Abstract
Biological data helps in disease analysis and drug discovery process. Study of protein–protein interactions plays a vital role to find the candidate proteins for causing chronicle diseases. Graphical representation of protein–protein interaction data gives more clues on protein functionality and pathways to research world. Many data sources are operating to provide such information upon request. However, each of them provides same information in different formats and levels. The word level denotes depth of interactions. This paper illustrates concatenation of different datasets related to target protein ERBB2 from prominent data sources. The resultant network highlights strong interactions of target protein after removing duplicate records with the help of computational tools and techniques, which makes work feasible and efficient.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
De Las Rivas J, Fontanillo C (2010) Protein–protein interactions essentials: key concepts to building and analyzing interactome networks. PLoS Comput Biol 6(6):e1000807. https://doi.org/10.1371/journal.pcbi.1000807
Zahiri J et al (2013) Computational prediction of protein-protein interaction networks: algorithms and resources. Curr Genomics 14:397–414
Mathivanan S et al (2006) An evaluation of human protein-protein interaction data in the public domain. BMC Bioinform 7:S19. https://doi.org/10.1186/1471-2105-7-S5-S19
Szklarczyk D et al (2014) STRING v10: protein–protein interaction networks, integrated over the tree of life. Nucleic Acids Res. https://doi.org/10.1093/nar/gku1003
Chatr-aryamontri A et al (2014) The BioGRID interaction database: 2015 update. Nucleic Acids Res 43:D470–D478. https://doi.org/10.1093/nar/gku1204
Orchard S et al (2013) The MIntAct project—IntAct as a common curation platform for 11 molecular interaction databases. Nucleic Acids Res 42:D358–D363. Database issue Published online 13 Nov 2013. https://doi.org/10.1093/nar/gkt1115
Rao VS, Srinivas K, Sujini GN, Kumar GN (2014) Protein protein interaction detection: methods and analysis. Int J Proteomics 2014, Article ID 147648 (Hindawi Publishing Corporation)
Mary Sujatha M, Srinivas K, Kiran Kumar R (2016) A review on computational methods used in construction of protein protein interaction network. IJEMR 6:71–77 (Vandana Publications)
Shannon P et al (2003) Cytoscape: a software environment for integrated models of biomolecular interaction networks. 13:2498–2504. ©2003 by Cold Spring Harbor Laboratory Press ISSN1088-9051/03
Apweiler R et al (2004) UniProt: the universal protein knowledgebase. Nucleic Acids Res 32(Database issue):D115–D119. https://doi.org/10.1093/nar/gkh131
Rodrigues FA et al (2010) Identifying abnormal nodes in protein-protein interaction networks. São José dos Campos, SP, Brazil, July 26–30, 2010
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2019 The Author(s)
About this chapter
Cite this chapter
Sujatha, M.M., Srinivas, K., Kumar, R.K. (2019). Construction of Breast Cancer-Based Protein–Protein Interaction Network Using Multiple Sources of Datasets. In: Soft Computing and Medical Bioinformatics. SpringerBriefs in Applied Sciences and Technology(). Springer, Singapore. https://doi.org/10.1007/978-981-13-0059-2_2
Download citation
DOI: https://doi.org/10.1007/978-981-13-0059-2_2
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-0058-5
Online ISBN: 978-981-13-0059-2
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)