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
Lateef Zabeen et al., Transcriptomic analysis of human norovirus NS1-2 protein highlights a multifunctional role in murine monocytes Transcriptomic methods. BMC Genomics (2017) doi:10.1186/s12864-016-3417-4
Lee Shih-Wei et al., Gene expression profiling identifies candidate biomarkers for active and latent tuberculosis. BMC Bioinformatics (2016) doi:10.1186/s12859-015-0848-x
Huang Kai-Yao et al., A new scheme to discover functional associations and regulatory networks of E3 ubiquitin ligases. BMC Systems Biology (2016) doi:10.1186/s12918-015-0244-1
Jin Ying et al., Identification of novel gene and pathway targets for human epilepsy treatment. Biological Research (2016) doi:10.1186/s40659-015-0060-5
Bertoni Natália et al., Integrative meta-analysis identifies microRNA-regulated networks in infantile hemangioma Clinical-Molecular Genetics and Cytogenetics. BMC Medical Genetics (2016) doi:10.1186/s12881-015-0262-2