Author
Stephen J. O'Brien
Other affiliations: University College Cork, QIMR Berghofer Medical Research Institute, Newcastle University ...read more
Bio: Stephen J. O'Brien is an academic researcher from Saint Petersburg State University of Information Technologies, Mechanics and Optics. The author has contributed to research in topics: Population & Gene. The author has an hindex of 153, co-authored 1062 publications receiving 93025 citations. Previous affiliations of Stephen J. O'Brien include University College Cork & QIMR Berghofer Medical Research Institute.
Topics: Population, Gene, Genome, Locus (genetics), Gene mapping
Papers published on a yearly basis
Papers
More filters
••
Ludwig Maximilian University of Munich1, Heidelberg University2, French Institute of Health and Medical Research3, University of Bologna4, Gdańsk Medical University5, VU University Medical Center6, University of Barcelona7, Uppsala University8, Royal Liverpool University Hospital9, Instituto Português de Oncologia Francisco Gentil10, Hammersmith Hospital11, Academy of Medical Sciences, United Kingdom12, Helsinki University Central Hospital13, University of Newcastle14, Vilnius University15, National and Kapodistrian University of Athens16, University of Tartu17, Nicosia General Hospital18
TL;DR: It is concluded that patients enrolled in investigator-sponsored studies represent fairly well the general population of CML patients in Europe, with the exception of sex and age distribution, which may limit the value of the calculations of overall survival.
3 citations
Cited by
More filters
••
TL;DR: The results of an international collaboration to produce and make freely available a draft sequence of the human genome are reported and an initial analysis is presented, describing some of the insights that can be gleaned from the sequence.
Abstract: The human genome holds an extraordinary trove of information about human development, physiology, medicine and evolution. Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome. We also present an initial analysis of the data, describing some of the insights that can be gleaned from the sequence.
22,269 citations
28 Jul 2005
TL;DR: PfPMP1)与感染红细胞、树突状组胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作�ly.
Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1(PfPMP1)与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员,通过启动转录不同的var基因变异体为抗原变异提供了分子基础。
18,940 citations
•
TL;DR: It is suggested that the natural selection against large insertion/deletion is so weak that a large amount of variation is maintained in a population.
11,521 citations
••
TL;DR: This study has demonstrated that careful use of a shared control group represents a safe and effective approach to GWA analyses of multiple disease phenotypes; generated a genome-wide genotype database for future studies of common diseases in the British population; and shown that, provided individuals with non-European ancestry are excluded, the extent of population stratification in theBritish population is generally modest.
Abstract: There is increasing evidence that genome-wide association ( GWA) studies represent a powerful approach to the identification of genes involved in common human diseases. We describe a joint GWA study ( using the Affymetrix GeneChip 500K Mapping Array Set) undertaken in the British population, which has examined similar to 2,000 individuals for each of 7 major diseases and a shared set of similar to 3,000 controls. Case-control comparisons identified 24 independent association signals at P < 5 X 10(-7): 1 in bipolar disorder, 1 in coronary artery disease, 9 in Crohn's disease, 3 in rheumatoid arthritis, 7 in type 1 diabetes and 3 in type 2 diabetes. On the basis of prior findings and replication studies thus-far completed, almost all of these signals reflect genuine susceptibility effects. We observed association at many previously identified loci, and found compelling evidence that some loci confer risk for more than one of the diseases studied. Across all diseases, we identified a large number of further signals ( including 58 loci with single-point P values between 10(-5) and 5 X 10(-7)) likely to yield additional susceptibility loci. The importance of appropriately large samples was confirmed by the modest effect sizes observed at most loci identified. This study thus represents a thorough validation of the GWA approach. It has also demonstrated that careful use of a shared control group represents a safe and effective approach to GWA analyses of multiple disease phenotypes; has generated a genome-wide genotype database for future studies of common diseases in the British population; and shown that, provided individuals with non-European ancestry are excluded, the extent of population stratification in the British population is generally modest. Our findings offer new avenues for exploring the pathophysiology of these important disorders. We anticipate that our data, results and software, which will be widely available to other investigators, will provide a powerful resource for human genetics research.
9,244 citations
•
9,185 citations