31 resultados para Manuscript maps.
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Resumo:
A combination of linkage analyses and association studies are currently employed to promote the identification of genetic factors contributing to inherited renal disease. We have standardized and merged complex genetic data from disparate sources, creating unique chromosomal maps to enhance genetic epidemiological investigations. This database and novel renal maps effectively summarize genomic regions of suggested linkage, association, or chromosomal abnormalities implicated in renal disease. Chromosomal regions associated with potential intermediate clinical phenotypes have been integrated, adding support for particular genomic intervals. More than 500 reports from medical databases, published scientific literature, and the World Wide Web were interrogated for relevant renal-related information. Chromosomal regions highlighted for prioritized investigation of renal complications include 3q13-26, 6q22-27, 10p11-15, 16p11-13, and 18q22. Combined genetic and physical maps are effective tools to organize genetic data for complex diseases. These renal chromosome maps provide insights into renal phenotype-genotype relationships and act as a template for future genetic investigations into complex renal diseases. New data from individual researchers and/or future publications can be readily incorporated to this resource via a user-friendly web-form accessed from the website: www.qub.ac.uk/neph-res/CORGI/index.php.
Resumo:
We provide an explicit formula which gives natural extensions of piecewise monotonic Markov maps defined on an interval of the real line. These maps are exact endomorphisms and define chaotic discrete dynamical systems.
Resumo:
Purpose: To use preferential hyperacuity perimetry to obtain a quantitative measure of central visual field distortion that would aid in the monitoring of functional responsiveness to ranibizumab treatment.
Resumo:
Aims To investigate secular trends in the incidence of Type 1 diabetes in Northern Ireland over the period 1989-2003. To highlight geographical variations in the incidence of Type 1 diabetes by producing disease maps and to compare incidence rates by relevant area characteristics.