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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/28303?offset=590</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36218/g-compass-a-comparative-genome-browser</guid>
	<pubDate>Thu, 12 Apr 2018 10:00:27 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36218/g-compass-a-comparative-genome-browser</link>
	<title><![CDATA[G-compass: a comparative genome browser]]></title>
	<description><![CDATA[<p><span>G-compass (</span><a href="http://www.h-invitational.jp/g-compass/" target="_top">http://www.h-invitational.jp/g-compass/</a><span>) is a comparative genome browser. It visualizes evolutionarily conserved genomic regions between human and other 12 vertebrates based on original genome alignments pursuing higher coverage (1,2). Annotations of human genes/transcripts and their ortholog information were derived from&nbsp;</span><a href="http://www.h-invitational.jp/hinv/ahg-db/index.jsp" target="_top">H-InvDB</a><span>&nbsp;and its subdatabase&nbsp;</span><a href="http://www.h-invitational.jp/evola/" target="_top">Evola</a><span>, respectively. G-compass is available for free of charge. [&nbsp;</span><a href="http://www.h-invitational.jp/g-compass/cgi-bin/gc_main.cgi?species_1=Hg18&amp;species_2=pt2&amp;strand_1=%2B&amp;strand_2=%2B&amp;from_win=main&amp;gen_str=2&amp;chr_1=01&amp;chr_2=01&amp;st_1=103804298&amp;ed_1=104204297&amp;st_2=105235351&amp;ed_2=105635350" target="_top">Sample</a><span>&nbsp;]</span></p><p>Address of the bookmark: <a href="http://www.h-invitational.jp/g-compass/" rel="nofollow">http://www.h-invitational.jp/g-compass/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/10127/assistant-professor-at-sardar-patel-university</guid>
  <pubDate>Mon, 21 Apr 2014 21:03:55 -0500</pubDate>
  <link></link>
  <title><![CDATA[Assistant Professor at SARDAR PATEL UNIVERSITY]]></title>
  <description><![CDATA[
<p>SARDAR PATEL UNIVERSITY<br />Centre for Interdisciplinary Studies in Science and Technology</p>

<p>No.: SPU/CISST/Advt./2014-15/519</p>

<p>ADVERTISEMENT for Teaching Positions (Contractual)</p>

<p>Applications for the following Contractual Teaching Position are invited for Centre for Interdisciplinary Studies in Science and Technology (CISST), Sardar Patel University:</p>

<p>2. Assistant Professor (ONE) (Contractual)</p>

<p>For the subject of Bioinformatics</p>

<p>Qualifications:</p>

<p>(I) Good academic record as defined by the concerned university with at least 55 % marks (or an equivalent grade in a point scale wherever grading system is followed) at the Master’s level</p>

<p>(II) Ph.D. degree in the concerned subject or in a relevant interdisciplinary subject<br />from an Indian University or NET/SLET clearance Contractual appointment carries a total Fixed Emoluments of Rs. 30,000/- p.m without any assurance of permanent Positions and related benefits.</p>

<p>An Application Form in prescribed Performa, available on University Website: www.spuvvn.edu should be filled in completely in Twelve Copies with self attested copies of certificates of qualifications and experience. Only one copy of each mark sheet be attached with the first copy of the application form. All 12 (Twelve) Application forms should be sent to Registrar’s office along with Demand Draft of Application form fee of Rs. 250/- (Non-refundable) in favour of “REGISTRAR, SARDAR PATEL UNIVERSITY, VALLABH VIDYANAGAR”. The S.C. and S.T. category candidates need not to pay Application fee.</p>

<p>Applicants who are in service should apply through their present employers. Candidates called for interview shall be required to attend at their own cost.</p>

<p>In absence of suitable candidate, the University may relax the eligibility criteria, for conditional appointment.</p>

<p>The last date of receipt of application by the University is 30th April, 2014</p>

