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.
You will learn:
This tutorial is a part of the tutorial group Text-related tools. You might find the other tutorials in the group interesting:
PubMatrix: PubMatrix, an on-line tool for multiplex literature mining of the PubMed database.
iHOP: Information Hyperlinked Over Proteins text mining resource
Textpresso: Text-mining the biological literature
Gene Ontology: Gene Ontology controlled vocabularies in biology
XplorMed: eXploring Medline abstracts
GoMiner: Ascribe biological significance to large lists of genes by annotating them with their corresponding GO categories
Controlled Vocabularies: Standardized term lists that can enhance interactions with biological databases
DAVID: A tool that analyzes large lists of genes to provide biological meaning
Entrez Overview: Overview of NCBI's Entrez Search Resource
PubMed: PubMed access to biomedical research literature
Literature and Text Mining : Tools which are related to scientific literature. Repositories, query tools, and mining resources are included.
Proteins : Tools that are primarily used in the storage, retrieval, or exploration of amino acid based data. Some tools may also involve nucleotide sequence information.
Pathways and Interactions : Tools that are involved with protein interactions and pathway features. Some tools are primarily repositories and some offer analysis options.
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Recent BioMed Central research articles citing this resource
Borirak Orawan et al., Quantitative proteomics analysis of an ethanol- and a lactate-producing mutant strain of Synechocystis sp. PCC6803. Biotechnology for Biofuels (2015) doi:10.1186/s13068-015-0294-z
Yong Han Chern et al., Prediction of problematic complexes from PPI networks: sparse, embedded, and small complexes. Biology Direct (2015) doi:10.1186/s13062-015-0067-4
Hayashi Junji et al., A proteomic profile of synoviocyte lesions microdissected from formalin-fixed paraffin-embedded synovial tissues of rheumatoid arthritis. Clinical Proteomics (2015) doi:10.1186/s12014-015-9091-8
Yeung N. W. Emily et al., Fibrinogen production is enhanced in an in-vitro model of non-alcoholic fatty liver disease: an isolated risk factor for cardiovascular events?. Lipids in Health and Disease (2015) doi:10.1186/s12944-015-0069-3
Yu Qian et al., Comparative proteomics analysis of Spodoptera frugiperda cells during Autographa californica multiple nucleopolyhedrovirus infection Other viruses (e.g. pox, papilloma, parvo, reoviridae). Virology Journal (2015) doi:10.1186/s12985-015-0346-9