From Big Data Analytics and Network Inference to Systems Modeling

Pawel Michalak, Bruno W. Sobral, Vida Abedi, Young Bun Kim, Xinwei Deng, Casandra Philipson, Monica Viladomiu, Pinyi Lu, Katherine Wendelsdorf, Raquel Hontecillas, Josep Bassaganya-Riera

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Informatics approaches that integrate high-throughput datasets across multicellular components and time points with predictive network modeling emerge as essential tools for understanding the organization, function, and dynamics of the immune system, and its relation to health and disease. Here we focus on integrative bioinformatics and network modeling techniques applied to large genome-wide transcriptional profiles enabled by the recent advancement of sequencing technologies. RNA sequencing (RNA-Seq) is widely used to characterize global changes in gene expression. In this chapter, we provide an introduction to RNA-Seq analysis, including its popular Galaxy implementation, cloud solutions, as well as applications to microbial transcriptomics (RNA Rocket). We also present a suite of new data analytic, network inference and supervised machine learning methods that can be integrated with the RNA-Seq pipeline toward comprehensive, predictive networks describing immune processes at the mechanistic level.

Original languageEnglish (US)
Title of host publicationComputational Immunology
Subtitle of host publicationModels and Tools
PublisherElsevier Inc.
Pages113-144
Number of pages32
ISBN (Electronic)9780128037157
ISBN (Print)9780128036976
DOIs
StatePublished - 2016

All Science Journal Classification (ASJC) codes

  • Medicine(all)

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