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Quantitative Biology > Molecular Networks

(q-bio)
[Submitted on 3 Nov 2014]

Title:Reverse enGENEering of regulatory networks from Big Data: a guide for a biologist

Authors:Xiaoxi Dong, Anatoly Yambartsev, Stephen Ramsey, Lina Thomas, Natalia Shulzhenko, Andrey Morgun
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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 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.
Subjects: Molecular Networks (q-bio.MN)
Cite as: arXiv:1411.0595 [q-bio.MN]
  (or arXiv:1411.0595v1 [q-bio.MN] for this version)
  https://doi.org/10.48550/arXiv.1411.0595
arXiv-issued DOI via DataCite

Submission history

From: Xiaoxi Dong [view email]
[v1] Mon, 3 Nov 2014 18:23:17 UTC (1,809 KB)
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