A system-wide understanding of cellular function requires knowledge of all functional interactions between the expressed proteins. The STRING database aims to collect and integrate this information, by consolidating known and predicted protein-protein association data for a large number of organisms. The associations in STRING include direct (physical) interactions, as well as indirect (functional) interactions, as long as both are specific and biologically meaningful. Apart from collecting and reassessing available experimental data on protein-protein interactions, and importing known pathways and protein complexes from curated databases, interaction predictions are derived from the following sources: (i) systematic co-expression analysis, (ii) detection of shared selective signals across genomes, (iii) automated text-mining of the scientific literature and (iv) computational transfer of interaction knowledge between organisms based on gene orthology. In the latest version 10.5 of STRING, the biggest changes are concerned with data dissemination: the web frontend has been completely redesigned to reduce dependency on outdated browser technologies, and the database can now also be queried from inside the popular Cytoscape software framework. Further improvements include automated background analysis of user inputs for functional enrichments, and streamlined download options. The STRING resource is available online, at http://string-db.org/.

/pdf/the-string-database-in-2017-quality-controlled-protein-1u6rx6raii.pdf

The STRING database in 2017: quality-controlled protein-protein association networks, made broadly accessible.

Outcomes of high-throughput biological experiments are typically interpreted by statistical testing for enriched gene functional categories defined by the Gene Ontology (GO). The resulting lists of GO terms may be large and highly redundant, and thus difficult to interpret.

REVIGO is a Web server that summarizes long, unintelligible lists of GO terms by finding a representative subset of the terms using a simple clustering algorithm that relies on semantic similarity measures. Furthermore, REVIGO visualizes this non-redundant GO term set in multiple ways to assist in interpretation: multidimensional scaling and graph-based visualizations accurately render the subdivisions and the semantic relationships in the data, while treemaps and tag clouds are also offered as alternative views. REVIGO is freely available at http://revigo.irb.hr/.

/pdf/revigo-summarizes-and-visualizes-long-lists-of-gene-ontology-3taarmiz8n.pdf

REVIGO Summarizes and Visualizes Long Lists of Gene Ontology Terms

The elucidation of breast cancer subgroups and their molecular drivers requires integrated views of the genome and transcriptome from representative numbers of patients. We present an integrated analysis of copy number and gene expression in a discovery and validation set of 997 and 995 primary breast tumours, respectively, with long-term clinical follow-up. Inherited variants (copy number variants and single nucleotide polymorphisms) and acquired somatic copy number aberrations (CNAs) were associated with expression in 40% of genes, with the landscape dominated by cisand trans-acting CNAs. By delineating expression outlier genes driven in cis by CNAs, we identified putative cancer genes, including deletions in PPP2R2A, MTAP and MAP2K4. Unsupervised analysis of paired DNA–RNA profiles revealed novel subgroups with distinct clinical outcomes, which reproduced in the validation cohort. These include a high-risk, oestrogen-receptor-positive 11q13/14 cis-acting subgroup and a favourable prognosis subgroup devoid of CNAs. Trans-acting aberration hotspots were found to modulate subgroup-specific gene networks, including a TCR deletion-mediated adaptive immune response in the ‘CNA-devoid’ subgroup and a basal-specific chromosome 5 deletion-associated mitotic network. Our results provide a novel molecular stratification of the breast cancer population, derived from the impact of somatic CNAs on the transcriptome.

/pdf/the-genomic-and-transcriptomic-architecture-of-2-000-breast-c1simcg604.pdf

The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups

Summary: Cytoscape is a popular bioinformatics package for biological network visualization and data integration. Version 2.8 introduces two powerful new features—Custom Node Graphics and Attribute Equations—which can be used jointly to greatly enhance Cytoscape's data integration and visualization capabilities. Custom Node Graphics allow an image to be projected onto a node, including images generated dynamically or at remote locations. Attribute Equations provide Cytoscape with spreadsheet-like functionality in which the value of an attribute is computed dynamically as a function of other attributes and network properties.

Availability and implementation: Cytoscape is a desktop Java application released under the Library Gnu Public License (LGPL). Binary install bundles and source code for Cytoscape 2.8 are available for download from http://cytoscape.org.

