title: 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.
authors.affiliation: College of Pharmacy, Oregon State University, Corvallis, OR, USA.
authors.forename: Xiaoxi
authors.initials: X
authors.lastname: Dong
authors.affiliation: Department of Statistics, Institute of Mathematics and Statistics, University of Sao Paulo, Sao Paulo, SP, Brazil.
authors.forename: Anatoly
authors.initials: A
authors.lastname: Yambartsev
authors.affiliation: School of Electrical Engineering and Computer Science, Department of Biomedical Sciences, Oregon State University, Corvallis, OR, USA. ; College of Veterinary Medicine, Department of Biomedical Sciences, Oregon State University, Corvallis, OR, USA.
authors.forename: Stephen A
authors.initials: SA
authors.lastname: Ramsey
authors.affiliation: Department of Statistics, Institute of Mathematics and Statistics, University of Sao Paulo, Sao Paulo, SP, Brazil.
authors.forename: Lina D
authors.initials: LD
authors.lastname: Thomas
authors.affiliation: College of Veterinary Medicine, Department of Biomedical Sciences, Oregon State University, Corvallis, OR, USA.
authors.forename: Natalia
authors.initials: N
authors.lastname: Shulzhenko
authors.affiliation: College of Pharmacy, Oregon State University, Corvallis, OR, USA.
authors.forename: Andrey
authors.initials: A
authors.lastname: Morgun
keywords: big data; data integration; inter-omics network; network interrogation; network reconstruction; systems biology; transkingdom network