Abstract
High-throughput (HTP) technologies enabling the simultaneous measurement of thousands of genes, proteins, and metabolites offer new opportunities for understanding the complex mechanisms underlying physiology, health, and disease. Mining these large “omics” datasets (transcriptomics, proteomics, and metabolomics) has required addressing issues such as high dimensionality of the data, experimental variability, noise, and low sensitivity of the methodologies. Numerous approaches have been developed to handle these issues and to utilize these datasets to generate meaningful biological insights. This chapter describes the types of omics measurements that have been performed on mammalian macrophage cells, methods, and tools for their analysis, and examples of insights gained in macrophage biology.
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Acknowledgments
This work is supported by the following grants to SS: NIH Collaborative Grant U54 GM69338-04 (LIPID MAPS), NIH/NIGMS Grant GM078005-05, NHLBI Grants R33 HL087375-02, R01 HL113601, 5R01HL106579, 1R01HL108735-10A1 and NIDDK Grant P01-DK074868, and NSF Collaborative Grants DBI-0835541 and STC 0939370. SG, ARD, MG, and MRM contributed equally to writing the first draft of this chapter. SG compiled and edited this chapter. SS provided overall supervision and revised the manuscript for submission.
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Gupta, S., Dinasarapu, A.R., Gersten, M.J., Maurya, M.R., Subramaniam, S. (2014). Omics Approaches to Macrophage Biology. In: Biswas, S., Mantovani, A. (eds) Macrophages: Biology and Role in the Pathology of Diseases. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-1311-4_29
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