12 resultados para Canada--Discovery and exploration
em Aston University Research Archive
Resumo:
Visualising data for exploratory analysis is a major challenge in many applications. Visualisation allows scientists to gain insight into the structure and distribution of the data, for example finding common patterns and relationships between samples as well as variables. Typically, visualisation methods like principal component analysis and multi-dimensional scaling are employed. These methods are favoured because of their simplicity, but they cannot cope with missing data and it is difficult to incorporate prior knowledge about properties of the variable space into the analysis; this is particularly important in the high-dimensional, sparse datasets typical in geochemistry. In this paper we show how to utilise a block-structured correlation matrix using a modification of a well known non-linear probabilistic visualisation model, the Generative Topographic Mapping (GTM), which can cope with missing data. The block structure supports direct modelling of strongly correlated variables. We show that including prior structural information it is possible to improve both the data visualisation and the model fit. These benefits are demonstrated on artificial data as well as a real geochemical dataset used for oil exploration, where the proposed modifications improved the missing data imputation results by 3 to 13%.
Resumo:
The World Wide Web provides plentiful contents for Web-based learning, but its hyperlink-based architecture connects Web resources for browsing freely rather than for effective learning. To support effective learning, an e-learning system should be able to discover and make use of the semantic communities and the emerging semantic relations in a dynamic complex network of learning resources. Previous graph-based community discovery approaches are limited in ability to discover semantic communities. This paper first suggests the Semantic Link Network (SLN), a loosely coupled semantic data model that can semantically link resources and derive out implicit semantic links according to a set of relational reasoning rules. By studying the intrinsic relationship between semantic communities and the semantic space of SLN, approaches to discovering reasoning-constraint, rule-constraint, and classification-constraint semantic communities are proposed. Further, the approaches, principles, and strategies for discovering emerging semantics in dynamic SLNs are studied. The basic laws of the semantic link network motion are revealed for the first time. An e-learning environment incorporating the proposed approaches, principles, and strategies to support effective discovery and learning is suggested.
Resumo:
Illustrative extracts from the writings of Paul P. Ewald and of Max von Laue are presented. The latter in turn contains extensive text contributions from William Lawrence Bragg. These selections we have chosen so as to indicate the nature of the discovery of X-ray diffraction from crystals (experiments undertaken by Friedrich, Knipping and von Laue) and its early and prompt application in crystal structure analyses (by William Henry Bragg and William Lawrence Bragg). The platform for these discoveries was provided by a macroscopic physics problem dealt with by Ewald in his doctoral thesis with Arnold Sommerfeld in the Munich Physics Department, which is also where von Laue was based. W.L. Bragg was a student in Cambridge who used Trinity College Cambridge as his address on his early papers; experimental work was done by him in the Cavendish Laboratory, Cambridge, and also with his father, W.H. Bragg, in the Leeds University Physics Department. Of further historical interest is the award of an Honorary DSc (Doctor of Science) degree in 1936 to Max von Laue by the University of Manchester, UK, while William Lawrence Bragg was Langworthy Professor of Physics there. © 2012 Copyright Taylor and Francis Group, LLC.
Resumo:
Genomics, proteomics and metabolomics are three areas that are routinely applied throughout the drug-development process as well as after a product enters the market. This review discusses all three 'omics, reporting on the key applications, techniques, recent advances and expectations of each. Genomics, mainly through the use of novel and next-generation sequencing techniques, has advanced areas of drug discovery and development through the comparative assessment of normal and diseased-state tissues, transcription and/or expression profiling, side-effect profiling, pharmacogenomics and the identification of biomarkers. Proteomics, through techniques including isotope coded affinity tags, stable isotopic labeling by amino acids in cell culture, isobaric tags for relative and absolute quantification, multidirectional protein identification technology, activity-based probes, protein/peptide arrays, phage displays and two-hybrid systems is utilized in multiple areas through the drug development pipeline including target and lead identification, compound optimization, throughout the clinical trials process and after market analysis. Metabolomics, although the most recent and least developed of the three 'omics considered in this review, provides a significant contribution to drug development through systems biology approaches. Already implemented to some degree in the drug-discovery industry and used in applications spanning target identification through to toxicological analysis, metabolic network understanding is essential in generating future discoveries.
