Abstract
Network biology has been widely used for the interaction studies and analysis in modern era. Studies associated with biological networks, their modeling, analysis, and visualization are imperative to the biological world. The advancements in network biology have helped us better understand the biomolecular complexities which in earlier times were difficult to study in vivo. High-throughput technologies have revolutionized the genomic-sequencing procedures for the generation of tremendous data that need to be analyzed and interpreted rigorously. However it has still been difficult to construe biological networks completely due to the complexity of the interactions that exist between its components. Great efforts have been made to disclose the maximum possible interactions that are significant to maintain the potential mechanisms with the help of network biology. With improvement in the analysis process, network biology has thought to be playing a key role in understanding the complex biological behavior of the networks. In this chapter we will cover the basics of network biology and its expansion in various disciplines and its implementations in complex diseases and disorders, current resources, and tools available for studying diverse forms of pathways (transcriptional regulation, protein–protein interaction, signal transduction, and metabolism). This chapter therefore deals with the core of network biology, its role in various disease studies, and the advancements introduced so far in this field.
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© 2017 Shanghai Jiao Tong University Press, Shanghai and Springer Science+Business Media Dordrecht
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Shukla, A., Singh, T.R. (2017). Computational Network Approaches and Their Applications for Complex Diseases. In: Wei, DQ., Ma, Y., Cho, W., Xu, Q., Zhou, F. (eds) Translational Bioinformatics and Its Application. Translational Medicine Research. Springer, Dordrecht. https://doi.org/10.1007/978-94-024-1045-7_14
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DOI: https://doi.org/10.1007/978-94-024-1045-7_14
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