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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/26852?offset=310</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26453/stacks</guid>
	<pubDate>Wed, 24 Feb 2016 15:52:30 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26453/stacks</link>
	<title><![CDATA[Stacks]]></title>
	<description><![CDATA[<p>Stacks is a software pipeline for building loci from short-read sequences, such as those generated on the Illumina platform. Stacks was developed to work with restriction enzyme-based data, such as RAD-seq, for the purpose of building genetic maps and conducting population genomics and phylogeography.</p>
<p>More at http://catchenlab.life.illinois.edu/stacks/</p><p>Address of the bookmark: <a href="http://catchenlab.life.illinois.edu/stacks/" rel="nofollow">http://catchenlab.life.illinois.edu/stacks/</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26539/scikit-learn</guid>
	<pubDate>Mon, 29 Feb 2016 17:39:24 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26539/scikit-learn</link>
	<title><![CDATA[scikit-learn]]></title>
	<description><![CDATA[<p>Machine Learning in Python</p>
<p>Simple and efficient tools for data mining and data analysis<br> Accessible to everybody, and reusable in various contexts<br> Built on NumPy, SciPy, and matplotlib<br> Open source, commercially usable - BSD license</p>
<p>More at&nbsp;http://scikit-learn.org/stable/index.html</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="http://scikit-learn.org/stable/auto_examples/index.html" rel="nofollow">http://scikit-learn.org/stable/auto_examples/index.html</a></p>]]></description>
	<dc:creator>Jitendra Prajapati</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28141/csbb-v10</guid>
	<pubDate>Wed, 29 Jun 2016 07:33:05 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28141/csbb-v10</link>
	<title><![CDATA[CSBB-v1.0]]></title>
	<description><![CDATA[<p>CSBB is a command line based bioinformatics suite to analyze biological data acquired through varied avenues of biological experiments. CSBB is implemented in Perl, while it also leverages the use of R and python in background for specific modules. Major focus of CSBB is to allow users from biology and bioinformatics community, to get benefited by performing down-stream analysis tasks while eliminating the need to write programming code. CSBB is currently available on Linux, UNIX, MAC OS and Windows platforms.</p>
<p>Currently CSBB provides 13 modules focused on analytical tasks like performing upper-quantile normalization on expression data or convert genome wide gene expression to z-scores when comparing expression data from different platforms.</p>
<p>More at&nbsp;https://github.com/skygenomics/CSBB-v1.0</p><p>Address of the bookmark: <a href="https://github.com/skygenomics/CSBB-v1.0" rel="nofollow">https://github.com/skygenomics/CSBB-v1.0</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30336/finding-patterns-in-biological-sequences</guid>
	<pubDate>Thu, 22 Dec 2016 10:30:49 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30336/finding-patterns-in-biological-sequences</link>
	<title><![CDATA[Finding Patterns in Biological Sequences]]></title>
	<description><![CDATA[<p>In this report we provide an overview of known techniques for discovery of patterns of biological sequences (DNA and proteins). We also provide biological motivation, and methods of biological verification of such patterns. Finally we list publicly available tools and databases for pattern discovery. On-line supplement is available through http://genetics.uwaterloo.ca/&sim;tvinar/cs798g/motif.</p><p>Address of the bookmark: <a href="http://engr.case.edu/li_jing/papers/00798gpattern.pdf" rel="nofollow">http://engr.case.edu/li_jing/papers/00798gpattern.pdf</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30966/maftools</guid>
