An Faster Network Motif Detection Tool

TL;DR

This paper introduces an enhanced network motif detection tool that efficiently identifies motifs up to six vertices using multithreading and a novel enumeration algorithm, significantly improving performance over existing methods.

Contribution

The paper presents a new enumeration algorithm with lower complexity, supports motifs up to six vertices, and employs multithread processing for faster network motif detection.

Findings

Faster motif detection for motifs up to 6 vertices

Lower computational complexity with the new algorithm

Improved performance over existing methods

Abstract

Network motif provides a way to uncover the basic building blocks of most complex networks. This task usually demands high computer processing, specially for motif with 5 or more vertices. This paper presents an extended methodology with the following features: (i) search for motifs up to 6 vertices, (ii) multithread processing, and a (iii) new enumeration algorithm with lower complexity. The algorithm to compute motifs solve isomorphism in $O(1)$ with the use of hash table. Concurrent threads evaluates distinct graphs. The enumeration algorithm has smaller computational complexity. The experiments shows better performance with respect to other methods available in literature, allowing bioinformatic researchers to efficiently identify motifs of size 3, 4, 5, and 6.