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Transcriptomics to Metabolomics: A Network Perspective for Big Data

Transcriptomics to Metabolomics: A Network Perspective for Big Data

Ankush Bansal, Pulkit Anupam Srivastava
Copyright: © 2018 |Pages: 19
ISBN13: 9781522526070|ISBN10: 1522526072|EISBN13: 9781522526087
DOI: 10.4018/978-1-5225-2607-0.ch008
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MLA

Bansal, Ankush, and Pulkit Anupam Srivastava. "Transcriptomics to Metabolomics: A Network Perspective for Big Data." Applying Big Data Analytics in Bioinformatics and Medicine, edited by Miltiadis D. Lytras and Paraskevi Papadopoulou, IGI Global, 2018, pp. 188-206. https://doi.org/10.4018/978-1-5225-2607-0.ch008

APA

Bansal, A. & Srivastava, P. A. (2018). Transcriptomics to Metabolomics: A Network Perspective for Big Data. In M. Lytras & P. Papadopoulou (Eds.), Applying Big Data Analytics in Bioinformatics and Medicine (pp. 188-206). IGI Global. https://doi.org/10.4018/978-1-5225-2607-0.ch008

Chicago

Bansal, Ankush, and Pulkit Anupam Srivastava. "Transcriptomics to Metabolomics: A Network Perspective for Big Data." In Applying Big Data Analytics in Bioinformatics and Medicine, edited by Miltiadis D. Lytras and Paraskevi Papadopoulou, 188-206. Hershey, PA: IGI Global, 2018. https://doi.org/10.4018/978-1-5225-2607-0.ch008

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Abstract

A lot of omics data is generated in a recent decade which flooded the internet with transcriptomic, genomics, proteomics and metabolomics data. A number of software, tools, and web-servers have developed to analyze the big data omics. This review integrates the various methods that have been employed over the years to interpret the gene regulatory and metabolic networks. It illustrates random networks, scale-free networks, small world network, bipartite networks and other topological analysis which fits in biological networks. Transcriptome to metabolome network is of interest because of key enzymes identification and regulatory hub genes prediction. It also provides an insight into the understanding of omics technologies, generation of data and impact of in-silico analysis on the scientific community.

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