	<pubDate>Thu, 16 Feb 2017 11:16:01 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30966/maftools</link>
	<title><![CDATA[MafTools]]></title>
	<description><![CDATA[<p>maftools - An R package to summarize, analyze and visualize MAF files. <a href="https://github.com/PoisonAlien/maftools#introduction"></a>Introduction.</p>
<p>With advances in Cancer Genomics, Mutation Annotation Format (MAF) is being widley accepted and used to store variants detected. <a href="http://cancergenome.nih.gov">The Cancer Genome Atlas</a> Project has seqenced over 30 different cancers with sample size of each cancer type being over 200. The <a href="https://wiki.nci.nih.gov/display/TCGA/TCGA+MAF+Files">resulting data</a> consisting of genetic variants is stored in the form of <a href="https://wiki.nci.nih.gov/display/TCGA/Mutation+Annotation+Format+%28MAF%29+Specification">Mutation Annotation Format</a>. This package attempts to summarize, analyze, annotate and visualize MAF files in an efficient manner either from TCGA sources or any in-house studies as long as the data is in MAF format. Maftools can also handle ICGC Simple Somatic Mutation format.</p>
<p>maftools is on <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f449.png" alt=":point_right:" width="20" height="20" style="border: 0px;"> <a href="http://biorxiv.org/content/early/2016/05/11/052662">bioRxiv</a> <img src="https://assets-cdn.github.com/images/icons/emoji/bowtie.png" alt=":bowtie:" title=":bowtie:" width="20" height="20" style="border: 0px; text-align: absmiddle;"></p>
<p>Please cite the below if you find this tool useful for you.</p>
<p>Mayakonda, A. and H.P. Koeffler, Maftools: Efficient analysis, visualization and summarization of MAF files from large-scale cohort based cancer studies. bioRxiv, 2016. doi: <a href="http://dx.doi.org/10.1101/052662">http://dx.doi.org/10.1101/052662</a></p><p>Address of the bookmark: <a href="https://github.com/PoisonAlien/maftools" rel="nofollow">https://github.com/PoisonAlien/maftools</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/31566/software-and-tools-to-detect-structure-variation-with-long-reads</guid>
	<pubDate>Wed, 15 Mar 2017 14:31:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/31566/software-and-tools-to-detect-structure-variation-with-long-reads</link>
	<title><![CDATA[Software and Tools to detect structure variation with long reads !!]]></title>
	<description><![CDATA[<p>Uncovering the connection between genetics and heritable diseases requires an approach that looks at all the variant bases and types in a genome. While a PacBio&nbsp;<em>de novo</em>&nbsp;assembly resolves the most novel SV variants. 8-10X PacBio coverage of single genomes or trios reveals triple the SVs detectable by short-read data.</p><p>With&nbsp;<span style="text-decoration: underline;"><a href="http://www.pacb.com/smrt-science/">Single Molecule, Real-Time (SMRT) Sequencing</a></span>, you can access structural variations having a broad range of sizes, types, and GC content with the ability to:</p><ul>
<li>Uncover missing heritability linked to structural variation</li>
<li>Unambiguously identify genomic context and variant breakpoints at the sequence level to unravel the genetic etiology of disease</li>
<li>Resolve structural variation across the complete size spectrum with basepair resolution</li>
