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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/17176?offset=1060</link>
	<atom:link href="https://bioinformaticsonline.com/related/17176?offset=1060" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	
<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/42164/postdoctoral-researcher-in-statistical-bioinformatics-at-orebro-university</guid>
  <pubDate>Wed, 26 Aug 2020 10:20:11 -0500</pubDate>
  <link></link>
  <title><![CDATA[Postdoctoral Researcher in Statistical Bioinformatics at Örebro University]]></title>
  <description><![CDATA[
<p>The position is in Medical Sciences, with special focus on Statistical Bioinformatics.</p>

<p>The position is a full-time position for a fixed term of two years. The salary depends on the successful candidate’s qualifications and experience.</p>

<p>For more information, please contact Prof. Dirk Repsilber,This is an email address, Prof. Hugo Hesser, This is an email addressor Prof. Allan Sirsjö, allan.This is an email address, or Prof. Robert Brummer,This is an email address.</p>

<p>Örebro University actively pursues an equal work environment and values the qualities that diversity adds to our operations.</p>

<p>More detail at https://www.oru.se/english/working-at-orebro-university/jobs-and-vacancies/job/?jid=20200286/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40611/deepvariant-an-analysis-pipeline-that-uses-a-deep-neural-network-to-call-genetic-variants-from-next-generation-dna-sequencing-data</guid>
	<pubDate>Sat, 25 Jan 2020 13:28:09 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40611/deepvariant-an-analysis-pipeline-that-uses-a-deep-neural-network-to-call-genetic-variants-from-next-generation-dna-sequencing-data</link>
	<title><![CDATA[DeepVariant : an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.]]></title>
	<description><![CDATA[<p><span>DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.</span></p>
<p><span><span>DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data. DeepVariant relies on&nbsp;</span><a href="https://github.com/google/nucleus">Nucleus</a><span>, a library of Python and C++ code for reading and writing data in common genomics file formats (like SAM and VCF) designed for painless integration with the&nbsp;</span><a href="https://www.tensorflow.org/">TensorFlow</a><span>&nbsp;machine learning framework.</span></span></p>
<p><span><a href="https://ai.googleblog.com/2017/12/deepvariant-highly-accurate-genomes.html">https://ai.googleblog.com/2017/12/deepvariant-highly-accurate-genomes.html</a></span></p>
<p><span><a href="https://www.biorxiv.org/content/10.1101/092890v6">https://www.biorxiv.org/content/10.1101/092890v6</a></span></p>
<p><span><img src="https://4.bp.blogspot.com/-2KlXZO60sWE/WiGc8qlZfxI/AAAAAAAACOs/s1pNiKI8jsAvJLr1E_po5udDO8eObm_awCLcBGAs/s640/image3.png" width="640" height="427" alt="image" style="border: 0px;"></span></p><p>Address of the bookmark: <a href="https://github.com/google/deepvariant" rel="nofollow">https://github.com/google/deepvariant</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/42206/pollard-lab</guid>
  <pubDate>Fri, 25 Sep 2020 20:20:50 -0500</pubDate>
  <link></link>
  <title><![CDATA[Pollard Lab]]></title>
  <description><![CDATA[
<p>We are a bioinformatics research lab focused on developing novel methods and using them to study genome evolution, organization, and regulation. Our mission is to decode biomedical knowledge that is missed without rigorous statistical approaches.</p>

