MOTIVATION: ADME SARfari is a freely available web resource that enables comparative analyses of drug-disposition genes. It does so by integrating a number of publicly available data sources, which have subsequently been used to build data mining services, predictive tools and visualizations for drug metabolism researchers. The data include the interactions of small molecules with ADME (absorption, distribution, metabolism and excretion) proteins responsible for the metabolism and transport of molecules; available pharmacokinetic (PK) data; protein sequences of ADME-related molecular targets for pre-clinical model species and human; alignments of the orthologues including information on known SNPs (Single Nucleotide Polymorphism) and information on the tissue distribution of these proteins. In addition, in silico models have been developed, which enable users to predict which ADME relevant protein targets a novel compound is likely to interact with.

This paper introduces a project to develop a reliable, cost‐effective method for classifying Internet texts into register categories, and apply that approach to the analysis of a large corpus of web documents. To date, the project has proceeded in 2 key phases. First, we developed a bottom‐up method for web register classification, asking end users of the web to utilize a decision‐tree survey to code relevant situational characteristics of web documents, resulting in a bottom‐up identification of register and subregister categories. We present details regarding the development and testing of this method through a series of 10 pilot studies. Then, in the second phase of our project we applied this procedure to a corpus of 53,000 web documents. An analysis of the results demonstrates the effectiveness of these methods for web register classification and provides a preliminary description of the types and distribution of registers on the web.

This paper reports on a study of 4CG, a cooperative enterprise located in rural Wales. 4CG operates for the good of the local economy and seeks to diversify its commercial portfolio through the creation of an online shop retailing goods and services from local suppliers. The paper compliments prior field studies focusing on rural enterprise and the challenges posed by this category of business for IT support. The current study is motivated by 4CG’s interest in setting up a local online shop and explicates the organisational issues that this venture turns upon and elaborates for broader sustainability agendas.

When are two entries about a small molecule in different datasets the same? If they have the same drug name, chemical structure, or some other criteria? The choice depends upon the application to which the data will be put. However, existing Linked Data approaches provide a single global view over the data with no way of varying the notion of equivalence to be applied.In this paper, we present an approach to enable applications to choose the equivalence criteria to apply between datasets. Thus, supporting multiple dynamic views over the Linked Data. For chemical data, we show that multiple sets of links can be automatically generated according to different equivalence criteria and published with semantic descriptions capturing their context and interpretation. This approach has been applied within a large scale public-private data integration platform for drug discovery. To cater for different use cases, the platform allows the application of different lenses which vary the equivalence rules to be applied based on the context and interpretation of the links.

MOTIVATION: Resource description framework (RDF) is an emerging technology for describing, publishing and linking life science data. As a major provider of bioinformatics data and services, the European Bioinformatics Institute (EBI) is committed to making data readily accessible to the community in ways that meet existing demand. The EBI RDF platform has been developed to meet an increasing demand to coordinate RDF activities across the institute and provides a new entry point to querying and exploring integrated resources available at the EBI.

UNLABELLED: myChEMBL is a completely open platform, which combines public domain bioactivity data with open source database and cheminformatics technologies. myChEMBL consists of a Linux (Ubuntu) Virtual Machine featuring a PostgreSQL schema with the latest version of the ChEMBL database, as well as the latest RDKit cheminformatics libraries. In addition, a self-contained web interface is available, which can be modified and improved according to user specifications. AVAILABILITY AND IMPLEMENTATION: The VM is available at: ftp://ftp.ebi.ac.uk/pub/databases/chembl/VM/myChEMBL/current. The web interface and web services code is available at: https://github.com/rochoa85/myChEMBL.

Ethnographic studies have played a key part in informing the design and development of a multitude of ubiquitous systems, from control room systems to pervasive games. While other papers have often focused on systems developed for urban contexts, this paper presents the initial findings of a study that focuses on a rural produce market in West Wales as a site for ubiquitous multimedia system-based intervention, digital economic considerations and co-design. The findings relate to the initial ethnographic fieldwork, digital-economic considerations for the site, the evolution of a participatory design strategy for developing a Market Portal and - importantly -- the way that these are informing the design of the ubiquitous technologies relating to the Market Portal.