NemoProfile as an efficient approach to network motif analysis with instance collection

BMC Bioinformatics

Research

Wooyoung Kim¹  Lynnette Haukap¹ 

[1] Division of Computing and Software Systems, School of Science, Technology, Engineering, and Mathematics (STEM), University of Washington Bothell, 18115 Campus Way NE, 98011-8246, Bothell, WA, USA;

关键词: NemoProfile;    NemoCollect;    ESU;    Systems biology;    Biological network;    Network motif;    Essential protein;   

DOI  :  10.1186/s12859-017-1822-6

来源: Springer

【 摘 要 】

BackgroundA network motif is defined as a statistically significant and recurring subgraph pattern within a network. Most existing instance collection methods are not feasible due to high memory usage issues and provision of limited network motif information. They require a two-step process that requires network motif identification prior to instance collection. Due to the impracticality in obtaining motif instances, the significance of their contribution to problem solving is debated within the field of biology.ResultsThis paper presents NemoProfile, an efficient new network motif data model. NemoProfile simplifies instance collection by resolving memory overhead issues and is seamlessly generated, thus eliminating the need for costly two-step processing. Additionally, a case study was conducted to demonstrate the application of network motifs to existing problems in the field of biology.ConclusionNemoProfile comprises network motifs and their instances, thereby facilitating network motifs usage in real biological problems.

【 授权许可】

CC BY   
© The Author(s) 2017

【 图 表 】

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