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Exposures in the period from conception to early childhood - including fetal growth, cell division, and organ functioning - may have long-lasting impact on health and disease susceptibility. To investigate these issues the Danish National Birth Cohort (Better health in generations) was established. A large cohort of pregnant women with long-term follow-up of the offspring was the obvious choice because many of the exposures of interest cannot be reconstructed with suffcient validity back in time. The study needed to be large, and the aim was to recruit 100,000 women early in pregnancy, and to continue follow-up for decades. Exposure information was collected by computer-assisted telephone interviews with the women twice during pregnancy and when their children were six and 18 months old. Participants were also asked to fill in a self-administered food frequency questionnaire in mid-pregnancy. Furthermore, a biological bank has been set up with blood taken from the mother twice during pregnancy and blood from theumbilical cord taken shortly after birth.
GESDB is a platform for sharing simulation data and discussion of simulation techniques for human genetic studies. The database contains simulation scripts, simulated data, and documentations from published manuscripts. The forum provides a platform for Q&A for the simulated data and exchanging simulation ideas. GESDB aims to promote transparency and efficiency in simulation studies for human genetic studies.
Older persons are often referred to physicians because of complaints of progressive difficulties in walking. The diagnostic and therapeutic approach to these patients is complex. Multiple physiologic subsystems may influence the ability to walk and no standard criteria are currently available to establish whether these subsystems are functioning within the “normal” range. To address lack of knowledge Dr. Luigi Ferrucci and Dr. Stefania Bandinelli conducted InCHIANTI, a representative population-based study of older persons living in the Chianti geographic area (Tuscany, Italy). The data collection started in September 1998 and was completed in March 2000. 3 and 6-year follow-up assessment of the InCHIANTI study population were performed in the years 2001-2003 and 2004-2006. A nine-year follow-up is already planned and funded through an NIA grant. The InCHIANTI Biobank is a collection of biological samples of the study population.
This site is dedicated to making high value health data more accessible to entrepreneurs, researchers, and policy makers in the hopes of better health outcomes for all. In a recent article, Todd Park, United States Chief Technology Officer, captured the essence of what the Health Data Initiative is all about and why our efforts here are so important.
The SICAS Medical Image Repository is a database for the management of medical images and subsequently generated models of the bony anatomy. The database will provide a framework for the integration of statistical shape models. This will contribute to less invasive procedures, e.g. by reduced radiation exposure, and it will enable patient specific implant design.
The Fungal Genetics Stock Center has preserved and distributed strains of genetically characterized fungi since 1960. The collection includes over 20,000 accessioned strains of classical and genetically engineered mutants of key model, human, and plant pathogenic fungi. These materials are distributed as living stocks to researchers around the world.
STOREDB is a platform for the archiving and sharing of primary data and outputs of all kinds, including epidemiological and experimental data, from research on the effects of radiation. It also provides a directory of bioresources and databases containing information and materials that investigators are willing to share. STORE supports the creation of a radiation research commons.
The European Prospective Investigation into Cancer and Nutrition (EPIC) study is one of the largest cohort studies in the world, with more than half a million (521 000) participants recruited across 10 European countries and followed for almost 15 years. EPIC was designed to investigate the relationships between diet, nutritional status, lifestyle and environmental factors, and the incidence of cancer and other chronic diseases. EPIC investigators are active in all fields of epidemiology, and important contributions have been made in nutritional epidemiology using biomarker analysis and questionnaire information, as well as genetic and lifestyle investigations.
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GAZEL is an open epidemiologic laboratory. Like major scientific instruments (telescopes or particle accelerators, for example, or genotyping laboratories equipped with sequencers), GAZEL was not constructed to answer a specific question. Instead it was designed to help analyze a wide range of scientific problems and is accessible to the community of researchers specializing in epidemiology. In accordance with its purpose as a scientific research platform, the GAZEL cohort is permanently open to epidemiologic research teams. Today, more than 50 projects on very diversified themes have been set up in GAZEL by some 20 teams, French, belonging to different bodies, and foreign (Germany, Belgium, Canada, Great Britain, Sweden, Finland, and USA).
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ALEXA is a microarray design platform for 'alternative expression analysis'. This platform facilitates the design of expression arrays for analysis of mRNA isoforms generated from a single locus by the use of alternative transcription initiation, splicing and polyadenylation sites. We use the term 'ALEXA' to describe a collection of novel genomic methods for 'alternative expression' analysis. 'Alternative expression' refers to the identification and quantification of alternative mRNA transcripts produced by alternative transcript initiation, alternative splicing and alternative polyadenylation. This website provides supplementary materials, source code and other downloads for recent publications describing our studies of alternative expression (AE). Most recently we have developed a method, 'ALEXA-Seq' and associated resources for alternative expression analysis by massively parallel RNA sequencing.