</ul><p>Following are the SV tools, which can assist you to achieve your goal.</p><p><strong>Sniffles:</strong>&nbsp;Structural variation caller using third generation sequencing</p><p>Sniffles is a structural variation caller using third generation sequencing (PacBio or Oxford Nanopore). It detects all types of SVs using evidence from split-read alignments, high-mismatch regions, and coverage analysis. Please note the current version of Sniffles requires sorted output from BWA-MEM (use -M and -x parameter) or NGM-LR with the optional SAM attributes enabled!&nbsp;</p><p>More at&nbsp;https://github.com/fritzsedlazeck/Sniffles</p><p><strong style="font-size: 12.8px;"><br />MultiBreak-SV:</strong> It identifies structural variants from next-generation paired end data, third-generation long read data, or data from a combination of sequencing platforms.</p><p>There are two pieces of software in this release: (1) a pre-processor that takes machineformat (.m5) BLASR files, and (2) MultiBreak-SV. For installation and usage instructions, see doc/MultiBreakSV-Manual.txt.</p><p>More at&nbsp;https://github.com/raphael-group/multibreak-sv</p><p><strong style="font-size: 12.8px;"><br />Parliament:</strong>&nbsp;A Structural Variation Tool. Why ask a single sv-detection approach to find every variant when you can have a parliament of tools deciding?</p><p>Publication about the algorithm and &ldquo;&hellip;the first long-read characterization of structural variation in a diploid human personal genome&hellip;&rdquo; (HS1011) -&nbsp;<a href="http://www.biomedcentral.com/1471-2164/16/286">&ldquo;Assessing structural variation in a personal genome&mdash;towards a human reference diploid genome&rdquo;</a></p><p>More at&nbsp;https://sourceforge.net/projects/parliamentsv/</p><p>https://www.dnanexus.com/papers/Parliament_Info_Sheet.pdf</p><p><br /><strong>PBHoney:</strong>&nbsp;the structural variation discovery tool&nbsp;<br /><br />PBHoney is an implementation of two variant-identification approaches designed to exploit the high mappability of long reads (i.e., greater than 10,000 bp). PBHoney considers both intra-read discordance and soft-clipped tails of long reads to identify structural variants.</p><p>Read The Paper&nbsp;<a href="http://www.biomedcentral.com/1471-2105/15/180/abstract" target="_blank">http://www.biomedcentral.com/1471-2105/15/180/abstract</a></p><p>More at&nbsp;https://sourceforge.net/projects/pb-jelly/</p><p><strong><br />SMRT-SV:</strong> Structural variant and indel caller for PacBio reads</p><p>Structural variant (SV) and indel caller for PacBio reads based on methods from&nbsp;<a href="http://www.nature.com/nature/journal/vaop/ncurrent/full/nature13907.html">Chaisson et al. 2014</a>.</p><p>SMRT-SV provides an official software package for tools described in&nbsp;<a href="http://www.nature.com/nature/journal/vaop/ncurrent/full/nature13907.html">Chaisson et al. 2014</a>&nbsp;and adds several key features including the following.</p><ul>
<li>Unified variant calling user interface with built-in cluster compute support</li>
<li>Small indel calling (2-49 bp)</li>
<li>Improved inversion calling (<code>screenInversions</code>)</li>
<li>Quality metric for SV calls based on number of local assemblies supporting each call</li>
<li>Higher sensitivity for SV calls using tiled local assemblies across the entire genome instead of "signature" regions</li>
<li>Genotyping of SVs with Illumina paired-end reads from WGS samples</li>
</ul><p>More at&nbsp;https://github.com/EichlerLab/pacbio_variant_caller</p>]]></description>
	<dc:creator>Archana Malhotra</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/2002/ibl-laboratory</guid>
  <pubDate>Mon, 12 Aug 2013 02:02:29 -0500</pubDate>
  <link></link>
  <title><![CDATA[IBL laboratory]]></title>
  <description><![CDATA[
<p>The IBL laboratory focuses on the multi-disciplinary analyses of the global responses of model microorganisms, cyanobacteria (mainly Synechocystis PCC6803) and yeasts (mainly Saccharomyces cerevisae) to environmental stresses triggered by oxidative agents, heavy metals, or drastic changes in nutrients availability. The genome-wide responses studied with the "omics" techniques (transcriptomics, proteomics, metabolomics and genetics) generate a wealth of experimental data, which are processed, archived, integrated and represented as working models through bioinformatics and mathematics. </p>

