Towards lensfield: Data management, processing and semantic publication for vernacular e-science

Lensfield is a desktop and filesystem-based tool designed as a “personal data management assistant” for the scientist. It combines distributed version control (DVCS), software transaction memory (STM) and linked open data (LOD) publishing to create a novel data management, processing and publication tool. The application “just looks after” these technologies for the scientist, providing simple interfaces for typical uses. It is built with Clojure and includes macros which define steps in a common workflow. Functions and Java libraries provide facilities for automatic processing of data which is ultimately published as RDF in a web application. The progress of data processing is tracked by a fine-grained data structure that can be serialized to disk, with the potential to include manual steps and programmatic interrupts in largely automated processes through seamless resumption. Flexibility in operation and minimizing barriers to adoption are major design features.This paper was presented at the IEEE eScience conference 2009, hosted by the Oxford eResearch Centre and held at the Kassam Stadium outside Oxford

MACiE: a database of enzyme reaction mechanisms.

SUMMARY: MACiE (mechanism, annotation and classification in enzymes) is a publicly available web-based database, held in CMLReact (an XML application), that aims to help our understanding of the evolution of enzyme catalytic mechanisms and also to create a classification system which reflects the actual chemical mechanism (catalytic steps) of an enzyme reaction, not only the overall reaction. AVAILABILITY: http://www-mitchell.ch.cam.ac.uk/macie/.EPSRC (G.L.H. and J.B.O.M.), the BBSRC (G.J.B. and J.M.T.—CASE studentship in association with Roche Products Ltd; N.M.O.B. and J.B.O.M.—grant BB/C51320X/1), the Chilean Government’s Ministerio de Planificacio´n y Cooperacio´n and Cambridge Overseas Trust (D.E.A.) for funding and Unilever for supporting the Centre for Molecular Science Informatics.application note restricted to 2 printed pages web site: http://www-mitchell.ch.cam.ac.uk/macie

Blue Obelisk - Interoperability in chemical informatics

The Blue Obelisk Movement (http://www.blueobelisk.org/) is the name used by a diverse Internet group promoting reusable chemistry via open source software development, consistent and complimentary chemoinformatics research, open data, and open standards. We outline recent examples of cooperation in the Blue Obelisk group:  a shared dictionary of algorithms and implementations in chemoinformatics algorithms drawing from our various software projects; a shared repository of chemoinformatics data including elemental properties, atomic radii, isotopes, atom typing rules, and so forth; and Web services for the platform-independent use of chemoinformatics programs

The influence of stereotypes about old age on the perception of elderly employees’ labor activity

In this article the problem of increasing retirement age in terms of age discrimination and creating conditions encouraging elderly people to continue to work is discussed. This paper presents a study of stereotypes that affect students of management specialties in Russian institutions of higher education between the ages of 20 to 25 years old. The stereotype is investigated in the context of emotionally colored image of reality simplifying the process of perceiving it. The correlation between the students’ existing stereotypes about elderly people and their perception of older employees has been conducted. As a result, 5 stereotypes that exist in young people have been defined. An analysis of the words chosen by students to describe the elderly shows little diversity in young people’s perception of them. Lexical analysis shows that in the Russian language there are practically no concepts which allow creating a positive image of the elderly. The influence of the stereotypes on the perception of elderly people in terms of employment shows that older specialists are perceived as people with experience and knowledge but these experience and knowledge are irrelevant to the present