<p>http://docpollard.org/</p>

<p>Tools</p>

<p>http://docpollard.org/resources/software/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41209/juicebox-visualization-and-analysis-software-for-hi-c-data</guid>
	<pubDate>Fri, 21 Feb 2020 00:33:38 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41209/juicebox-visualization-and-analysis-software-for-hi-c-data</link>
	<title><![CDATA[Juicebox: Visualization and analysis software for Hi-C data]]></title>
	<description><![CDATA[<p>Juicebox is visualization software for Hi-C data. This distribution includes the source code for Juicebox,&nbsp;<a href="https://github.com/theaidenlab/juicer/wiki/Download">Juicer Tools</a>, and&nbsp;<a href="https://aidenlab.org/assembly/">Assembly Tools</a>.&nbsp;<a href="https://github.com/theaidenlab/juicebox/wiki/Download">Download Juicebox here</a>, or use&nbsp;<a href="https://aidenlab.org/juicebox">Juicebox on the web</a>. Detailed documentation is available&nbsp;<a href="https://github.com/theaidenlab/juicebox/wiki">on the wiki</a>. Instructions below pertain primarily to usage of command line tools and the Juicebox jar files.</p>
<p>Juicebox can now be used to visualize and interactively (re)assemble genomes. Check out the Juicebox Assembly Tools Module website&nbsp;<a href="https://aidenlab.org/assembly">https://aidenlab.org/assembly</a>&nbsp;for more details on how to use Juicebox for assembly.</p>
<p>GUI at&nbsp;<a href="https://aidenlab.org/juicebox/">https://aidenlab.org/juicebox/</a></p><p>Address of the bookmark: <a href="https://github.com/aidenlab/Juicebox" rel="nofollow">https://github.com/aidenlab/Juicebox</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/42308/icmr-scientist-jobs-for-biotechlife-sciencebiology-bioinformatics</guid>
  <pubDate>Tue, 10 Nov 2020 18:45:49 -0600</pubDate>
  <link></link>
  <title><![CDATA[ICMR Scientist Jobs For Biotech/Life Science/Biology &amp; Bioinformatics]]></title>
  <description><![CDATA[
<p>CMR welcomes on-line applications up to 5th December 2020 till 5:30 PM to fill out the vacancies of 42 Scientist’ E’ (Medical), 01 Scientist ‘E’ (Non-Medical), 16 Scientist ‘D’ (Medical) and also 06 Scientist ‘D’ (Non-Medical) from Indian Citizens for appointment on regular basis under Direct Recruitment with all India transfer liability under the Council.</p>

<p>Post I</p>

<p>Name of the Post: Scientist-E (Non-Medical)</p>

<p>Number of positions: One</p>

<p>Upper Age limit: 50 years</p>

<p>Post II</p>

<p>Name of the Post: Scientist-D (Non-Medical)</p>

<p>Number of positions: Six</p>

<p>Upper Age limit: 45 years</p>

<p>Fee:</p>

<p>Application Fee of Rs. 1500/- (Rupees one thousand five hundred only) is needed. SC / ST / Women/ PWD/ EWS applicants are exempted from application fee. Application Fee is to be paid by candidates through online web link given up the application. Application fees when paid will certainly not be reimbursed under any situations.</p>

<p>How to apply:</p>

<p>i) Candidates should apply online on https://recruit.icmr.org.in. A separate application needs to be submitted for every post, with the required application fee.</p>

<p>ii) Following self-attested documents are required to be uploaded together with the application:<br />a) Proof of Date of Birth.<br />b) Educational qualifications.<br />c) Experience.</p>

