http://www.vanhemert.co.uk Follow bits of Jano van Hemert's life. en-us http://www.vanhemert.co.uk/index.html#eDIKT2007 http://www.vanhemert.co.uk/index.html#eDIKT2007 presentationJano I. van Hemert, Jos Koetsier and Srihathai Prammanee 2007-12-04T09:00:00+00:00 We aim to build a portlet that allows developers and advanced users to create and deploy quickly job submission portlets. The portlet builder should allow specification of the parameters to their applications, and even allow parameter sweeps to be set up so as to do their in-silico experiments and sensitivity analyses. Job submission portlets will be deployed dynamically in the portal. Such a tool fits well in OMII-UK's portal support call, as it would speed up the deployment of portals that provide an interface to applications of end-users. http://www.vanhemert.co.uk/index.html#MicrosofteScience2007 http://www.vanhemert.co.uk/index.html#MicrosofteScience2007 presentationJano I. van Hemert, Douglas Armstrong and Malcolm Atkinson 2007-10-22T09:00:00+00:00 Research into animal and human health covers a vast array of biological components and functions. Yet strategies to simulate biological systems across multiple levels, by integrating many components and modelling their interaction, are largely undeveloped. We will explore how this challenge can be approached by considering how to build a virtual fly brain. This offers a new proving ground for collaboration between e-Scientists, biologists and neuroinformaticists. Mental Health accounts for 11% of global disease burden, it is growing rapidly yet it is one of the most challenging areas for drug discovery and development. Realistic models that capture the processes of the human brain would provide new insights into the diagnosis and treatment of certain disorders. However, to achieve this, we need to begin by working from much simpler models. The brain of the Drosophila contains in the region of 100,000 neurons; it provide perhaps the simplest brain capable of what we would consider complex behaviour, much of which offers insight into animal and human cognition. The genome was sequenced in 2000 and efforts to improve its functional annotation are highly integrated (www.flybase.org). Of the estimated 12,000 Drosophila genes, more than 2,000 are conserved in human disease indications. In order to bring together the many disciplines, the e-Science Institute of the UK has sponsored a theme to allow the establishment of programme with a point of focus for bioinformatics and neuroinformatics in Drosophila, such that gaps in the current databases, biological domain and modelling/simulation efforts can be identified and translated into new projects. In the context of e-Science, the project shall serve as a testbed for the new service oriented platform to enable a distributed data integration and data mining infrastructure, which will be developed in a European project. http://www.vanhemert.co.uk/index.html#EdinburghRIKEN2007 http://www.vanhemert.co.uk/index.html#EdinburghRIKEN2007 presentationJano I. van Hemert and Richard Baldock 2007-09-21T09:00:00+00:00 We introduce the Edinburgh Mouse Atlas and show several examples of the analyses now available to biologists on the spatio-temporal in-situ gene expression data. Then we move on to more advanced methodologies for extracting knowledge from these data. http://www.vanhemert.co.uk/index.html#BSASeminar2007 http://www.vanhemert.co.uk/index.html#BSASeminar2007 presentationJano I. van Hemert 2007-09-04T09:00:00+00:00 A new top down approach to extracting knowledge from the spatio-temporal atlas of gene expression patterns in the developing mouse embryo. http://www.vanhemert.co.uk/index.html#SysBioSeminar2007 http://www.vanhemert.co.uk/index.html#SysBioSeminar2007 presentationJano I. van Hemert 2007-05-24T09:00:00+00:00 We analyse data from the Edinburgh Mouse Atlas Gene-Expression Database (EMAGE) which is a high quality data source for spatio-temporal gene expression patterns. Using a novel process whereby generated patterns are used to probe spatially-mapped gene expression domains, we are able to get unbiased results as opposed to using annotations based predefined anatomy regions. We describe two processes to form association rules based on spatial configurations, one that associates spatial regions, the other associates genes. http://www.vanhemert.co.uk/index.html#DCCLunch2007 http://www.vanhemert.co.uk/index.html#DCCLunch2007 presentationJano I. van Hemert 2007-05-23T09:00:00+00:00 An overview of e-Science and the activities at the Edinburgh National e-Science Centre. http://www.vanhemert.co.uk/index.html#RAPID2007 http://www.vanhemert.co.uk/index.html#RAPID2007 grantJano van Hemert (PI), Jos Koetsier 2007-05-01T09:00:00+00:00 We aim to build a portlet that allows developers and advanced users to create and deploy quickly job submission portlets. The portlet builder should allow specification of the parameters to their applications, and even allow parameter sweeps to be set up so as to do their in-silico experiments and sensitivity analyses. Job submission portlets will be deployed dynamically