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The genome-wide association study (GWAS) publications listed here include only those attempting to assay at least 100,000 single nucleotide polymorphisms (SNPs) in the initial stage. Publications are organized from most to least recent date of publication, indexing from online publication if available. Studies focusing only on candidate genes are excluded from this catalog. Studies are identified through weekly PubMed literature searches, daily NIH-distributed compilations of news and media reports, and occasional comparisons with an existing database of GWAS literature (HuGE Navigator). SNP-trait associations listed here are limited to those with p-values < 1.0 x 10-5. Note that we are now including all identified SNP-trait associations meeting this p-value threshhold. Multipliers of powers of 10 in p-values are rounded to the nearest single digit; odds ratios and allele frequencies are rounded to two decimals. Standard errors are converted to 95 percent confidence intervals where applicable. Allele frequencies, p-values, and odds ratios derived from the largest sample size, typically a combined analysis (initial plus replication studies), are recorded below if reported; otherwise statistics from the initial study sample are recorded. Odds ratios < 1 in the original paper are converted to OR > 1 for the alternate allele. Where results from multiple genetic models are available, we prioritized effect sizes (OR's or beta-coefficients) as follows: 1) genotypic model, per-allele estimate; 2) genotypic model, heterozygote estimate, 3) allelic model, allelic estimate. Gene regions corresponding to SNPs were identified from the UCSC Genome Browser. Gene names are those reported by the authors in the original paper. Only one SNP within a gene or region of high linkage disequilibrium is recorded unless there was evidence of independent association.

GenBioWiki is the student home page for the Genetics, Bioinformatics, and Computational Biology (GBCB) program at Virginia Tech. Bioinformatics and computational biology provide a research platform to acquire, manage, analyze, and display large amounts of data, which in turn catalyze a systems approach to understanding biological organisms, as well as making useful predictions about their behavior in response to environmental and other perturbations. Moreover, bioinformatics is the study of biological systems and large biological data sets using analytical methods borrowed from computer science, mathematics, statistics, and the physical sciences. This transdisciplinary approach to research requires graduates with extensive cross-cultural professional and technical training and provides ample employment opportunities for Ph.D. graduates. [1]

Welcome to the Gene Wiki portal. This portal is dedicated to the goal of applying community intelligence to the annotation of gene and protein function. The Gene Wiki is an informal collection of pages on human genes and proteins, and this effort to develop these pages is tightly coordinated with the Molecular and Cellular Biology Wikiproject. Our specific aims are summarized as follows: * To provide a well written and informative Wikipedia article for every notable human gene * To invite participation by interested lay editors, students, professionals, and academics from around the world * To integrate Gene Wiki articles with existing Wikipedia content through the use of internal wiki links increasing the value of both Please browse around the Gene Wiki, make an edit to your favorite gene page, and feel free to ask questions!

Sixty years of study have made Escherichia coli K-12 the most deeply understood organism at the molecular level. Much of what we know about cellular processes can be traced to fundamental discoveries in E. coli. In spite of its great importance as a model organism, information about E. coli is distributed among many online resources. EcoliHub uses web services that are being developed to make seamless bidirectional connections between E. coli resources, thereby enabling the full use of existing knowledge and supporting cutting-edge research into the molecular basis of life. Read More EcoliHub is being developed to serve the user community. Users can help teach us what is desirable in future releases by taking our User Survey.

Bowtie is an ultrafast, memory-efficient short read aligner. It aligns short DNA sequences (reads) to the human genome at a rate of 25 million reads per hour on a typical workstation with 2 gigabytes of memory. Bowtie indexes the genome with a Burrows-Wheeler index to keep its memory footprint small: 1.3 GB for the human genome. It supports alignment policies equivalent to Maq and SOAP but is much faster: about 35x faster than Maq and over 350x faster than SOAP when aligning to the human genome.

CloudBurst: Highly Sensitive Short Read Mapping with MapReduce Michael Schatz Center for Bioinformatics and Computational Biology, University of Maryland Next-generation DNA sequencing machines are generating an enormous amount of sequence data, placing unprecedented demands on traditional single-processor read mapping algorithms. CloudBurst is a new parallel read-mapping algorithm optimized for mapping next-generation sequence data to the human genome and other reference genomes, for use in a variety of biological analyses including SNP discovery, genotyping, and personal genomics. It is modeled after the short read mapping program RMAP, and reports either all alignments or the unambiguous best alignment for each read with any number of mismatches or differences. This level of sensitivity could be prohibitively time consuming, but CloudBurst uses the open-source Hadoop implementation of MapReduce to parallelize execution using multiple compute nodes. CloudBurst's running time scales linearly with the number of reads mapped, and with near linear speedup as the number of processors increases. In a 24-processor core configuration, CloudBurst is up to 30 times faster than RMAP executing on a single core, while computing an identical set of alignments. In a large remote compute clouds with 96 cores, CloudBurst reduces the running time from hours to mere minutes for typical jobs involving mapping of millions of short reads to the human genome. CloudBurst is available open-source as a model for parallelizing other bioinformatics algorithms with MapReduce.

WikiGenes is the first wiki system to combine the collaborative and largely altruistic possibilities of wikis with explicit authorship. In view of the extraordinary success of Wikipedia there remains no doubt about the potential of collaborative publishing, yet its adoption in science has been limited. Here I discuss a dynamic collaborative knowledge base for the life sciences that provides authors with due credit and that can evolve via continual revision and traditional peer review into a rigorous scientific