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Reverse enGENEering of Regulatory Networks from Big Data: A Roadmap for Biologists.


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.

SUBMITTER: Dong X 

PROVIDER: S-EPMC4415676 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Reverse enGENEering of Regulatory Networks from Big Data: A Roadmap for Biologists.

Dong Xiaoxi X   Yambartsev Anatoly A   Ramsey Stephen A SA   Thomas Lina D LD   Shulzhenko Natalia N   Morgun Andrey A  

Bioinformatics and biology insights 20150429


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  ...[more]

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