BackgroundVegetables of the genus Allium are widely consumed but remain poorly understood genetically. Genetic mapping has been conducted in intraspecific crosses of onion (Allium cepa L.), A. fistulosum and interspecific crosses between A. roylei and these two species, but it has not been possible to access genetic maps and underlying data from these studies easily.DescriptionAn online comparative genomics database, AlliumMap, has been developed based on the GMOD CMap tool at http://alliumgenetics.org. It has been populated with curated data linking genetic maps with underlying markers and sequence data from multiple studies. It includes data from multiple onion mapping populations as well as the most closely related species A. roylei and A. fistulosum. Further onion EST-derived markers were evaluated in the A. cepa x A. roylei interspecific population, enabling merging of the AFLP-based maps. In addition, data concerning markers assigned in multiple studies to the Allium physical map using A. cepa-A. fistulosum alien monosomic addition lines have been compiled. The compiled data reveal extensive synteny between onion and A. fistulosum.ConclusionsThe database provides the first online resource providing genetic map and marker data from multiple Allium species and populations. The additional markers placed on the interspecific Allium map confirm the value of A. roylei as a valuable bridge between the genetics of onion and A. fistulosum and as a means to conduct efficient mapping of expressed sequence markers in Allium. The data presented suggest that comparative approaches will be valuable for genetic and genomic studies of onion and A. fistulosum. This online resource will provide a valuable means to integrate genetic and sequence-based explorations of Allium genomes.

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of a thesis submitted in partial fulfilment of the requirements for the Degree of Doctor of Philosophy in Software and Information Technology Designing a Framework for End User Applications by Yanbo DengEnd user developers (i.e. non-professional developers) often create database applications to meet their immediate needs. However, these applications can often be difficult to generalise or adapt when requirements inevitably change. As part of this thesis, we visited several research institutions to investigate the issues of end user developed databases. We found that different user groups in the same organisation might require similar, but different, data management applications. However, the very specific designs used in most of these systems meant it was difficult to adapt them for other similar uses.In this thesis we propose a set of guidelines for supporting end user developers to create more flexible and adaptable data management applications. Our approach involves professional and end user developers working together to find a "middle way" between very specific and very generic designs. We propose a framework solution that allows the data model to have several co-existing variations which can satisfy the requirements of different user groups in a common domain. A "framework provider" (IT professional) will create the initial framework and data model. Configuration tools are then provided for a "framework manager" to easily customise the model to the specific needs of various user groups. The system also provides client toolkits and application generators to help end user developers (EUDs) to quickly create and customise applications based on the framework.The framework approach was applied to a case study involving a Laboratory Information Management System (LIMS) for data on research experiments. We demonstrated that the framework developed could be successfully applied to several groups working in the same domain and could be extended to include new or changed requirements.We also evaluated the framework through software trials at several research organisations. All participants successfully used the configuration tools to extend the LIMS framework within an average of 40 minutes. EUDs were also able to easily create basic applications within an average of 25 minutes. The overall feedback was that the framework approach was a useful and efficient way to create adaptable data management applications. More importantly, ii participants were able to immediately see how the framework could be applied to their own laboratory data.