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Existing studies on BitTorrent systems are single-torrent based, while more than 85% of all peers participate in multiple torrents according to our trace analysis. In addition, these studies are not sufficiently insightful and accurate even for single-torrent models, due to some unrealistic assumptions. Our analysis of representative BitTorrent traffic provides several new findings regarding the limitations of BitTorrent systems: (1) Due to the exponentially decreasing peer arrival rate in reality, service availability in such systems becomes poor quickly, after which it is difficult for the file to be located and downloaded. (2) Client performance in the BitTorrent-like systems is unstable, and fluctuates widely with the peer population. (3) Existing systems could provide unfair services to peers, where peers with high downloading speed tend to download more and upload less. In this paper, we study these limitations on torrent evolution in realistic environments. Motivated by the analysis and modeling results, we further build a graph based multi-torrent model to study inter-torrent collaboration. Our model quantitatively provides strong motivation for inter-torrent collaboration instead of directly stimulating seeds to stay longer. We also discuss a system design to show the feasibility of multi-torrent collaboration.

This package of tools encompasses many of the common pieces of software required for the analysis of short read sequences produced by the Second Generation DNA sequencing machines. (eg. Illumina/Solexa sequencers, ABI SOLiD and 454). The focus of this project is on post-alignment analysis, thus the input for this process should be the files produced by sequence aligners such as MAQ, Eland or Exonerate. The output should be provided in several formats, including BED and WIG files which are readable by the UCSC Genome Browser.

For large amounts of data and more detailed analysis, we recommend you use our publicly-accessible MySQL server, ensembldb.ensembl.org, which you can access as user 'anonymous'. A second server, martdb.ensembl.org provides public access to the BioMart databases.

A fully developed set of DNA sequence assembly (Gap4), editing and analysis tools (Spin) for Unix, Linux, MacOSX and MS Windows.

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.

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).

The Bioinformatics Toolkit is a platform that integrates a great variety of tools for protein sequence analysis. Many tools are developed in-house, and serveral public tools are offered with extended functionality. The toolkit includes, among others: NucleotideBLAST, ProteinBLAST, PSI-BLAST, fastHMMER, HHsenser; ClustalW, MUSCLE, Mafft, ProbCons; HHrep, PCOILS, REPPER; Quick2D; HHpred, Modeller; CLANS, ANCESCON, PHYLIP; Reformat, RetrieveSeq, gi2promoter. For a short description of the tools, click the section tabs.

bioconductor.org Bioconductor is an open source and open development software project for the analysis and comprehension of genomic data.

A Knoppix / Debian variant tailored to numerical and quantitative analysis.

UCSF Chimera is a highly extensible program for interactive visualization and analysis of molecular structures and related data, including density maps, supramolecular assemblies, sequence alignments, docking results, trajectories, and conformational ensembles. High-quality images and animations can be generated. Chimera includes complete documentation and several tutorials, and can be downloaded free of charge for academic, government, non-profit, and personal use. Chimera is developed by the Resource for Biocomputing, Visualization, and Informatics and funded by the NIH National Center for Research Resources (grant P41-RR01081).

This package contains code for use with Short Read DNA Sequencing technologies, and includes packages for ChIP-Seq, Whole Transcriptome Shotgun Sequencing, Whole Genome Shotgun Sequencing, SNP Detection, Transcript expression and file conversion.

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