<?xml version='1.0'?><rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:georss="http://www.georss.org/georss" xmlns:atom="http://www.w3.org/2005/Atom" >
<channel>
	<title><![CDATA[BOL: All site bookmarks]]></title>
	<link>https://bioinformaticsonline.com/bookmarks/all?offset=1250</link>
	<atom:link href="https://bioinformaticsonline.com/bookmarks/all?offset=1250" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/18021/junk-part-of-the-human-genome-unlocked</guid>
	<pubDate>Thu, 09 Oct 2014 12:22:20 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/18021/junk-part-of-the-human-genome-unlocked</link>
	<title><![CDATA[Junk part of the human genome unlocked]]></title>
	<description><![CDATA[<p><strong>More</strong>:</p>
<p><strong>Texas A&amp;M Biologists Unlock Non-Coding Half of Human Genome with Novel DNA Sequencing Technique</strong></p>
<p><a href="http://www.science.tamu.edu/news/story.php?story_ID=1282#.VDbBQ_mSyyA">http://www.science.tamu.edu/news/story.php?story_ID=1282#.VDbBQ_mSyyA</a></p>
<p>"<em>this study stated that differences in the heterochromatin exist ; the junk DNA is not stagnant as researchers originally had believed </em>"</p>
<p><strong>Simple Quantitative PCR Approach to Reveal Naturally Occurring and Mutation-Induced Repetitive Sequence Variation on the Drosophila Y Chromosome</strong></p>
<p>Link :<a href="http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0109906">http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0109906</a></p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="http://www.sciencedaily.com/releases/2014/10/141007091753.htm" rel="nofollow">http://www.sciencedaily.com/releases/2014/10/141007091753.htm</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/17946/7th-international-conference-on-bioinformatics-and-computational-biology-bicob</guid>
	<pubDate>Mon, 06 Oct 2014 16:19:36 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/17946/7th-international-conference-on-bioinformatics-and-computational-biology-bicob</link>
	<title><![CDATA[7th International Conference on Bioinformatics and Computational Biology (BICoB)]]></title>
	<description><![CDATA[<p><span>In recent years, computational biology and medical informatics have seen significant advances driven by computational techniques in bioinformatics making bioinformatics and computational biology among the most vibrant research areas. The 7th international conference on Bioinformatics and Computational Biology (BICoB-2015) provides an excellent venue for researchers and practitioners in the fields of bioinformatics and computational biology to present and publish their research results and techniques. The BICoB conference seeks original and high quality papers in the fields of bioinformatics, computational biology, systems biology, medical informatics and the related disciplines. </span><span>We also encourage work in progress and research results in the emerging and evolutionary computational areas. Computational techniques have already enabled unprecedented advances in modern biology and medicine. Work in the computational methods related to, or with application in, bioinformatics is also encouraged including: data mining, text mining, machine learning, modeling and simulation, pattern recognition, data visualization, biostatistics, .etc. The topics of interest include (and are not limited to):&nbsp;</span><br><strong><span>Genome analysis:</span></strong><span>&nbsp;Genome assembly, genome annotation, gene finding, alternative splicing, EST analysis and comparative genomics.&nbsp;</span><br><strong><span>Sequence analysis:</span></strong><span>&nbsp;Multiple sequence alignment, sequence search and clustering, function prediction, motif discovery, functional site recognition in protein, RNA and DNA sequences.&nbsp;</span><br><strong><span>Phylogenetics:</span></strong><span>&nbsp;Phylogeny estimation, models of evolution, comparative biological methods, population genetics.