泛关注。全局网络对齐试图唯一地找到将一个网络中的节点映射到另一个网络中的唯一节点的最佳方法。映射是根据取决于数据性质的一些匹配标准执行的。在分子生物学中，功能直系同源物、蛋白质复合物和进化保守途径是通过全局网络对齐揭示的一些信息的示例。全局网络对齐的当前技术存在一些缺点，例如性能差和内存需求高。我们通过提出 IBNAL（基于索引的网络对齐器）来解决这些问题，以获得更好的对齐质量和更快的结果。为了加速对齐步骤，IBNAL 利用了一种新颖的基于团的索引，能够在几秒钟内对齐大型网络。与其他最先进的对齐器相比，IBNAL 产生的拓扑质量对齐更高，并且在对齐方面具有可比的生物学匹配，尽管拓扑拟合主要用于匹配节点。IBNAL 的结果证实并提供了另一个证据，即同源信息更有可能编码在网络拓扑中，而不是序列信息中。
