The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Transcriptomics to Metabolomics: A Network Perspective for Big Data
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.
Related Content
Linkon Chowdhury, Md Sarwar Kamal, Shamim H. Ripon, Sazia Parvin, Omar Khadeer Hussain, Amira Ashour, Bristy Roy Chowdhury.
© 2024.
20 pages.
|
Mousomi Roy.
© 2024.
21 pages.
|
Nassima Dif, Zakaria Elberrichi.
© 2024.
20 pages.
|
Pyingkodi Maran, Shanthi S., Thenmozhi K., Hemalatha D., Nanthini K..
© 2024.
16 pages.
|
Mohamed Nadjib Boufenara, Mahmoud Boufaida, Mohamed Lamine Berkane.
© 2024.
16 pages.
|
Meroua Daoudi, Souham Meshoul, Samia Boucherkha.
© 2024.
25 pages.
|
Zhongyu Lu, Qiang Xu, Murad Al-Rajab, Lamogha Chiazor.
© 2024.
56 pages.
|
|
|