<p>Link : http://www-dsv.cea.fr/en/instituts/institut-de-biologie-et-de-technologies-de-saclay-ibitec-s/unites-de-recherche/service-de-biologie-integrative-et-genetique-moleculaire-sbigem/laboratoire-de-biologie-integrative-lbi/presentation__1</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/926/list-of-popular-bioinformatics-softwaretools</guid>
	<pubDate>Tue, 16 Jul 2013 14:30:30 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/926/list-of-popular-bioinformatics-softwaretools</link>
	<title><![CDATA[List of popular bioinformatics software/tools]]></title>
	<description><![CDATA[<p><a href="http://samtools.sourceforge.net/swlist.shtml">I</a>n current genome era, our day to day work is to handle the huge geneome sequences, expression data, several other datasets. This link provide a comprehensive list of commonly used sofware/tools.</p><p>Address of the bookmark: <a href="http://samtools.sourceforge.net/swlist.shtml" rel="nofollow">http://samtools.sourceforge.net/swlist.shtml</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/1212/computational-proteomics-lets-remember-the-basics</guid>
	<pubDate>Thu, 01 Aug 2013 17:24:20 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/1212/computational-proteomics-lets-remember-the-basics</link>
	<title><![CDATA[Computational Proteomics : Lets remember the basics]]></title>
	<description><![CDATA[<p>I spend some of my valuable time in computational drug designing sector. I remember my initial proteomics days, playing with interactive protein visualization software and dreaming big. Fortunately or unfortunately, I switched to genomics and handling the genomic floods in Petabytes which is expected to be in Brontobytes in coming years. Did I mention Brontobytes ??? Let me call to my server personnel &hellip; it gonna tsunami !!!!!</p><p>Today, refreshing my old memories I decided to blog about the basic knowledge of biochemistry and computational proteomics&nbsp;skills, but after I found several article on internet saying exactly what I had wanted to say I thought I might as well just redirect BOL's blog readers there instead:</p><p>Here is the list of website and videos links which provide a good resource for you basic chemistry need:</p><p><a href="http://tecreativ.blogspot.co.uk/2012/09/funny-shortcut-remember-periodic-table.html"></a><a href="http://tecreativ.blogspot.co.uk/2012/09/funny-shortcut-remember-periodic-table.html"></a><a href="http://tecreativ.blogspot.co.uk/2012/09/funny-shortcut-remember-periodic-table.html"></a><a href="http://tecreativ.blogspot.co.uk/2012/09/funny-shortcut-remember-periodic-table.html">http://tecreativ.blogspot.co.uk/2012/09/funny-shortcut-remember-periodic-table.html</a></p><p>This blog have some specific hindi word to remember entire periodic table. I really like</p><p>Group 14 (C Si Ge Sn Pb) -&gt; Sentence &ldquo;<strong>C</strong>hemistry&nbsp;<strong>Si</strong>r&nbsp;<strong>G</strong>iv<strong>e</strong>s&nbsp;<strong>S</strong>a<strong>n</strong>ki&nbsp;<strong>P</strong>ro<strong>b</strong>lems&rdquo;</p><p>Sanki is a hindi word which mean crazy :P</p><p>I found this link useful as well&nbsp;<a href="http://www.wikihow.com/Memorise-the-Periodic-Table"></a><a href="http://www.wikihow.com/Memorise-the-Periodic-Table"></a><a href="http://www.wikihow.com/Memorise-the-Periodic-Table"></a><a href="http://www.wikihow.com/Memorise-the-Periodic-Table">http://www.wikihow.com/Memorise-the-Periodic-Table</a></p><p>The eagle genomics group provide an element of bioinformatics in periodic tables. Yes you got it, this is not periodic table rather bioinformatics tools with periodicals</p><p><a href="http://elements.eaglegenomics.com/"></a><a href="http://elements.eaglegenomics.com/"></a><a href="http://elements.eaglegenomics.com/"></a><a