Ami - The Chemist's Amanuensis

RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are.Abstract The Ami project was a six month Rapid Innovation project sponsored by JISC to explore the Virtual Research Environment space. The project brainstormed with chemists and decided to investigate ways to facilitate monitoring and collection of experimental data. A frequently encountered use-case was identified of how the chemist reaches the end of an experiment, but finds an unexpected result. The ability to replay events can significantly help make sense of how things progressed. The project therefore concentrated on collecting a variety of dimensions of ancillary data - data that would not normally be collected due to practicality constraints. There were three main areas of investigation: 1) Development of a monitoring tool using infrared and ultrasonic sensors; 2) Time-lapse motion video capture (for example, videoing 5 seconds in every 60); and 3) Activity-driven video monitoring of the fume cupboard environs. The Ami client application was developed to control these separate logging functions. The application builds up a timeline of the events in the experiment and around the fume cupboard. The videos and data logs can then be reviewed after the experiment in order to help the chemist determine the exact timings and conditions used. The project experimented with ways in which a Microsoft Kinect could be used in a laboratory setting. Investigations suggest that it would not be an ideal device for controlling a mouse, but it shows promise for usages such as manipulating virtual molecules.Peer Reviewe

Report from the “What is Open?” Workgroup

The scholarly community’s current definition of “open” captures only some of the attributes of openness that exist across different publishing models and content types. Open is not an end in itself, but a means for achieving the most effective dissemination of scholarship and research. We suggest that the different attributes of open exist along a broad spectrum and propose an alternative way of describing and evaluating openness based on four attributes: discoverable, accessible, reusable, and transparent. These four attributes of openness, taken together, form the draft “DART Framework for Open Access.” This framework can be applied to both research artifacts as well as research processes. We welcome input from the broader scholarly community about this framework

MACiE (Mechanism, Annotation and Classification in Enzymes): novel tools for searching catalytic mechanisms

MACiE (Mechanism, Annotation and Classification in Enzymes) is a database of enzyme reaction mechanisms, and is publicly available as a web-based data resource. This paper presents the first release of a web-based search tool to explore enzyme reaction mechanisms in MACiE. We also present Version 2 of MACiE, which doubles the dataset available (from Version 1). MACiE can be accessed fro

O- vs. N-protonation of 1-dimethylaminonaphthalene-8-ketones: formation of a peri N–C bond or a hydrogen bond to the pi-electron density of a carbonyl group

X-ray crystallography and solid-state NMR measurements show that protonation of a series of 1-dimethylaminonaphthalene-8-ketones leads either to O protonation with formation of a long N–C bond (1.637–1.669 Å) between peri groups, or to N protonation and formation of a hydrogen bond to the π surface of the carbonyl group, the latter occurring for the larger ketone groups (C(O)R, R = t-butyl and phenyl). Solid state 15N MAS NMR studies clearly differentiate the two series, with the former yielding significantly more deshielded resonances. This is accurately corroborated by DFT calculation of the relevant chemical shift parameters. In the parent ketones X-ray crystallography shows that the nitrogen lone pair is directed towards the carbonyl group in all cases

Using Workflows to Explore and Optimise Named Entity Recognition for Chemistry

Chemistry text mining tools should be interoperable and adaptable regardless of system-level implementation, installation or even programming issues. We aim to abstract the functionality of these tools from the underlying implementation via reconfigurable workflows for automatically identifying chemical names. To achieve this, we refactored an established named entity recogniser (in the chemistry domain), OSCAR and studied the impact of each component on the net performance. We developed two reconfigurable workflows from OSCAR using an interoperable text mining framework, U-Compare. These workflows can be altered using the drag-&-drop mechanism of the graphical user interface of U-Compare. These workflows also provide a platform to study the relationship between text mining components such as tokenisation and named entity recognition (using maximum entropy Markov model (MEMM) and pattern recognition based classifiers). Results indicate that, for chemistry in particular, eliminating noise generated by tokenisation techniques lead to a slightly better performance than others, in terms of named entity recognition (NER) accuracy. Poor tokenisation translates into poorer input to the classifier components which in turn leads to an increase in Type I or Type II errors, thus, lowering the overall performance. On the Sciborg corpus, the workflow based system, which uses a new tokeniser whilst retaining the same MEMM component, increases the F-score from 82.35% to 84.44%. On the PubMed corpus, it recorded an F-score of 84.84% as against 84.23% by OSCAR