Resumo:
Genomics, proteomics and metabolomics are three areas that are routinely applied throughout the drug-development process as well as after a product enters the market. This review discusses all three 'omics, reporting on the key applications, techniques, recent advances and expectations of each. Genomics, mainly through the use of novel and next-generation sequencing techniques, has advanced areas of drug discovery and development through the comparative assessment of normal and diseased-state tissues, transcription and/or expression profiling, side-effect profiling, pharmacogenomics and the identification of biomarkers. Proteomics, through techniques including isotope coded affinity tags, stable isotopic labeling by amino acids in cell culture, isobaric tags for relative and absolute quantification, multidirectional protein identification technology, activity-based probes, protein/peptide arrays, phage displays and two-hybrid systems is utilized in multiple areas through the drug development pipeline including target and lead identification, compound optimization, throughout the clinical trials process and after market analysis. Metabolomics, although the most recent and least developed of the three 'omics considered in this review, provides a significant contribution to drug development through systems biology approaches. Already implemented to some degree in the drug-discovery industry and used in applications spanning target identification through to toxicological analysis, metabolic network understanding is essential in generating future discoveries.
Resumo:
Imaging using MS has the potential to deliver highly parallel, multiplexed data on the specific localization of molecular ions in tissue samples directly, and to measure and map the variations of these ions during development and disease progression or treatment. There is an intrinsic potential to be able to identify the biomarkers in the same experiment, or by relatively simple extension of the technique. Unlike many other imaging techniques, no a priori knowledge of the markers being sought is necessary. This review concentrates on the use of MALDI-MS for MS imaging (MSI) of proteins and peptides, with an emphasis on mammalian tissue. We discuss the methodologies used, their potential limitations, overall experimental considerations and progress that has been made towards establishing MALDI-MSI as a routine technique for the spatially resolved measurement of peptides and proteins. As well as determining the local abundance of individual molecular ions, there is the potential to determine their identity within the same experiment using relatively simple extensions of the basic techniques. In this way MSI offers an important opportunity for biomarker discovery and identification.
Resumo:
There has been a recent explosion of interest in Lesbian, Gay, Bisexual and Trans Perspective Psychology amongst students and academics, and this interest is predicted to continue to rise. Recent media debates on subjects such as same–sex marriage have fuelled interest in LGBTQ perspectives. This edited collection showcases the latest thinking in LGBTQ psychology. The book has 21 chapters covering subjects such as same sex parenting, outing, young LGBTQ people, sport, learning disabilities, lesbian and gay identities etc. The book has an international focus, with contributors from UK, US, Canada, Australia and New Zealand List of Contributors. Foreword by Jerry J. Bigner. 1. Introducing Out in Psychology (Victoria Clarke and Elizabeth Peel). 2. From lesbian and gay psychology to LGBTQ psychologies: A journey into the unknown (Victoria Clarke and Elizabeth Peel) 3. What comes after discourse analysis for LGBTQ psychology(Peter Hegarty). 4. Recognising race in LGBTQ psychology: Power, privilege and complicity (Damien W. Riggs). 5. Personality, individual differences and LGB psychology (Gareth Hagger Johnson). 6. Heteronormativity and the exclusion of bisexuality in psychology (Meg Barker). 7. A minority within a minority: Experiences of gay men with intellectual disabilities.(Christopher Bennett and Adrian Coyle). 8. Closet talk: The contemporary relevance of the closet in lesbian and gay interaction (Victoria Land and Celia Kitzinger) 9. Romance, rights, recognition, responsibilities and radicalism: Same-sex couples’ accounts of civil partnership and marriage (Victoria Clarke, Carole Burgoyne and Maree Burns). 10. The experience of social power in the lives of trans people (Clair Clifford and Jim Orford). 11. What do they look like and are they among us? Bisexuality, (dis.closure and (Maria Gurevich, Jo Bower, Cynthia M. Mathieson and Bramilee Dhayanandhan). 12. Heterosexism at work: Diversity training, discrimination law and the limits of liberal individualism (Rosie Harding and Elizabeth Peel). 13. Out on the ball fields: Lesbians in sport (Vikki Krane and Kerrie J. Kauer). 14. Homophobia, rights and community: Contemporary issues in the lives of LGB people in the UK (Sonja J. Ellis). 15. Striving for holistic success: How lesbians come out on top (Faith Rostad and Bonita C. Long). 16. On Passing: The Interactional Organization of Appearance Attributions in the Psychiatric Assessment of Transsexual Patients (Susan A. Speer and Richard Green). 17. Alcohol and gay men: Consumption, promotion and policy responses (Jeffrey Adams, Timothy McCreanor and Virginia Braun). 18. Towards a clinical-psychological approach to address the hetero sexual concerns of intersexed women (Lih-Mei Liao). 19. Educational psychology practice with LGB youth in schools: Individual and institutional interventions (Jeremy J. Monsen and Sydney Bailey). 20. Que(e)rying the meaning of lesbian health: Individual(izing and community discourses (Sara MacBride-Stewart). 21. Transsexualism: Diagnostic dilemmas, transgender politics and the future of transgender care (Katherine Johnson). Index.
