The remarkable progress in characterizing the human genome sequence, exemplified by the Human Genome Project and the HapMap Consortium, has led to the perception that knowledge and the tools (e.g., microarrays) are sufficient for many if not most biomedical research efforts. A large amount of data from diverse studies proves this perception inaccurate at best, and at worst, an impediment for further efforts to characterize the variation in the human genome. Since variation in genotype and environment are the fundamental basis to understand phenotypic variability and heritability at the population level, identifying the range of human genetic variation is crucial to the development of personalized nutrition and medicine. The Human Variome Project (HVP; http://www.humanvariomeproject.org/) was proposed initially to systematically collect mutations that cause human disease and create a cyber infrastructure to link locus specific databases (LSDB). We report here the discussions and recommendations from the 2008 HVP planning meeting held in San Feliu de Guixols, Spain, in May 2008.
SummaryThis paper presents a novel bioinformatics data warehouse software kit that integrates biological information from multiple public life science data sources into a local database management system. It stands out from other approaches by providing up-to-date integrated knowledge, platform and database independence as well as high usability and customization. This open source software can be used as a general infrastructure for integrative bioinformatics research and development. The advantages of the approach are realized by using a Java-based system architecture and object-relational mapping (ORM) technology. Finally, a practical application of the system is presented within the emerging area of medical bioinformatics to show the usefulness of the approach. The BioDWH data warehouse software is available for the scientific community at http: //sourceforge.net/projects/biodwh/.
RAMEDIS is a manually curated resource of human variations and corresponding phenotypes for rare metabolic diseases. The system is based on separate case reports that comprehensively describe various aspects of anonymous case study, e.g. molecular genetics, symptoms, lab findings, treatments, etc. Scientists are able to make use of the database by a simple and intuitive web-based user interface with a common web browser. A registration or login is not necessary for a full reading access to the system content. Furthermore, a mutation analysis table summarizes the submitted variations per diagnosis and enables direct access to detailed information of corresponding case reports. Interested scientists may open an account to submit their case reports in order to share valuable genotype-phenotype information efficiently with the scientific community. Currently, 794 case reports have been submitted, describing 92 different genetic metabolic diseases. To enhance the comprehensive coverage of available knowledge in the field of rare metabolic diseases, all case reports are linked to integrated information from public molecular biology databases like KEGG, OMIM and ENZYME. This information upgrades the case reports by related data of the corresponding diseases as well as involved enzymes, genes and metabolic pathways. Academic users may freely use the RAMEDIS system at http://www.ramedis.de.
Control of cell proliferation, differentiation, activation and cell removal is crucial for the development and existence of multi-cellular organisms. Apoptosis, or programmed cell death, is a major control mechanism by which cells die and is also important in controlling cell number and proliferation as part of normal development. Molecular networks that regulate these processes are critical targets for drug development, gene therapy, and metabolic engineering. The molecular interactions involved in this and other processes are analyzed and annotated by experts and stored as data in different databases. The key task is to integrate, manage and visualize these data available from different sources and present them in a user-comprehensible manner.Here we present VINEdb, a data warehouse developed to interact with and to explore integrated life science data. Extendable open source data warehouse architecture enables platform-independent usability of the web application and the underlying infrastructure. A high degree of transparency and up-to-dateness is ensured by a monitor component to control and update the data from the sources. Furthermore, the system is supported by a visualization component to allow interactive graphical exploration of the integrated data. We will use apoptotic pathway and caspase-3 as a case study to show capability and usability of our approach. VINEdb is available at http://tunicata.techfak.unibielefeld.de/VINEdb/.
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