Publications
46 results found
Tomlinson CD, Barton GR, Woodbridge M, et al., 2013, XperimentR: painless annotation of a biological experiment for the laboratory scientist, Bmc Bioinformatics
Harries P, Tomlinson CD, 2012, Teaching young dogs new tricks: improving occupational therapists' referral prioritization capacity with a web-based decision-training aid, Scandinavian Journal of Occupational Therapy
Thomas G, Unger K, Krznaric M, et al., 2012, The Chernobyl Tissue Bank - A Repository for Biomaterial and Data Used in Integrative and Systems Biology Modeling the Human Response to Radiation, Genes, Vol: 3, Pages: 278-290, ISSN: 2073-4425
The only unequivocal radiological effect of the Chernobyl accident on human health is the increase in thyroid cancer in those exposed in childhood or early adolescence. In response to the scientific interest in studying the molecular biology of thyroid cancer post Chernobyl, the Chernobyl Tissue Bank (CTB: www.chernobyltissuebank.com) was established in 1998. Thus far it is has collected biological samples from 3,861 individuals, and provided 27 research projects with 11,254 samples. The CTB was designed from its outset as a resource to promote the integration of research and clinical data to facilitate a systems biology approach to radiation related thyroid cancer. The project has therefore developed as a multidisciplinary collaboration between clinicians, dosimetrists, molecular biologists and bioinformaticians and serves as a paradigm for tissue banking in the omics era.
Woodbridge M, Tomlinson CD, Butcher S, 2012, ADAM: Automated Data Management for research datasets, Bioinformatics
Harries P, Tomlinson CD, Notley E, et al., 2012, Effectiveness of a decision-training aid on referral prioritization capacity: a randomized controlled trial, Journal of Medical Decision Making
Harries P, Tomlinson CD, Notley E, 2011, Randomized controlled trial to test the effectiveness of a referral prioritization decision training tool for student occupational therapists, Higher Education Academy conference
Barton G, Abbott J, Chiba N, et al., 2008, EMAAS: An extensible grid-based Rich Internet Application for microarray data analysis and management, BMC Bioinformatics, Vol: 9, ISSN: 1471-2105
BackgroundMicroarray experimentation requires the application of complex analysis methods as well as the use of non-trivial computer technologies to manage the resultant large data sets. This, together with the proliferation of tools and techniques for microarray data analysis, makes it very challenging for a laboratory scientist to keep up-to-date with the latest developments in this field. Our aim was to develop a distributed e-support system for microarray data analysis and management.ResultsEMAAS (Extensible MicroArray Analysis System) is a multi-user rich internet application (RIA) providing simple, robust access to up-to-date resources for microarray data storage and analysis, combined with integrated tools to optimise real time user support and training. The system leverages the power of distributed computing to perform microarray analyses, and provides seamless access to resources located at various remote facilities. The EMAAS framework allows users to import microarray data from several sources to an underlying database, to pre-process, quality assess and analyse the data, to perform functional analyses, and to track data analysis steps, all through a single easy to use web portal. This interface offers distance support to users both in the form of video tutorials and via live screen feeds using the web conferencing tool EVO. A number of analysis packages, including R-Bioconductor and Affymetrix Power Tools have been integrated on the server side and are available programmatically through the Postgres-PLR library or on grid compute clusters. Integrated distributed resources include the functional annotation tool DAVID, GeneCards and the microarray data repositories GEO, CELSIUS and MiMiR. EMAAS currently supports analysis of Affymetrix 3' and Exon expression arrays, and the system is extensible to cater for other microarray and transcriptomic platforms.ConclusionEMAAS enables users to track and perform microarray data management and analysis tasks through
Tomlinson C, Thimma M, Alexandrakis S, et al., 2008, MiMiR - an integrated platform for microarray data sharing, mining and analysis, BMC Bioinformatics, Vol: 9, Pages: 1-11, ISSN: 1471-2105
BackgroundDespite considerable efforts within the microarray community for standardising data format, content and description, microarray technologies present major challenges in managing, sharing, analysing and re-using the large amount of data generated locally or internationally. Additionally, it is recognised that inconsistent and low quality experimental annotation in public data repositories significantly compromises the re-use of microarray data for meta-analysis. MiMiR, the Mi croarray data Mi ning R esource was designed to tackle some of these limitations and challenges. Here we present new software components and enhancements to the original infrastructure that increase accessibility, utility and opportunities for large scale mining of experimental and clinical data.ResultsA user friendly Online Annotation Tool allows researchers to submit detailed experimental information via the web at the time of data generation rather than at the time of publication. This ensures the easy access and high accuracy of meta-data collected. Experiments are programmatically built in the MiMiR database from the submitted information and details are systematically curated and further annotated by a team of trained annotators using a new Curation and Annotation Tool. Clinical information can be annotated and coded with a clinical Data Mapping Tool within an appropriate ethical framework. Users can visualise experimental annotation, assess data quality, download and share data via a web-based experiment browser called MiMiR Online. All requests to access data in MiMiR are routed through a sophisticated middleware security layer thereby allowing secure data access and sharing amongst MiMiR registered users prior to publication. Data in MiMiR can be mined and analysed using the integrated EMAAS open source analysis web portal or via export of data and meta-data into Rosetta Resolver data analysis package.ConclusionThe new MiMiR suite of software enables systematic and effective c
Tomlinson CD, Alexandrakis S, Chiba N, et al., 2007, MiMiR : A Flexible Microarray Data Warehouse for the Rat Community, Rat Genomics and Models
Swierzbinski J, Tomlinson CD, Binmore K, 2007, An Experimental Test of Rubinstein’s Bargaining Model
This paper offers an experimental test of a version of Rubinstein’s bargaining model in which the players’ discount factors are unequal. We find that learning, rationality, and fairnessare all significant in determining the outcome. In particular, we find that a model of myopic optimization over time predictsthe sign of deviations in the opening proposal from the finalundiscounted agreement in the previous period rather well. Toexplain the amplitude of the deviations, we then successfully fita perturbed version of the model of myopic adjustment to the data that allows for a bias toward refusing inequitable offers.
Harries P, Gilhooley K, Tomlinson CD, et al., 2006, Training Decision Making in Novices; A website to develop skills in referral prioritisation, European Medical Decision Making Conference
Binmore K, Swierzbinski J, Tomlinson CD, et al., 2005, An Experimental Comparison of Bidding and Entry in the Sealed-Bid (Dutch) and Open (English) Versions of Vickrey's Asymmetric Auction, ELSE conference in honor of Ken Binmore
Harries P, Tomlinson CD, Harries C, 2005, Focussing on occupation; a tool to guide novices in community mental health teams, 29th Annual Conference of the College of Occupational Therapy National Conference
Fountain TJ, Duff MJB, Crawley DG, et al., 1998, The Use of Nanoelectronic Devices in Highly-Parallel Computing System, IEEE Transactions on VLSI Systems, Vol: 6, Pages: 31-38
Tomlinson CD, Crawley DG, Fountain TJ, 1996, The Effect of Nanowire Limitations on Massively Parallel Computer Architectures, Nanowires – Proc NATO Advanced Research Workshop, Pages: 399-407
Fountain TJ, Tomlinson CD, 1995, The propagated instruction processor, Proceedings of the 6th British conference on Machine vision, Pages: 563-572
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