Resumo:
We introduce a flexible visual data mining framework which combines advanced projection algorithms from the machine learning domain and visual techniques developed in the information visualization domain. The advantage of such an interface is that the user is directly involved in the data mining process. We integrate principled projection algorithms, such as generative topographic mapping (GTM) and hierarchical GTM (HGTM), with powerful visual techniques, such as magnification factors, directional curvatures, parallel coordinates and billboarding, to provide a visual data mining framework. Results on a real-life chemoinformatics dataset using GTM are promising and have been analytically compared with the results from the traditional projection methods. It is also shown that the HGTM algorithm provides additional value for large datasets. The computational complexity of these algorithms is discussed to demonstrate their suitability for the visual data mining framework. Copyright 2006 ACM.
Resumo:
G-protein coupled receptors (GPCRs) constitute the largest class of membrane proteins and are a major drug target. A serious obstacle to studying GPCR structure/function characteristics is the requirement to extract the receptors from their native environment in the plasma membrane, coupled with the inherent instability of GPCRs in the detergents required for their solubilization. In the present study, we report the first solubilization and purification of a functional GPCR [human adenosine A
Resumo:
The evaluation of geospatial data quality and trustworthiness presents a major challenge to geospatial data users when making a dataset selection decision. The research presented here therefore focused on defining and developing a GEO label – a decision support mechanism to assist data users in efficient and effective geospatial dataset selection on the basis of quality, trustworthiness and fitness for use. This thesis thus presents six phases of research and development conducted to: (a) identify the informational aspects upon which users rely when assessing geospatial dataset quality and trustworthiness; (2) elicit initial user views on the GEO label role in supporting dataset comparison and selection; (3) evaluate prototype label visualisations; (4) develop a Web service to support GEO label generation; (5) develop a prototype GEO label-based dataset discovery and intercomparison decision support tool; and (6) evaluate the prototype tool in a controlled human-subject study. The results of the studies revealed, and subsequently confirmed, eight geospatial data informational aspects that were considered important by users when evaluating geospatial dataset quality and trustworthiness, namely: producer information, producer comments, lineage information, compliance with standards, quantitative quality information, user feedback, expert reviews, and citations information. Following an iterative user-centred design (UCD) approach, it was established that the GEO label should visually summarise availability and allow interrogation of these key informational aspects. A Web service was developed to support generation of dynamic GEO label representations and integrated into a number of real-world GIS applications. The service was also utilised in the development of the GEO LINC tool – a GEO label-based dataset discovery and intercomparison decision support tool. The results of the final evaluation study indicated that (a) the GEO label effectively communicates the availability of dataset quality and trustworthiness information and (b) GEO LINC successfully facilitates ‘at a glance’ dataset intercomparison and fitness for purpose-based dataset selection.
Resumo:
The IUPHAR database (IUPHAR-DB) integrates peer-reviewed pharmacological, chemical, genetic, functional and anatomical information on the 354 nonsensory G protein-coupled receptors (GPCRs), 71 ligand-gated ion channel subunits and 141 voltage-gated-like ion channel subunits encoded by the human, rat and mouse genomes. These genes represent the targets of approximately one-third of currently approved drugs and are a major focus of drug discovery and development programs in the pharmaceutical industry. IUPHAR-DB provides a comprehensive description of the genes and their functions, with information on protein structure and interactions, ligands, expression patterns, signaling mechanisms, functional assays and biologically important receptor variants (e.g. single nucleotide polymorphisms and splice variants). In addition, the phenotypes resulting from altered gene expression (e.g. in genetically altered animals or in human genetic disorders) are described. The content of the database is peer reviewed by members of the International Union of Basic and Clinical Pharmacology Committee on Receptor Nomenclature and Drug Classification (NC-IUPHAR); the data are provided through manual curation of the primary literature by a network of over 60 subcommittees of NC-IUPHAR. Links to other bioinformatics resources, such as NCBI, Uniprot, HGNC and the rat and mouse genome databases are provided. IUPHAR-DB is freely available at http://www.iuphar-db.org. © 2008 The Author(s).
Resumo:
This book constitutes the revised selected papers from the 10th Global Sourcing Workshop held in Val d’Isère, France, in February 2016. The 11 papers presented in this volume were carefully reviewed and selected from 47 submissions. The book offers a review of the key topics in outsourcing and offshoring of information technology and business services offering practical frameworks that serve as a tool kit to students and managers. The range of topics covered is wide and diverse, but predominately focused on how to achieve success in shared services and outsourcing. More specifically, the book examines outsourcing decisions and management practices, giving specific attention to shared services that have become one of the dominant sourcing models. The topics discussed combine theoretical and practical insights regarding challenges that industry leaders, policy makers, and professionals face or should be concerned with. Case studies from various organizations, industries and countries such as UK, Italy, The Netherlands, Canada, Australia and Denmark complete the book.