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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.

The Open Computer Vision Library has > 500 algorithms, documentation and sample code for real time computer vision. Tutorial documentation is in O'Reilly Book: Learning OpenCV http://www.amazon.com/Learning-OpenCV-Computer-Vision-Library/dp/0596516134

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]

OpenCV is an open source computer vision library originally developed by Intel. It is free for commercial and research use under a BSD license. The library is cross-platform, and runs on Mac OS X, Windows and Linux. It focuses mainly towards real-time image processing, as such, if it finds Intel's Integrated Performance Primitives on the system, it will use these commercial optimized routines to accelerate itself. This implementation is not a complete port of OpenCV. Currently, this library supports : * real-time capture * video file import * basic image treatment (brightness, contrast, threshold, …) * object detection (face, body, …) * blob detection Future versions will include more advanced functions such as motion analysis, object and color tracking, multiple OpenCV object instances … For more information about OpenCV visit the Open Source Computer Vision Library Intel webpage, the OpenCV Library Wiki, and the OpenCV Reference Manual (pdf).

With the following three steps, you can set up a Disco cluster in the Amazon's Elastic Computing Cloud. This will cost you a few dollars (or more, depending on your needs) but requires no resources on your side besides a single machine that you use to setup the cluster. In this setup Disco master and nodes run on EC2. Your Disco client can run either on the master node on EC2 or on a local machine.

Hadoop comes bundled with launch scripts to simplify initializing an Amazon Elastic Compute Cloud (EC2) cloud for Hadoop. Once initialized, running CloudBurst is identical to running on a local cluster. If you use EC2 regularly with the same datasets (i.e. the human genome as a reference), you will probably want to copy the data once to Amazon Simple Storage Service (S3) so you can quickly copy the data from S3 to your cloud at low cost.

What is WebcamStudio? Your own TV studio in your computer for broadcasting thru a virtual webcam. Mix multiple video source as webcams, movies, images, your desktop and log in your prefered video streaming site like Stikam or BlogTV and start your own show or video blog with: - Cool Special Effects - Text overlay - Video Source transition/rotation/movement... - Animations and Faces! - A webcam at your own image See the features! Why for GNU/Linux? Because there are no solution for Linux and Windows users already have acces to this kind of software. And mostly because I use a lot of Linux technologies that are not available under Microsoft Windows. (Sorry guys!) Based on... * Gstreamer libraries and plugins * gstreamer-java libraries * Java 6 (from Sun)

The Neuroscience Information Framework (NIF) is a dynamic inventory of web-based neurosciences data, resources, and tools that scientists and students can access via any computer connected to the Internet. An initiative of the NIH Blueprint for Neuroscience Research, the NIF will advance neuroscience research by enabling discovery and access to public research data and tools worldwide through an open source, networked environment.

SciPy (pronounced "Sigh Pie") is open-source software for mathematics, science, and engineering. It is also the name of a very popular conference on scientific programming with Python. The SciPy library depends on NumPy, which provides convenient and fast N-dimensional array manipulation. The SciPy library is built to work with NumPy arrays, and provides many user-friendly and efficient numerical routines such as routines for numerical integration and optimization. Together, they run on all popular operating systems, are quick to install, and are free of charge. NumPy and SciPy are easy to use, but powerful enough to be depended upon by some of the world's leading scientists and engineers. If you need to manipulate numbers on a computer and display or publish the results, give SciPy a try!

Our community guide allows you to set up your own MPI (Message Passing Interface) based supercomputer cluster with the Playstation 3. This guide was co-written by Gaurav Khanna, based on his previous work on the Gravity Grid and is a current run-time environment for the research of co-author (Chris Poulin), based on his current work in distributed pattern recognition. As such, we currently utilize the Fedora Core for this infrastructure and illustrate a "how-to" below. NOTE: We focus on the Fedora 8 distribution, due to prevalence of Fedora and its Cell SDK (3.0) compatibility. Finally, this content should be considered open source, and here is the license.