known and predicted protein-protein interactions
Tutorial and training materials by OpenHelix
| Learn to use STRING, a database of known and predicted protein-protein interactions. Predictions are based on a series of evidences such as gene neighborhood, patterns of co-expression, text-mining of the literature and more. STRING allows the user to view data from individual evidences of interaction or view a 'network' of interactions among a collection of proteins. Learn to use this resource and find interaction predictions to facilitate characterization of gene and protein function. | Advertisement:
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You'll learn:
- how to search for predicted interactions with a selected gene product
- how to view networks of interactions among individual molecules or COGs
- the many types of evidences of interaction and how to analyze them
- how to find information from outside sources used in the predictions
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Related tutorialsThis tutorial is a part of the tutorial group Bork Group Resources. You might find the other tutorials in the group interesting: | Recent BioMed Central research articles citing this resourceLiu Baohua et al., Accumulation of prelamin A compromises NF-κB-regulated B-lymphopoiesis in a progeria mouse model. Longevity Healthspan (2013) doi:10.1186/2046-2395-2-1 Xie Li et al., Multiscale modeling of the causal functional roles of nsSNPs in a genome-wide association study: application to hypoxia SNP-SIG 2012: Identification and annotation of SNPs in the context of structure, function, and disease SNP-SIG 2012: Identification and annotation of SNPs in the context of structure, function, and disease. BMC Genomics (2013) doi:10.1186/1471-2164-14-S3-S9 Vigone Giulia et al., Transcriptome based identification of mouse cumulus cell markers that predict the developmental competence of their enclosed antral oocytes Human and rodent genomics. BMC Genomics (2013) doi:10.1186/1471-2164-14-380 Halbach Sebastian et al., Alterations of Gab2 signalling complexes in imatinib and dasatinib treated chronic myeloid leukaemia cells. Cell Communication and Signaling (2013) doi:10.1186/1478-811X-11-30 Issa Amine et al., Combinatorial targeting of FGF and ErbB receptors blocks growth and metastatic spread of breast cancer models. Breast Cancer Research (2013) doi:10.1186/bcr3379 |
More about the resource:
The STRING database of predicted molecular interactions was developed by the Bork Lab at the European Molecular Biology Laboratory (EMBL) in Heidelberg Germany. Predictions are based on a series of evidences and given scores of probability. Researchers can search for specific protein interactions (using gene name or other identifiers) or search for COG (Cluster of Orthologous Groups) predicted interactions. Most data views link out to other more detailed databases. This resource is a free publicly available tool.
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