&nbsp;</span><br><strong><span>Structural Bioinformatics:</span></strong><span>&nbsp;Structure matching, prediction, analysis and comparison; methods and tools for docking; protein design&nbsp;</span><br><strong><span>Analysis of high-throughput biological data:</span></strong><span>&nbsp;Microarrays (nucleic acid, protein, array CGH, genome tiling, and other arrays), EST, SAGE, MPSS, proteomics, mass spectrometry.&nbsp;</span><br><strong><span>Genetics and population analysis:</span></strong><span>&nbsp;Linkage analysis, association analysis, population simulation, haplotyping, marker discovery, genotype calling.&nbsp;</span><br><strong><span>Systems biology:</span></strong><span>&nbsp;Systems approaches to molecular biology, multiscale modeling, pathways,gene networks.&nbsp;</span><br><strong><span>Computational Proteomics:&nbsp;</span></strong><span>Filtering and indexing sequence databases, Peptide quantification and identification, Genome annotations via mass spectrometry, Identification of post-translational modifications, Structural genomics via mass spectrometry, Protein-protein interactions, Computational approaches to analysis of large scale Mass spectrometry data, Exploration and visualization of proteomic data, Data models and integration for proteomics and genomics, Querying and retrieval of proteomics and genomics data etc.</span></p>
<p><span><span>Authors of selected high quality papers in BICoB-2015 will be invited to submit extended version of their papers for possible publication in bioinformatics journals (</span><a href="http://www.worldscinet.com/jbcb/" target="_blank"><strong>Journal of Bioinformatics and Computational Biology JBCB).</strong></a></span></p>
<p><span><strong>Deadlines</strong>:</span></p>
<p><span></span></p>
<p>Paper Submission Deadline October 24, 2014<br>Notification of Acceptance December 15, 2014<br>Camera-Ready Manuscript January 16, 2015</p>
<p><span></span></p><p>Address of the bookmark: <a href="http://www.cs.umb.edu/bicob/" rel="nofollow">http://www.cs.umb.edu/bicob/</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/17926/orange-bioinformatics-2534</guid>
	<pubDate>Mon, 06 Oct 2014 12:51:37 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/17926/orange-bioinformatics-2534</link>
	<title><![CDATA[Orange-Bioinformatics 2.5.34]]></title>
	<description><![CDATA[<p>Orange Bioinformatics extends <a href="http://orange.biolab.si/">Orange</a>, a data mining software package, with common functionality for bioinformatics. The provided functionality can be accessed as a Python library or through a visual programming interface (Orange Canvas). The latter is also suitable for non-programmers.</p>
<p>Orange Bioinformatics provides access to publicly available data, like GEO data sets, Biomart, GO, KEGG, Atlas, ArrayExpress, and PIPAx database. As for the analytics, there is gene selection, quality control, scoring distances between experiments with multiple factors. All features can be combined with powerful visualization, network exploration and data mining techniques from the Orange data mining framework.</p><p>Address of the bookmark: <a href="https://pypi.python.org/pypi/Orange-Bioinformatics/2.5.34" rel="nofollow">https://pypi.python.org/pypi/Orange-Bioinformatics/2.5.34</a></p>]]></description>
	<dc:creator>Robert M Willioms</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/17924/software-developed-in-pevsner-lab</guid>
	<pubDate>Mon, 06 Oct 2014 12:41:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/17924/software-developed-in-pevsner-lab</link>
	<title><![CDATA[Software developed in pevsner lab]]></title>
	<description><![CDATA[<div>
<div id="block-system-main">
<div>
<div id="node-7">
<div>
<div>
<div>
<div>
<p><a href="http://pevsnerlab.kennedykrieger.org/dragon.htm">DRAGON</a>: Database Referencing of Array Genes Online</p>
<p><a href="http://pevsnerlab.kennedykrieger.org/php/node/96">SNOMAD</a>: Standardization and Normalization of Microarray Data</p>
<p><a href="http://pevsnerlab.kennedykrieger.org/php/node/70">SNPduo</a>: SNP Analysis Between Two Individuals</p>
<p><a href="http://pevsnerlab.kennedykrieger.org/php/node/71">SNPtrio</a>: Analyzing and Visualizing and Inheritance Patterns in Trios</p>
