Chapter title |
Computational Approaches to Study Gene Regulatory Networks
|
---|---|
Chapter number | 18 |
Book title |
Plant Gene Regulatory Networks
|
Published in |
Methods in molecular biology, June 2017
|
DOI | 10.1007/978-1-4939-7125-1_18 |
Pubmed ID | |
Book ISBNs |
978-1-4939-7124-4, 978-1-4939-7125-1
|
Authors |
Omranian, Nooshin, Nikoloski, Zoran, Nooshin Omranian, Zoran Nikoloski |
Editors |
Kerstin Kaufmann, Bernd Mueller-Roeber |
Abstract |
The goal of the gene regulatory network (GRN) inference is to determine the interactions between genes given heterogeneous data capturing spatiotemporal gene expression. Since transcription underlines all cellular processes, the inference of GRN is the first step in deciphering the determinants of the dynamics of biological systems. Here, we first describe the generic steps of the inference approaches that rely on similarity measures and group the similarity measures based on the computational methodology used. For each group of similarity measures, we not only review the existing approaches but also describe specifically the detailed steps of the existing state-of-the-art algorithms. |
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