Contact: [email protected]

Cytoscape 2.8

An essential prerequisite for any systems-level understanding of cellular functions is to correctly uncover and annotate all functional interactions among proteins in the cell. Toward this goal, remarkable progress has been made in recent years, both in terms of experimental measurements and computational prediction techniques. However, public efforts to collect and present protein interaction information have struggled to keep up with the pace of interaction discovery, partly because protein-protein interaction information can be error-prone and require considerable effort to annotate. Here, we present an update on the online database resource Search Tool for the Retrieval of Interacting Genes (STRING); it provides uniquely comprehensive coverage and ease of access to both experimental as well as predicted interaction information. Interactions in STRING are provided with a confidence score, and accessory information such as protein domains and 3D structures is made available, all within a stable and consistent identifier space. New features in STRING include an interactive network viewer that can cluster networks on demand, updated on-screen previews of structural information including homology models, extensive data updates and strongly improved connectivity and integration with third-party resources. Version 9.0 of STRING covers more than 1100 completely sequenced organisms; the resource can be reached at http://string-db.org.

https://www.zora.uzh.ch/id/eprint/41629/4/21045058_V.pdf

The STRING database in 2011: functional interaction networks of proteins, globally integrated and scored

Cytoscape is a free software package for visualizing, modeling and analyzing molecular and genetic interaction networks. This protocol explains how to use Cytoscape to analyze the results of mRNA expression profiling, and other functional genomics and proteomics experiments, in the context of an interaction network obtained for genes of interest. Five major steps are described: (i) obtaining a gene or protein network, (ii) displaying the network using layout algorithms, (iii) integrating with gene expression and other functional attributes, (iv) identifying putative complexes and functional modules and (v) identifying enriched Gene Ontology annotations in the network. These steps provide a broad sample of the types of analyses performed by Cytoscape.

/pdf/integration-of-biological-networks-and-gene-expression-data-40nso072qr.pdf

Integration of biological networks and gene expression data using Cytoscape

Allergic Contact Dermatitis (ACD; chemical-induced skin sensitisation) represents a key consumer safety endpoint for the cosmetics industry. At present, animal tests (predominantly the mouse Local Lymph Node Assay) are used to generate skin sensitisation hazard data for use in consumer safety risk assessments. An animal testing ban on chemicals to be used in cosmetics will come into effect in the European Union (EU) from March 2009. This animal testing ban is also linked to an EU marketing ban on products containing any ingredients that have been subsequently tested in animals, from March 2009 or March 2013, depending on the toxicological endpoint of concern. Consequently, the testing of cosmetic ingredients in animals for their potential to induce skin sensitisation will be subject to an EU marketing ban, from March 2013 onwards. Our conceptual framework and strategy to deliver a non-animal approach to consumer safety risk assessment can be summarised as an evaluation of new technologies (e.g. 'omics', informatics), leading to the development of new non-animal (in silico and in vitro) predictive models for the generation and interpretation of new forms of hazard characterisation data, followed by the development of new risk assessment approaches to integrate these new forms of data and information in the context of human exposure. Following the principles of the conceptual framework, we have been investigating existing and developing new technologies, models and approaches, in order to explore the feasibility of delivering consumer safety risk assessment decisions in the absence of new animal data. We present here our progress in implementing this conceptual framework, with the skin sensitisation endpoint used as a case study.

Assuring consumer safety without animal testing: a feasibility case study for skin sensitisation.

A report on the joint Cold Spring Harbor/Wellcome Trust Meeting 'Interactome Networks', Hinxton, UK, 31 August-4 September 2005. High-throughput analyses are identifying the DNA, RNA, proteins and metabolites within a biological system with increasing accuracy and speed. As a result, we now have a relatively detailed understanding of the components that make up the dynamic and temporal characteristics of the cell. In most cases, however, we know very little about how the individual components work together to carry out specific biological functions. To get over this hurdle, it will be necessary to map how individual biomolecules interact with one another within a larger network of molecular interactions (the so-called 'interactome') in the cell as a whole. Mapping this network is the shared goal of an increasing number of researchers from the UK, Europe, US, and Japan, who gathered at the first annual Cold Spring Harbor/Wellcome Trust meeting on interactome networks in Hinxton. This meeting provided an opportunity to review the recent experimental and computational advances that have been applied to uncover biomolecular interactions. Here we report a few of the key advances in the areas of new interaction-mapping techniques, new experimental reagents and resources, and new computational tools for understanding interaction networks that were presented at the meeting.

/pdf/interactome-networks-the-state-of-the-science-4xg9rwwci3.pdf

Guy J. Warner

Papers

Integration of biological networks and gene expression data using Cytoscape

Assuring consumer safety without animal testing: a feasibility case study for skin sensitisation.

Interactome networks: the state of the science

Development of a systems approach for the analysis of toxicogenomic data