TitleReverse enGENEering of Regulatory Networks from Big Data: A Roadmap for Biologists.
Publication TypeJournal Article
Year of Publication2015
AuthorsDong, X, Yambartsev, A, Ramsey, SA, Thomas, LD, Shulzhenko, N, Morgun, A
JournalBioinform Biol Insights
Volume9
Pagination61-74
Date Published2015
ISSN1177-9322
Abstract

Omics technologies enable unbiased investigation of biological systems through massively parallel sequence acquisition or molecular measurements, bringing the life sciences into the era of Big Data. A central challenge posed by such omics datasets is how to transform these data into biological knowledge, for example, how to use these data to answer questions such as: Which functional pathways are involved in cell differentiation? Which genes should we target to stop cancer? Network analysis is a powerful and general approach to solve this problem consisting of two fundamental stages, network reconstruction, and network interrogation. Here we provide an overview of network analysis including a step-by-step guide on how to perform and use this approach to investigate a biological question. In this guide, we also include the software packages that we and others employ for each of the steps of a network analysis workflow.

DOI10.4137/BBI.S12467
Alternate JournalBioinform Biol Insights
PubMed ID25983554
PubMed Central IDPMC4415676
Grant ListK25 HL098807 / HL / NHLBI NIH HHS / United States
R21 AI107485 / AI / NIAID NIH HHS / United States
U01 AI109695 / AI / NIAID NIH HHS / United States