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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/32485?offset=1180</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33960/mgra-breakpoint-graphs-and-ancestral-genome-reconstructions</guid>
	<pubDate>Tue, 25 Jul 2017 08:48:25 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33960/mgra-breakpoint-graphs-and-ancestral-genome-reconstructions</link>
	<title><![CDATA[MGRA: Breakpoint graphs and ancestral genome reconstructions]]></title>
	<description><![CDATA[<p>MGRA (Multiple Genome Rearrangements and Ancestors) is a tool for reconstruction of ancestor genomes and evolutionary history of extant genomes.</p>
<p>It takes as an input a set of genomes represented as sequences of genes (or synteny blocks) and produces such sequences for ancestral genomes at the internal nodes of the phylogenetic tree.</p>
<p>The phylogenetic tree may be also specified completely or partially, in the latter case MGRA can reconstruct conserved ancestral regions (CARs) of the ancestral genome of interest.</p>
<p>Since version 2 MGRA supports gene insertion and deletions in addition to genome rearrangements and allows the input genomes to have different gene content.</p>
<p>It also can reconstruct most plausible phylogenetic tree based on the rearrangement characters.</p><p>Address of the bookmark: <a href="http://mgra.cblab.org/" rel="nofollow">http://mgra.cblab.org/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/3046/r-and-bioconductor-tutorial</guid>
	<pubDate>Fri, 23 Aug 2013 08:23:59 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/3046/r-and-bioconductor-tutorial</link>
	<title><![CDATA[R and Bioconductor Tutorial]]></title>
	<description><![CDATA[<p>This tutorial is intended to introduce users quickly to the basics of R, focusing on a few common tasks that &nbsp;biologists need to perform &nbsp;some basic analysis: &nbsp;load a table, plot some graphs, and perform some basic statistics. More extensive tutorials can be found on the project website and via bioconductor (not covered here).</p>
<p>You can add more tutorial links in comments if found new pages.</p><p>Address of the bookmark: <a href="http://manuals.bioinformatics.ucr.edu/home/R_BioCondManual" rel="nofollow">http://manuals.bioinformatics.ucr.edu/home/R_BioCondManual</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34482/ribbon-visualizing-complex-genome-alignments-and-structural-variation</guid>
	<pubDate>Wed, 29 Nov 2017 07:40:22 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34482/ribbon-visualizing-complex-genome-alignments-and-structural-variation</link>
	<title><![CDATA[Ribbon: Visualizing complex genome alignments and structural variation:]]></title>
	<description><![CDATA[<p>Ribbon can be used for long reads, short reads, paired-end reads, and assembly/genome alignments. Instructions for each data format are available by clicking on "instructions" in each tab on the right.</p>
<p>Local installation:</p>
<p>You can install Ribbon locally from Github by following the instructions here:&nbsp;<a href="https://github.com/MariaNattestad/ribbon" target="_blank">https://github.com/MariaNattestad/Ribbon</a></p><p>Address of the bookmark: <a href="http://genomeribbon.com/" rel="nofollow">http://genomeribbon.com/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/4043/what-is-bioinformatics</guid>
	<pubDate>Wed, 28 Aug 2013 06:53:05 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/4043/what-is-bioinformatics</link>
	<title><![CDATA[What is Bioinformatics?]]></title>
	<description><![CDATA[<iframe src="http://player.vimeo.com/video/71581534?byline=0" width="" height="" frameborder="0" webkitAllowFullScreen allowFullScreen></iframe>Illustration and Animation: Rachel Robinson Script: Tiffany Trent Voice-over: Kris Monger Sound: Glisten Carefully by Guennadi Malyshevski]]></description>
	
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34620/mash-fast-genome-and-metagenome-distance-estimation-using-minhash</guid>
	<pubDate>Tue, 12 Dec 2017 17:30:12 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34620/mash-fast-genome-and-metagenome-distance-estimation-using-minhash</link>
	<title><![CDATA[Mash: fast genome and metagenome distance estimation using MinHash]]></title>
	<description><![CDATA[<p>Mash is normally distributed as a dependency-free binary for Linux or OSX (see&nbsp;<a href="https://github.com/marbl/Mash/releases">https://github.com/marbl/Mash/releases</a>). This source distribution is intended for other operating systems or for development. Mash requires c++11 to build, which is available in and GCC &gt;= 4.8 and OSX &gt;= 10.7.</p>
<p>See&nbsp;<a href="http://mash.readthedocs.org/">http://mash.readthedocs.org</a>&nbsp;for more information.</p><p>Address of the bookmark: <a href="https://github.com/marbl/Mash/releases" rel="nofollow">https://github.com/marbl/Mash/releases</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/4093/ibm-research-computational-biology-center</guid>
	<pubDate>Thu, 29 Aug 2013 08:43:59 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/4093/ibm-research-computational-biology-center</link>
	<title><![CDATA[IBM Research Computational Biology Center]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/lr2bB_2g_Uc" frameborder="0" allowfullscreen></iframe>The IBM Computational Biology Center embraces activities at Yorktown Heights, with strong affiliations with activities at Almaden and other IBM Research Centers. Computational Biology (CompBio) including bioinformatics is the study of how computer systems can manage, analyze, and simulate the complex structures and processes inherent in living systems. CompBio Research at IBM spans pattern recognition in sequences, structures and processes, the studying of systems ranging from single protein molecules through to complex molecular interactions, and the data analysis, interpretation and reverse-engineering of complex disease-lifestyle-genomic interactions for fuller biological understanding. "CompBio" has a flavor of its own independant of its parents, biology and computer science. Nonetheless, CompBio is inherently a multi- disciplinary field with important applications in biology, chemical physics, materials science, agriculture, chemistry and ultimately nanotechnology.]]></description>
	
