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WikiGenes - Collaborative Publishing

WikiGenes - Collaborative Publishing
Related:  molecular biology

Genome Browser Welcome | bioontology.org Q-value Software QVALUE Downloading: Features: This software takes a list of p-values resulting from the simultaneous testing of many hypotheses and estimates their q-values. A point-and-click interface is now available! The q-value of a test measures the proportion of false positives incurred (called the false discovery rate) when that particular test is called significant. References: Estimation Methodology: Storey JD. (2002) A direct approach to false discovery rates. Credits: QVALUE was written by Alan Dabney and John Storey.

Cell Signaling Technology BioSharing MDACC: Cancer Genomics: Tutorials Listed below are several introductory tutorials on microarray and SAGE related topics. Additional courses will be posted here as they are written. Analysis of Microarray Data Course material for the GSBS course "Analysis of Microarray Data". A Close Look at a Microarray Image Web introduction by Keith Baggerly Basic Analysis of a Single Microarray Web introduction by Kevin Coombes Analysis of SAGE Data; An Introduction PowerPoint talk presented in the MD Anderson Bioinformatics Workshop An Introduction to Sweave Pdf version of one talk given at the FDA in 2008.

National Center for Biotechnology Information Interpretome Load your genome file (upper-right corner) and choose some of the analyses above. Currently, only raw data files from 23andme and Lumigenix (unzipped) are supported. Sample genotype files (and a description of the individuals) can be found here. A detailed description of the website design and some of the modules can be found in our PSB paper as well as in blog posts here and here. Interpretome is intended for educational and research purposes only. No information should be considered diagnostic and as with any genetic testing service, the interpretation is not regulated by the FDA. How are my data kept private? Your genome will not be sent to any server, it remains on your computer. Your browser is NOT compatible with the Interpretome! Compatibility This website requires an HTML5 compatible browser, including current versions of: Google Chrome (≥ 6.0), the preferred browser Mozilla Firefox (≥ 4.0) Safari (≥ 6.0) RockMelt Citation Happy Exploring! -The interpreteam (About us)

BioMed Central | The Open Access Publisher This Week in Virology — A netcast about viruses – the kind that make you sick Genomes Pages The first completed genomes from viruses, phages and organelles were deposited into the EMBL Database in the early 1980's. Since then, molecular biology's shift to obtain the complete sequences of as many genomes as possible combined with major developments in sequencing technology resulted in hundreds of complete genome sequences being added to the database, including Archaea, Bacteria and Eukaryota. These web pages give access to a large number of complete genomes, help is available to describe the layout. Whole Genome Shotgun Sequences (WGS) Methods using whole genome shotgun data are used to gain a large amount of genome coverage for an organism. More information about WGS projects...

BioQUEST Curriculum Consortium | Biology Curriculum Development | Curriculum Resources IMP Bioinformatics Group The IMP-IMBA Bioinformatics group was established in August 2007 in recognition of the growing importance of computational biology in biomedical research. We offer inter-disciplinary expertise in biocomputing and information technology. Special thanks to the for their cooperation. Sequence Analysis A major aspect of our work is the functional and structural characterization of biological sequences in close cooperation with experimental partners. Due to the multitude of similar and complementary tools available for protein sequence analysis, it can be valuable to consider the predictions from many tools at once. Using meta-analysis of different prediction results one can typically derive far reaching conclusions that can not be obtained using one automatic procedures alone. Large Scale Data Sets Functional information on sequences are often stored in many individual databases.

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