in the portal. Such a tool fits well in OMII-UK's portal support call, as it would speed up the deployment of portals that provide an interface to applications of end-users. This project runs until 31 August 2008; funded through EPSRC it is worth GBP 201,760. http://www.vanhemert.co.uk/index.html#Ure2007 http://www.vanhemert.co.uk/index.html#Ure2007 inproceedingsJ. Ure and R. Proctor and M. Martone and D. Porteous and S. Lloyd and S. Lawrie and D. Job and R. Baldock and A. Philp and D. Liewald and F. Rakebrand and A. Blaikie and C. McKay and S. Anderson and J. Ainsworth and van Hemert, J. and I. Blanquer and R. Sinnott and C. Barillot and F. Bernard Gibaud and A. Williams and M. Hartswood and P. Watson and L. Smith and A. Burger and J. Kennedy and H. Gonzalez-Velez and R. Stevens and O. Coecho and R. Morton and P. Linksted and M. Deschenne and M. McGilchrist and P Johnson and A. Voss and R. Gertz and J. Wardlaw 2007-04-27T09:00:00+00:00 The paper documents a series of data integration workshops held in 2006 at the UK National e-Science Centre, summarizing a range of the problem/solution scenarios in multi-site and multi-scale data integration with six HealthGrid projects using schizophrenia as a domain-specific test case. It outlines emerging strategies, recommendations and objectives for collaboration on shared ontology-building and harmonization of data for multi-site trials in this domain. http://www.vanhemert.co.uk/index.html#EvoCOP2007 http://www.vanhemert.co.uk/index.html#EvoCOP2007 proceedingsCarlos Cotta and van Hemert, Jano 2007-04-11T09:00:00+00:00 Metaheuristics have often been shown to be effective for difficult combinatorial optimization problems appearing in various industrial, economical, and scientific domains. Prominent examples of metaheuristics are evolutionary algorithms, simulated annealing, tabu search, scatter search, memetic algorithms, variable neighborhood search, iterated local search, greedy randomized adaptive search procedures, estimation of distribution algorithms, and ant colony optimization. Successfully solved problems include scheduling, timetabling, network design, transportation and distribution, vehicle routing, the traveling salesman problem, satisfiability, packing and cutting, and general mixed integer programming. EvoCOP began in 2001 and has been held annually since then. It was the first event specifically dedicated to the application of evolutionary computation and related methods to combinatorial optimization problems. Originally held as a workshop, EvoCOP became a conference in 2004. The events gave researchers an excellent opportunity to present their latest research and to discuss current developments and applications as well as providing for improved interaction between members of this scientific community. Following the general trend of hybrid metaheuristics and diminishing boundaries between the different classes of metaheuristics, EvoCOP has broadened its scope over the last years and invited submissions on any kind of metaheuristic for combinatorial optimization. http://www.vanhemert.co.uk/index.html#EvoPhD2007 http://www.vanhemert.co.uk/index.html#EvoPhD2007 proceedingsMario Giacobini and van Hemert, Jano 2007-03-27T09:00:00+00:00 Evolutionary computation involves the study of problem-solving and optimization techniques inspired by principles of evolution and genetics. As any other scientific field, its success relies on the continuity provided by new researchers joining the field to help it progress. One of the most important sources for new researchers is the next generation of PhD students that are actively studying a topic relevant to this field. It is from this main observation the idea arose of providing a platform exclusively for PhD students. http://www.vanhemert.co.uk/index.html#HB2007 http://www.vanhemert.co.uk/index.html#HB2007 inproceedingsvan Hemert, J.I. and R.A. Baldock 2007-03-12T09:00:00+00:00 We analyse data from the Edinburgh Mouse Atlas Gene-Expression Database (EMAGE) which is a high quality data source for spatio-temporal gene expression patterns. Using a novel process whereby generated patterns are used to probe spatially-mapped gene expression domains, we are able to get unbiased results as opposed to using annotations based predefined anatomy regions. We describe two processes to form association rules based on spatial configurations, one that associates spatial regions, the other associates genes. http://www.vanhemert.co.uk/index.html#BIRD2007 http://www.vanhemert.co.uk/index.html#BIRD2007 presentationJ.I. van Hemert 2007-03-10T09:00:00+00:00 We analyse data from the Edinburgh Mouse Atlas Gene-Expression Database (EMAGE) which is a high quality data source for spatio-temporal gene expression patterns. Using a novel process whereby generated patterns are used to probe spatially-mapped gene expression domains, we are able to get unbiased results as opposed to using annotations based predefined anatomy regions. We describe two processes to form association rules based on spatial configurations, one that associates spatial regions, the other associates genes.