STITCH: interaction networks of chemicals and proteins

The knowledge about interactions between proteins and small molecules is essential for the understanding of molecular and cellular functions. However, information on such interactions is widely dispersed across numerous databases and the literature. To facilitate access to this data, STITCH (‘search tool for interactions of chemicals’) integrates information about interactions from metabolic pathways, crystal structures, binding experiments and drug–target relationships. Inferred information from phenotypic effects, text mining and chemical structure similarity is used to predict relations between chemicals. STITCH further allows exploring the network of chemical relations, also in the context of associated binding proteins. Each proposed interaction can be traced back to the original data sources. Our database contains interaction information for over 68 000 different chemicals, including 2200 drugs, and connects them to 1.5 million genes across 373 genomes and their interactions contained in the STRING database. STITCH is available at http://stitch.embl.de

Constructing female entrepreneurship policy in the UK : is the US a relevant benchmark?

Successive UK governments have introduced a range of policy initiatives designed to encourage more women to start new firms. Underpinning these policies has been an explicit ambition for the UK to achieve similar participation rates as those in the US where it is widely reported that women own nearly half the stock of businesses. The data underlying these objectives are critically evaluated and it is argued that the definitions and measures of female enterprise used in the UK and the US restrict meaningful comparisons between the two. It is suggested that the expansion of female entrepreneurship in the US is historically and culturally specific to that country. UK policy goals should reflect the national socioeconomic context, while drawing upon good practice examples from a range of other countries. The paper concludes by discussing the economic and social viability of encouraging more women in the UK to enter self-employment without fully recognising the intensely competitive sectors in which they are often located

GLIDA: GPCR—ligand database for chemical genomics drug discovery—database and tools update

G-protein coupled receptors (GPCRs) represent one of the most important families of drug targets in pharmaceutical development. GLIDA is a public GPCR-related Chemical Genomics database that is primarily focused on the integration of information between GPCRs and their ligands. It provides interaction data between GPCRs and their ligands, along with chemical information on the ligands, as well as biological information regarding GPCRs. These data are connected with each other in a relational database, allowing users in the field of Chemical Genomics research to easily retrieve such information from either biological or chemical starting points. GLIDA includes a variety of similarity search functions for the GPCRs and for their ligands. Thus, GLIDA can provide correlation maps linking the searched homologous GPCRs (or ligands) with their ligands (or GPCRs). By analyzing the correlation patterns between GPCRs and ligands, we can gain more detailed knowledge about their conserved molecular recognition patterns and improve drug design efforts by focusing on inferred candidates for GPCR-specific drugs. This article provides a summary of the GLIDA database and user facilities, and describes recent improvements to database design, data contents, ligand classification programs, similarity search options and graphical interfaces. GLIDA is publicly available at http://pharminfo.pharm.kyoto-u.ac.jp/services/glida/. We hope that it will prove very useful for Chemical Genomics research and GPCR-related drug discovery

Bioinformatics Training Network (BTN): a community resource for bioinformatics trainers

Funding bodies are increasingly recognizing the need to provide graduates and researchers with access to short intensive courses in a variety of disciplines, in order both to improve the general skills base and to provide solid foundations on which researchers may build their careers. In response to the development of ‘high-throughput biology’, the need for training in the field of bioinformatics, in particular, is seeing a resurgence: it has been defined as a key priority by many Institutions and research programmes and is now an important component of many grant proposals. Nevertheless, when it comes to planning and preparing to meet such training needs, tension arises between the reward structures that predominate in the scientific community which compel individuals to publish or perish, and the time that must be devoted to the design, delivery and maintenance of high-quality training materials. Conversely, there is much relevant teaching material and training expertise available worldwide that, were it properly organized, could be exploited by anyone who needs to provide training or needs to set up a new course. To do this, however, the materials would have to be centralized in a database and clearly tagged in relation to target audiences, learning objectives, etc. Ideally, they would also be peer reviewed, and easily and efficiently accessible for downloading. Here, we present the Bioinformatics Training Network (BTN), a new enterprise that has been initiated to address these needs and review it, respectively, to similar initiatives and collections

Effects of sex hormones on vascular reactivity in boys with hypospadias

Background: Arteries from boys with hypospadias demonstrate hypercontractility and impaired vasorelaxation. The role of sex hormones in these responses in unclear. Aims: We compared effects of sex steroids on vascular reactivity in healthy boys and boys with hypospadias. Methods: Excess foreskin tissue was obtained from 11 boys undergoing hypospadias repair (cases) and 12 undergoing routine circumcision (controls) (median age [range], 1.5 [1.2-2.7] years) and small resistance arteries were isolated. Vessels were mounted on wire myographs and vascular reactivity was assessed in the absence/presence of 17β-estradiol, dihydrotestosterone (DHT), and testosterone. Results: In controls, testosterone and 17β-estradiol increased contraction (percent of maximum contraction [Emax]: 83.74 basal vs 125.4 after testosterone, P < .0002; and 83.74 vs 110.2 after estradiol, P = .02). 17β-estradiol reduced vasorelaxation in arteries from controls (Emax: 10.6 vs 15.6 to acetylcholine, P < .0001; and Emax: 14.6 vs 20.5 to sodium nitroprusside, P < .0001). In hypospadias, testosterone (Emax: 137.9 vs 107.2, P = .01) and 17β-estradiol (Emax: 156.9 vs 23.6, P < .0001) reduced contraction. Androgens, but not 17β-estradiol, increased endothelium-dependent and endothelium-independent vasorelaxation in cases (Emax: 77.3 vs 51.7 with testosterone, P = .02; and vs 48.2 with DHT to acetylcholine, P = .0001; Emax: 43.0 vs 39.5 with testosterone, P = .02; and 39.6 vs 37.5 with DHT to sodium nitroprusside, P = .04). Conclusion: In healthy boys, testosterone and 17β-estradiol promote a vasoconstrictor phenotype, whereas in boys with hypospadias, these sex hormones reduce vasoconstriction, with androgens promoting vasorelaxation. Differences in baseline artery function may therefore be sex hormone-independent and the impact of early-life variations in androgen exposure on vascular function needs further study

Classificatory Theory in Data-Intensive Science: The Case of Open Biomedical Ontologies

publication-status: Publishedtypes: ArticleThis is the author's version of a paper that was subsequently published in International Studies in the Philosophy of Science. Please cite the published version by following the DOI link.Knowledge-making practices in biology are being strongly affected by the availability of data on an unprecedented scale, the insistence on systemic approaches and growing reliance on bioinformatics and digital infrastructures. What role does theory play within data-intensive science, and what does that tell us about scientific theories in general? To answer these questions, I focus on Open Biomedical Ontologies, digital classification tools that have become crucial to sharing results across research contexts in the biological and biomedical sciences, and argue that they constitute an example of classificatory theory. This form of theorizing emerges from classification practices in conjunction with experimental know-how and expresses the knowledge underpinning the analysis and interpretation of data disseminated online.Economic and Social Research Council (ESRC)The British AcademyLeverhulme Trus