<p><a href="http://pevsnerlab.kennedykrieger.org/php/node/64">SNPscan</a>: Data Analysis and Visualization of SNP Data</p>
<p><a href="http://pevsnerlab.kennedykrieger.org/php/node/64">pediSNP</a>: Analyze SNP Data From a Pedigree of Two Generations</p>
<p><a href="http://pevsnerlab.kennedykrieger.org/php/node/73">kcoeff</a>: Calculate Cotterman Coefficients of SNP Genotype Data</p>
<p><a href="http://pevsnerlab.kennedykrieger.org/php/node/113">triPOD:</a> Detects chromosomal abnormalities in parent-child trio-based microarray data</p>
</div>
</div>
</div>
</div>
</div>
</div>
</div>
</div><p>Address of the bookmark: <a href="http://pevsnerlab.kennedykrieger.org/php/?q=software" rel="nofollow">http://pevsnerlab.kennedykrieger.org/php/?q=software</a></p>]]></description>
	<dc:creator>Robert M Willioms</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/17885/international-conference-on-bioinformatics-models-methods-and-algorithms</guid>
	<pubDate>Sun, 05 Oct 2014 11:42:52 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/17885/international-conference-on-bioinformatics-models-methods-and-algorithms</link>
	<title><![CDATA[International Conference on Bioinformatics Models, Methods and Algorithms]]></title>
	<description><![CDATA[<p><span>The purpose of the International Conference on Bioinformatics Models, Methods and Algorithms is to bring together researchers and practitioners interested in the application of computational systems and information technologies to the field of molecular biology, including for example the use of statistics and algorithms to understanding biological processes and systems, with a focus on new developments in genome bioinformatics and computational biology. Areas of interest for this community include sequence analysis, biostatistics, image analysis, scientific data management and data mining, machine learning, pattern recognition, computational evolutionary biology, computational genomics and other related fields.</span></p>
<p><span><span>Position Paper Submission Extension:</span><span>&nbsp;</span><span>October 9, 2014</span><span>&nbsp;</span><br><span>Regular Paper Authors Notification:</span><span>&nbsp;</span><span>November 3, 2014</span><span>&nbsp;</span><br><span>Position Paper Authors Notification:</span><span>&nbsp;</span><span>November 6, 2014</span><span>&nbsp;</span><br><span>Regular and Position Paper Camera Ready and Registration:</span><span>&nbsp;</span><span>November 17, 2014</span><span>&nbsp;</span></span></p><p>Address of the bookmark: <a href="http://www.bioinformatics.biostec.org/" rel="nofollow">http://www.bioinformatics.biostec.org/</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/17176/arvados</guid>
	<pubDate>Sat, 20 Sep 2014 16:54:21 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/17176/arvados</link>
	<title><![CDATA[Arvados]]></title>
	<description><![CDATA[<p>Arvados is a free and open&nbsp;source bioinformatics&nbsp;platform for genomic and&nbsp;biomedical data. User can&nbsp;Store | Organize | Compute | Share the data for free.&nbsp;</p>
<p><img src="https://arvados.org/images/dax.png" width="400" height="535" alt="image" style="border: 0px;"></p><p>Address of the bookmark: <a href="https://arvados.org/" rel="nofollow">https://arvados.org/</a></p>]]></description>
	<dc:creator>Martin Jones</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/16682/java-utilities-for-next-generation-sequencing-by-pierre-lindenbaum</guid>
	<pubDate>Mon, 15 Sep 2014 17:24:49 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/16682/java-utilities-for-next-generation-sequencing-by-pierre-lindenbaum</link>
	<title><![CDATA[Java utilities for Next Generation Sequencing  by Pierre Lindenbaum]]></title>
	<description><![CDATA[<div>
<div>
<p>Java utilities for Bioinformatics</p>
</div>
<div>
<p><a href="https://github.com/lindenb/jvarkit">https://github.com/lindenb/jvarkit</a></p>
</div>
</div><p>Address of the bookmark: <a href="https://github.com/lindenb/jvarkit" rel="nofollow">https://github.com/lindenb/jvarkit</a></p>]]></description>
