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Accepted (AM)Open Access (License Unspecified), Open
Journal article
Integrating In Silico Resources to Map a Signaling Network
Methods in molecular biology (Clifton, N.J.), v 1101, pp 197-245
01 Jan 2014
PMID: 24233784
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
The abundance of publicly available life science databases offer a wealth of information that can support interpretation of experimentally derived data and greatly enhance hypothesis generation. Protein interaction and functional networks are not simply new renditions of existing data: they provide the opportunity to gain insights into the specific physical and functional role a protein plays as part of the biological system. In this chapter, we describe different
in silico
tools that can quickly and conveniently retrieve data from existing data repositories and discuss how the available tools are best utilized for different purposes. While emphasizing protein-protein interaction databases (e.g., BioGrid and IntAct), we also introduce metasearch platforms such as STRING and GeneMANIA, pathway databases (e.g., BioCarta and Pathway Commons), text mining approaches (e.g., PubMed and Chilibot), and resources for drug-protein interactions, genetic information for model organisms and gene expression information based on microarray data mining. Furthermore, we provide a simple step-by-step protocol to building customized protein-protein interaction networks in Cytoscape, a powerful network assembly and visualization program, integrating data retrieved from these various databases. As we illustrate, generation of composite interaction networks enables investigators to extract significantly more information about a given biological system than utilization of a single database or sole reliance on primary literature.
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Details
- Title
- Integrating In Silico Resources to Map a Signaling Network
- Creators
- Hanqing Liu - Fox Chase Cancer CenterTim N. Beck - Fox Chase Cancer CenterErica A. Golemis - Fox Chase Cancer CenterIlya G. Serebriiskii - Fox Chase Cancer Center
- Publication Details
- Methods in molecular biology (Clifton, N.J.), v 1101, pp 197-245
- Publisher
- Springer Nature
- Grant note
- P30 CA006927 || CA / National Cancer Institute : NCI U54 CA149147 || CA / National Cancer Institute : NCI P50 CA083638 || CA / National Cancer Institute : NCI R01 CA063366 || CA / National Cancer Institute : NCI
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Biochemistry and Molecular Biology
- Web of Science ID
- WOS:000328151100012
- Scopus ID
- 2-s2.0-84934438168
- Other Identifier
- 9781627037211; 1627037217; 991019319071204721
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Biochemical Research Methods
- Genetics & Heredity
- Mathematical & Computational Biology