href="http://elements.eaglegenomics.com/">http://elements.eaglegenomics.com/</a></p><p>You can also try this video links, which provide you an overview with tricks on periodic tables:</p><p><a href="http://www.youtube.com/watch?v=fLSfgNxoVGk"></a><a href="http://www.youtube.com/watch?v=fLSfgNxoVGk"></a><a href="http://www.youtube.com/watch?v=fLSfgNxoVGk"></a><a href="http://www.youtube.com/watch?v=fLSfgNxoVGk">http://www.youtube.com/watch?v=fLSfgNxoVGk</a></p><p><a href="http://www.youtube.com/user/periodicvideos"></a><a href="http://www.youtube.com/user/periodicvideos"></a><a href="http://www.youtube.com/user/periodicvideos"></a><a href="http://www.youtube.com/user/periodicvideos">http://www.youtube.com/user/periodicvideos</a></p><p>For drug design educational material, software, tools, databses, viewer, file format and many more stuff at one place&nbsp;<a href="http://www.allfordrugs.com/drug-design/.%C2%A0I"></a><a href="http://www.allfordrugs.com/drug-design/"></a><a href="http://www.allfordrugs.com/drug-design/"></a><a href="http://www.allfordrugs.com/drug-design/">http://www.allfordrugs.com/drug-design/</a>&nbsp;I highly recommend you all computational drug designer to bookmark this page for future studies as well.</p><p>I just remember one of my mini project in which I use my flash knowledge (flash .. oh ya flash) to explain amino acids in interactive and user friendly manner. I can&rsquo;t provide It right now, but promise you to provide a link in near future. I hope that you will enjoy my flashy creative skills :).</p><p>Moreover, I found some of very interesting tricks to remember all amino acids chemical formulae on youtube at</p><p><a href="http://www.youtube.com/watch?v=gqrWb0fmzQ&amp;list=PL6132651E70BB5575"></a><a href="http://www.youtube.com/watch?v=gqrWb0fmzQ&amp;list=PL6132651E70BB5575"></a><a href="http://www.youtube.com/watch?v=gqrWb0fmzQ&amp;list=PL6132651E70BB5575"></a><a href="http://www.youtube.com/watch?v=gqrWb0fmzQ&amp;list=PL6132651E70BB5575">http://www.youtube.com/watch?v=gqrWb0fmzQ&amp;list=PL6132651E70BB5575</a></p><p><a href="http://www.youtube.com/watch?v=C2GfoGXfySQ&amp;list=PL6132651E70BB5575"></a><a href="http://www.youtube.com/watch?v=C2GfoGXfySQ&amp;list=PL6132651E70BB5575"></a><a href="http://www.youtube.com/watch?v=C2GfoGXfySQ&amp;list=PL6132651E70BB5575"></a><a href="http://www.youtube.com/watch?v=C2GfoGXfySQ&amp;list=PL6132651E70BB5575">http://www.youtube.com/watch?v=C2GfoGXfySQ&amp;list=PL6132651E70BB5575</a></p><p><br />Key points for computer added drug designers?<br />1. A shortage of biochemistry skills means that you absolutely nowhere in understanding the key concept and do research.<br />2. Keep handy with complex mathematical formula, before merely running tools or software.<br />3. Dig it better and deeper guys .. design it.</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/4552/imtech-lab</guid>
  <pubDate>Sun, 15 Sep 2013 09:41:04 -0500</pubDate>
  <link></link>
  <title><![CDATA[IMTECH Lab]]></title>
  <description><![CDATA[
<p>Computer Aided Protein Structure Prediction; Identification of Vaccine<br />Candidates (T-Epitope prediction); Analysis of Nucleotide/Protein Sequences; Development of Web Server/</p>

<p>Software; Creation of Public Domain Resources in Biology<br />Present Status::</p>

<p>Developing prediction methods for gene, beta-turn, secondary structure and MHC-binding sites.<br />Area of Interest ::</p>

<p>Comparison of force field simulations. Analysis of DNA-protein interactions using molecular mechanics methods.Drug Target Identification using in silico biology.</p>

<p>More @ http://www.imtech.res.in/bic/index.php?option=com_content&amp;view=article&amp;id=65</p>

<p>PIs: http://www.imtech.res.in/bic/index.php?option=com_content&amp;view=article&amp;id=69</p>
]]></description>
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