	<dc:creator>Robert M Willioms</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/13842/swabs-to-genomes-a-comprehensive-workflow</guid>
	<pubDate>Sun, 10 Aug 2014 03:01:21 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/13842/swabs-to-genomes-a-comprehensive-workflow</link>
	<title><![CDATA[Swabs to Genomes: A Comprehensive Workflow]]></title>
	<description><![CDATA[<p>The sequencing, assembly, and basic analysis of microbial genomes, once a painstaking and expensive undertaking, has become almost trivial for research labs with access to standard molecular biology and computational tools. However, there are a wide variety of options available for DNA library preparation and sequencing, and inexperience with bioinformatics can pose a significant barrier to entry for many who may be interested in microbial genomics. The objective of the present study was to design, test, troubleshoot, and publish a simple, comprehensive workflow from the collection of an environmental sample (a swab) to a published microbial genome; empowering even a lab or classroom with limited resources and bioinformatics experience to perform it.</p><p>Address of the bookmark: <a href="https://peerj.com/preprints/453.pdf" rel="nofollow">https://peerj.com/preprints/453.pdf</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/13523/megadock-40</guid>
	<pubDate>Thu, 07 Aug 2014 18:08:54 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/13523/megadock-40</link>
	<title><![CDATA[MEGADOCK 4.0]]></title>
	<description><![CDATA[<p>An ultra&ndash;high-performance protein&ndash;protein docking software for heterogeneous supercomputers</p>
<p id="p-4"><strong>Summary:</strong> The application of protein&ndash;protein docking in large-scale interactome analysis is a major challenge in structural bioinformatics and requires huge computing resources. In this work, we present MEGADOCK 4.0, an FFT-based docking software that makes extensive use of recent heterogeneous supercomputers and shows powerful, scalable performance of over 97% strong scaling.</p>
<p id="p-5"><strong>Availability and Implementation:</strong> MEGADOCK 4.0 is written in C++ with OpenMPI and NVIDIA CUDA 5.0 (or later) and is freely available to all academic and non-profit users at: <a href="http://www.bi.cs.titech.ac.jp/megadock">http://www.bi.cs.titech.ac.jp/megadock</a>.</p>
<p id="p-6"><strong>Contact:</strong> <a href="mailto:akiyama@cs.titech.ac.jp">akiyama@cs.titech.ac.jp</a></p><p>Address of the bookmark: <a href="http://bioinformatics.oxfordjournals.org/content/early/2014/08/06/bioinformatics.btu532.short" rel="nofollow">http://bioinformatics.oxfordjournals.org/content/early/2014/08/06/bioinformatics.btu532.short</a></p>]]></description>
	<dc:creator>Suleman Khan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/12963/cosmos-our-workflow-management-system-for-ngs-data</guid>
	<pubDate>Wed, 23 Jul 2014 07:29:14 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/12963/cosmos-our-workflow-management-system-for-ngs-data</link>
	<title><![CDATA[COSMOS, our workflow management system for NGS data]]></title>
	<description><![CDATA[<p><strong>COSMOS</strong>, our Python-based management system for implementing large-scale parallel workflows focusing on, but not restricted to, large-scale short-read "NGS" sequencing data is open-access published via <a href="http://bioinformatics.oxfordjournals.org/content/early/2014/06/29/bioinformatics.btu385.abstract">Advance Access</a> in <em>Bioinformatics</em> (<a href="http://scholar.harvard.edu/lancaster/publications/cosmos-python-library-massively-parallel-workflows">Gafni et al. 2014</a>).&nbsp; It is also available for download for non-commercial academic and research purposes at:</p>
<p><strong>&nbsp;<a href="http://cosmos.hms.harvard.edu/">http://cosmos.hms.harvard.edu/</a></strong>.</p><p>Address of the bookmark: <a href="https://cosmos.hms.harvard.edu/" rel="nofollow">https://cosmos.hms.harvard.edu/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

</channel>
</rss>