论文标题
Blant：网络拓扑的基本本地比对，第1部分：用明确的8节点绘制播种局部对齐
BLANT: Basic Local Alignment of Network Topology, Part 1: Seeding local alignments with unambiguous 8-node graphlets
论文作者
论文摘要
BLAST是生物信息学的标准工具，用于使用“种子和扩展”方法创建局部序列比对。在这里，我们介绍了一种类似的种子和扩展算法，该算法产生了本地网络对齐：Blant，用于网络拓扑的基本局部对齐。本文介绍了易碎的种子：给定输入图，单种子单独使用网络拓扑来创建一个有限的，高特异性的索引诱导k-graphlets（类似于Blasts的K-Mers）的k-node诱导子图。该索引的构建是这样，因此，如果两个图之间存在重要的共同网络拓扑，则它们的索引可能会重叠。然后，布兰特种子会查询两个网络的索引，以生成一个常见的k-graphlet列表，并在配对后形成一个种子对。我们的同伴论文（在其他地方提交）描述了Blant-Extend，该论文仅使用拓扑信息将这些种子“生长”到较大的本地对齐。
BLAST is a standard tool in bioinformatics for creating local sequence alignments using a "seed-and-extend" approach. Here we introduce an analogous seed-and-extend algorithm that produces local network alignments: BLANT, for Basic Local Alignment of Network Topology. This paper introduces BLANT-seed: given an input graph, BLANT-seed uses network topology alone to create a limited, high-specificity index of k-node induced subgraphs called k-graphlets (analogous to BLASTS's k-mers). The index is constructed so that, if significant common network topology exists between two graphs, their indexes are likely to overlap. BLANT-seed then queries the indexes of two networks to generate a list of common k-graphlets which, when paired, form a seed pair. Our companion paper (submitted elsewhere) describes BLANT-extend, which "grows" these seeds to larger local alignments, again using only topological information.
