Networking omic data to envisage systems biological regulation
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Publication Details
Author list: Kalapanulak S., Saithong T., Thammarongtham C.
Publisher: Springer Verlag Kg
Publication year: 2017
Journal: Advances in Biochemical Engineering Biotechnology (0724-6145)
Volume number: 160
Start page: 121
End page: 141
Number of pages: 21
ISBN: 978-3-319-56459-3
ISSN: 0724-6145
Languages: English-Great Britain (EN-GB)
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Abstract
To understand how biological processes work, it is necessary to explore the systematic regulation governing the behaviour of the processes. Not only driving the normal behavior of organisms, the systematic regulation evidently underlies the temporal responses to surrounding environments (dynamics) and long-term phenotypic adaptation (evolution). The systematic regulation is, in effect, formulated from the regulatory components which collaboratively work together as a network. In the drive to decipher such a code of lives, a spectrum of technologies has continuously been developed in the post-genomic era. With current advances, high-throughput sequencing technologies are tremendously powerful for facilitating genomics and systems biology studies in the attempt to understand system regulation inside the cells. The ability to explore relevant regulatory components which infer transcriptional and signaling regulation, driving core cellular processes, is thus enhanced. This chapter reviews high-throughput sequencing technologies, including second and third generation sequencing technologies, which support the investigation of genomics and transcriptomics data. Utilization of this high-throughput data to form the virtual network of systems regulation is explained, particularly transcriptional regulatory networks. Analysis of the resulting regulatory networks could lead to an understanding of cellular systems regulation at the mechanistic and dynamics levels. The great contribution of the biological networking approach to envisage systems regulation is finally demonstrated by a broad range of examples. ฉ 2016, Springer International Publishing Switzerland.
Keywords
High throughput sequencing, Network biology, Network reconstruction, Systems regulation
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