<p>More at https://recruit.icmr.org.in/assets/uploads/advertisement/ICMR_Advertisement_06112020.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41996/wgd%E2%80%94simple-command-line-tools-for-the-analysis-of-ancient-whole-genome-duplications</guid>
	<pubDate>Thu, 23 Jul 2020 05:49:45 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41996/wgd%E2%80%94simple-command-line-tools-for-the-analysis-of-ancient-whole-genome-duplications</link>
	<title><![CDATA[wgd—simple command line tools for the analysis of ancient whole-genome duplications]]></title>
	<description><![CDATA[<p><span>wgd is a easy to use command-line tool for<span>&nbsp;</span></span><em>K</em><sub>S</sub><span><span>&nbsp;</span>distribution construction named wgd. The wgd suite provides commonly used<span>&nbsp;</span></span><em>K</em><sub>S</sub><span><span>&nbsp;</span>and colinearity analysis workflows together with tools for modeling and visualization, rendering these analyses accessible to genomics researchers in a convenient manner.</span></p>
<p><a href="https://academic.oup.com/bioinformatics/article/35/12/2153/5162749">https://academic.oup.com/bioinformatics/article/35/12/2153/5162749</a></p><p>Address of the bookmark: <a href="https://github.com/arzwa/wgd" rel="nofollow">https://github.com/arzwa/wgd</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42499/galaxy-training-resources</guid>
	<pubDate>Sun, 27 Dec 2020 05:28:07 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42499/galaxy-training-resources</link>
	<title><![CDATA[Galaxy Training Resources !]]></title>
	<description><![CDATA[<p>Welcome to Galaxy Training!</p>
<p>Collection of tutorials developed and maintained by the worldwide Galaxy community</p>
<table>
<thead>
<tr><th>Topic</th><th>Tutorials</th></tr>
</thead>
<tbody>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/introduction/">Introduction to Galaxy Analyses</a></td>
<td>10</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/assembly/">Assembly</a></td>
<td>6</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/climate/">Climate</a></td>
<td>3</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/computational-chemistry/">Computational chemistry</a></td>
<td>6</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/ecology/">Ecology</a></td>
<td>6</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/epigenetics/">Epigenetics</a></td>
<td>6</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/genome-annotation/">Genome Annotation</a></td>
<td>3</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/imaging/">Imaging</a></td>
<td>3</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/metabolomics/">Metabolomics</a></td>
<td>4</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/metagenomics/">Metagenomics</a></td>
<td>7</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/proteomics/">Proteomics</a></td>
<td>18</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/sequence-analysis/">Sequence analysis</a></td>
<td>2</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/statistics/">Statistics and machine learning</a></td>
<td>8</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/transcriptomics/">Transcriptomics</a></td>
<td>23</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/variant-analysis/">Variant Analysis</a></td>
<td>8</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/visualisation/">Visualisation</a></td>
<td>2</td>
</tr>
</tbody>
</table>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://training.galaxyproject.org/training-material/" rel="nofollow">https://training.galaxyproject.org/training-material/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43268/kmer-a-suite-of-tools-for-dna-sequence-analysis</guid>
	<pubDate>Wed, 18 Aug 2021 00:02:54 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43268/kmer-a-suite-of-tools-for-dna-sequence-analysis</link>
	<title><![CDATA[Kmer: a suite of tools for DNA sequence analysis]]></title>
	<description><![CDATA[<p>More at&nbsp;https://help.rc.ufl.edu/doc/Kmer</p>
<p>This also includes:</p>
<ul>
<li>A2Amapper: ATAC, Assembly to Assembly Comparision tool:
<ul>
<li>Comparative mapping between two genome assemblies (same species), or between two different genomes (cross species).</li>
</ul>
</li>
</ul>
<ul>
<li>Sim4db:
<ul>
<li>Spliced alignment of cDNA and genomic sequences, from the same (sim4) or related (sim4cc) species. Optimized for high-throughput batched alignment.</li>
</ul>
</li>
</ul>
<ul>
<li>LEAFF:
<ul>
<li>LEAFF (ahem, Let's Extract Anything From Fasta) is a utility program for working with multi-fasta files. In addition to providing random access to the base level, it includes several analysis functions.</li>
</ul>
</li>
</ul>
<ul>
<li>Meryl:
<ul>
<li>An out-of-core k-mer counter. The amount of sequence that can be processed for any size k depends only on the amount of free disk space.</li>
</ul>
</li>
</ul><p>Address of the bookmark: <a href="https://help.rc.ufl.edu/doc/Kmer" rel="nofollow">https://help.rc.ufl.edu/doc/Kmer</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/42801/scientist-position-in-structural-bioinformatics-at-lonza</guid>
  <pubDate>Wed, 03 Feb 2021 21:38:06 -0600</pubDate>
  <link></link>
  <title><![CDATA[Scientist position in Structural Bioinformatics at Lonza]]></title>
  <description><![CDATA[
<p>Lonza (https://www.lonza.com/) are seeking a highly motivated and skilled (Senior) Scientist with experience in Structure-based Protein Engineering and Bioinformatics to join Lonza's Applied Protein Services (APS) Bioinformatics team based in Cambridge, UK.</p>

<p>More at https://instruct-eric.eu/jobs/scientist-position-in-structural-bioinformatics-at-lonza-cambridge-uk/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43902/interactivenn-a-web-based-tool-for-the-analysis-of-sets-through-venn-diagrams</guid>
	<pubDate>Wed, 29 Jun 2022 03:22:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43902/interactivenn-a-web-based-tool-for-the-analysis-of-sets-through-venn-diagrams</link>
	<title><![CDATA[InteractiVenn: a web-based tool for the analysis of sets through Venn diagrams]]></title>
	<description><![CDATA[<p><span>InteractiVenn, a more flexible tool for interacting with Venn diagrams including up to six sets. It offers a clean interface for Venn diagram construction and enables analysis of set unions while preserving the shape of the diagram. Set unions are useful to reveal differences and similarities among sets and may be guided in our tool by a tree or by a list of set unions. The tool also allows obtaining subsets&rsquo; elements, saving and loading sets for further analyses, and exporting the diagram in vector and image formats. InteractiVenn has been used to analyze two biological datasets, but it may serve set analysis in a broad range of domains.</span></p>
<p><span>More at&nbsp;https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-015-0611-3</span></p>
<p><span><img src="https://media.springernature.com/lw685/springer-static/image/art%3A10.1186%2Fs12859-015-0611-3/MediaObjects/12859_2015_611_Fig1_HTML.gif?as=webp" alt="image" style="border: 0px;"></span></p><p>Address of the bookmark: <a href="http://www.interactivenn.net/" rel="nofollow">http://www.interactivenn.net/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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