Abstract
Next-generation sequencing techniques make it clear that all eukaryotes share significant portions of the genome specifying the core biological functions. Understanding of the biological function of such distributed proteins in one organism can normally be assigned to different species, which ultimately helps in extracting relevant biological information. This can be achieved by examining the basic components individually and then studying how these are connected in a network. Networks help in visualization and understanding the interactions between myriad components of a system that are mainly represented as graphs where different nodes (proteins) are connected via edges. The core biological information portrayal is provided by gene ontology that covers several domains of molecular and cellular biology. In this chapter, we tried to elaborate the data types extracted from various techniques and made them conveniently coherent to the readers through examples. We have also explained the complex biological networks theory comprehensively, following the functional analysis speculations, using real examples from various bioinformatics tools.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Albert R (2005) Scale-free networks in cell biology. J Cell Sci 118:4947–4957
Alberts B et al (2002) Molecular biology of the cell, 4th edn. Garland Science, New York
Arita M (2004) The metabolic world of Escherichia coli is not small. Proc Natl Acad Sci U S A 101:1543–1547
Bader S, Kühner S, Gavin AC (2008) Interaction networks for systems biology. FEBS Lett 582(8):1220–1224
Batada NN, Reguly T, Breitkreutz A, Boucher L, Breitkreutz BJ, Hurst LD et al (2006) Stratus not altocumulus: a new view of the yeast protein interaction network. PLoS Biol 4:e317
Beadle GW, Tatum EL (1941) Genetic control of biochemical reactions in Neurospora. Proc Natl Acad Sci U S A 27:499–506
Binns D et al (2009) QuickGO: a web-based tool for Gene Ontology searching. Bioinformatics 25(22):3045–3046
Blake JA (2013) Ten quick tips for using the gene ontology. PLoS Comput Biol 9(11):e1003343
Botstein D et al (2000) Gene Ontology: tool for the unification of biology. Nat Genet 25(1):25–29
Carbon S et al (2008) AmiGO: online access to ontology and annotation data. Bioinformatics 25(2):288–289
Goh KI, Cusick ME, Valle D, Childs B, Vidal M, Barabási AL (2007) The human disease network. Proc Natl Acad Sci 104(21):8685–8690
Han JD, Bertin N, Hao T, Goldberg DS, Berriz GF, Zhang LV, Dupuy D, Walhout AJ, Cusick ME, Roth FP, Vidal M (2004) Evidence for dynamically organized modularity in the yeast protein–protein interaction network. Nature 430(6995):88–93
Hill DP et al (2008) Gene Ontology annotations: what they mean and where they come from. BMC Bioinf 9(5):S2; BioMed Central
Huang DW, Sherman BT, Lempicki RA (2008) Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc 4(1):44
Langfelder P, Horvath S (2008) WGCNA: an R package for weighted correlation network analysis. BMC Bioinf 9(1):559
Ma’ayan A (2011) Introduction to network analysis in systems biology. Sci Signal 4(190):tr5
Reference Genome Group of the Gene Ontology Consortium (2009) The Gene Ontology’s Reference Genome Project: a unified framework for functional annotation across species. PLoS Comput Biol 5(7):e1000431
Shannon P et al (2003) Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res 13(11):2498–2504
Szklarczyk D et al (2016) The STRING database in 2017: quality-controlled protein–protein association networks, made broadly accessible. Nucleic Acids Res. https://doi.org/10.1093/nar/gkw937
Weirauch MT (2011) Gene coexpression networks for the analysis of DNA microarray data. In: Applied statistics for network biology: methods in systems biology. Wiley-Blackwell, Weinheim, pp 215–250
Yook SH, Oltvai ZN, Barabási AL (2004) Functional and topological characterization of protein interaction networks. Proteomics 4(4):928–942
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Bhat, B.A., Singh, G., Sharma, R., Yaseen, M., Ganai, N.A. (2019). Biological Networks: Tools, Methods, and Analysis. In: Shaik, N., Hakeem, K., Banaganapalli, B., Elango, R. (eds) Essentials of Bioinformatics, Volume I. Springer, Cham. https://doi.org/10.1007/978-3-030-02634-9_12
Download citation
DOI: https://doi.org/10.1007/978-3-030-02634-9_12
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-02633-2
Online ISBN: 978-3-030-02634-9
eBook Packages: Biomedical and Life SciencesBiomedical and Life Sciences (R0)