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35432/mummer4-a-fast-and-versatile-genome-alignment-system</guid>
	<pubDate>Sat, 03 Feb 2018 04:59:17 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35432/mummer4-a-fast-and-versatile-genome-alignment-system</link>
	<title><![CDATA[MUMmer4: A fast and versatile genome alignment system]]></title>
	<description><![CDATA[<p><span>MUMmer4, a substantially improved version of MUMmer that addresses genome size constraints by changing the 32-bit suffix tree data structure at the core of MUMmer to a 48-bit suffix array, and that offers improved speed through parallel processing of input query sequences. With a theoretical limit on the input size of 141Tbp, MUMmer4 can now work with input sequences of any biologically realistic length. We show that as a result of these enhancements, the&nbsp;</span><span>nucmer</span><span>&nbsp;program in MUMmer4 is easily able to handle alignments of large genomes;&nbsp;</span></p><p>Address of the bookmark: <a href="https://mummer4.github.io/" rel="nofollow">https://mummer4.github.io/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/4271/may-17-2013-differential-network-analysis</guid>
	<pubDate>Wed, 04 Sep 2013 16:22:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/4271/may-17-2013-differential-network-analysis</link>
	<title><![CDATA[May 17, 2013 - Differential Network Analysis]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/BvD6SkZRw9w" frameborder="0" allowfullscreen></iframe>Steve Horvath presents Differential Network Analysis at the UCLA Human Genetics/Biostatistics Network Course]]></description>
	
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36516/metassembler-merging-and-optimizing-de-novo-genome-assemblies</guid>
	<pubDate>Tue, 08 May 2018 04:52:33 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36516/metassembler-merging-and-optimizing-de-novo-genome-assemblies</link>
	<title><![CDATA[Metassembler: merging and optimizing de novo genome assemblies]]></title>
	<description><![CDATA[<p><span>Metassembler combines multiple whole genome de novo assemblies into a combined consensus assembly using the best segments of the individual assemblies.</span></p>
<p><span><span>Genome assembly projects typically run multiple algorithms in an attempt to find the single best assembly, although those assemblies often have complementary, if untapped, strengths and weaknesses. We present our metassembler algorithm that merges multiple assemblies of a genome into a single superior sequence.&nbsp;</span></span></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/metassembler/?source=directory" rel="nofollow">https://sourceforge.net/projects/metassembler/?source=directory</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/4353/project-fellow-alagappa-university</guid>
  <pubDate>Sat, 07 Sep 2013 14:24:13 -0500</pubDate>
  <link></link>
  <title><![CDATA[Project Fellow @ Alagappa University]]></title>
  <description><![CDATA[
<p>Advertisement for the post of project Fellow in UGC project</p>

<p>Project Fellow – One Post</p>

<p>Duration: Three Years</p>

<p>Fellowship : Rs.14, 000/- per month + HRA</p>

<p>Walk-in-interview: 16th Sept, 2013 at 10.00 am</p>

<p>Venue : Department of Bioinformatics, Alagappa University</p>

<p>Eligible candidates can attend walk in interview for the post of Project Fellow in UGC supported project entitled “Shape and chemical feature based 3D- Pharmacophore Model generation, Virtual Screening and MESP studies to identify Potential Leads for Antifungal Azoles”</p>

<p>Interested candidates may apply to Dr. Sanjeev Kumar Singh, Principal Investigator, Department of Bioinformatics, Karaikudi with their Curriculum Vitae along with the copies of the certificates in proof of their educational qualification and experience at skysanjeev@gmail.com</p>

<p>Qualification:</p>

<p>PG Degree in Bioinformatics / Chemistry/ Molecular Biology/ Biotechnology / Biophysics / Biochemistry / Life Sciences/ Pharmacy with minimum of 55% marks in the PG examinations</p>

<p>Desirable:</p>

<p>Research experience in Molecular modeling and CADD will be given preference. UGC-NET/ CSIR-JRF qualified candidates will get preference.</p>

<p>The posts are purely on temporary basis. No TA/DA will be paid for attending the interview.</p>

<p>Advertisement: http://www.alagappauniversity.ac.in/files/news_files/new%20advt-UGC-16sept,13.doc</p>
]]></description>
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