RT Journal Article
SR Electronic
T1 Reverse enGENEering of regulatory networks from Big Data: a guide for a biologist
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 011056
DO 10.1101/011056
A1 Xiaoxi Dong, Postdoctoral scholar
A1 Anatoly Yambartsev, Assistant professor
A1 Stephen Ramsey, Assistant professor
A1 Lina Thomas, Graduate student
A1 Natalia Shulzhenko, Assistant professor
A1 Andrey Morgun, Assistant professor
YR 2014
UL http://biorxiv.org/content/early/2014/11/03/011056.abstract
AB 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 this data into biological knowledge. For example, how to use this 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. Herein, 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.