<p>Advertisement: www.spuvvn.edu/careers/CISST%20Advt.%20April%202014.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37306/genome-u-plot-a-whole-genome-visualization</guid>
	<pubDate>Fri, 13 Jul 2018 19:50:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37306/genome-u-plot-a-whole-genome-visualization</link>
	<title><![CDATA[Genome U-Plot: a whole genome visualization]]></title>
	<description><![CDATA[<p><span>Genome U-Plot for producing clear and intuitive graphs that allows researchers to generate novel insights and hypotheses by visualizing SVs such as deletions, amplifications, and chromoanagenesis events. The main features of the Genome U-Plot are its layered layout, its high spatial resolution and its improved aesthetic qualities.&nbsp;</span></p>
<p><span>https://github.com/gaitat/GenomeUPlot</span></p><p>Address of the bookmark: <a href="https://github.com/gaitat/GenomeUPlot" rel="nofollow">https://github.com/gaitat/GenomeUPlot</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/10394/bioinformatics-protocols</guid>
	<pubDate>Mon, 05 May 2014 10:21:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/10394/bioinformatics-protocols</link>
	<title><![CDATA[Bioinformatics Protocols]]></title>
	<description><![CDATA[<h2><span> RNA Seq </span></h2>
<p><strong> Basic Galaxy Tutorial </strong></p>
<ul>
<li><a href="https://docs.google.com/document/pub?id=1KbTiBHtvHLfPRZ39AY3uriazrINA8TJzgjjwn1zPP7Y">RNA-Seq tutorial</a> based on <a href="http://www.nature.com/protocolexchange/protocols/2327">Trapnell et al. (2012)</a> <em>Nature Protocols</em></li>
</ul>
<dl><dd>In this tutorial we cover the concepts of <a href="http://en.wikipedia.org/wiki/RNA-Seq">RNA-Seq</a> differential gene expression (DGE) analysis using a very small synthetic dataset from a well studied organism.</dd></dl>
<p><strong> Advanced Galaxy Tutorial </strong></p>
<ul>
<li><a href="https://docs.google.com/document/d/1fQ1XfeOKhezJUDTzMXtZVY20c3RGoHe-HLvFOGzqU4s/pub">RNA-Seq (Advanced) Tutorial</a></li>
</ul>
<dl><dd>In this tutorial we compare the performance of three statistically-based differential expression tools:</dd><dd>* CuffDiff</dd><dd>* EdgeR</dd><dd>* DESeq2</dd></dl>
<p><strong> Advanced Command Line Tutorial </strong></p>
<ul>
<li><a href="https://docs.google.com/document/d/1ayJXtgBP1OXtnV7o7lq4QHKMNk5SdPHFq4hGkqndBtI/pub">Graphical Output with CummeRbund</a> introduces some basic commands using the cummeRbund package of the R programming language</li>
</ul>
<dl><dd>You will need to install R, RStudio and cummeRbund on your PC (explained in the Tutorial). You will learn how to produce graphical output from RNA-Seq analysis previously done using a Cuffdiff analysis.</dd></dl>
<h2><span> Variant Detection </span></h2>
<p><strong> Basic Galaxy Tutorial </strong></p>
<ul>
<li><a href="https://docs.google.com/document/pub?id=1ZRzrjjOCvtAu3m-IKL-rbJ1f4On60dDL_IEwG7oejdI">Variant Detection tutorial</a></li>
</ul>
<dl><dd>In this tutorial we cover the concepts of detecting small variants (SNVs and indels) in human genomic DNA using a small set of reads from chromosome 22.</dd></dl>
<p><strong>Advanced Galaxy Tutorial</strong></p>
<ul>
<li><a href="https://docs.google.com/document/pub?id=1CuKkKylVDb03tnN7RSWl5EUzleetn0ctjmvaidPKLxM">Variant Detection (Advanced) Tutorial</a></li>
</ul>
<dl><dd>In this tutorial we compare the performance of three statistically-based variant detection tools:</dd><dd>* SAMtools: Mpileup</dd><dd>* GATK: Unified Genotyper</dd><dd>* FreeBayes</dd><dd>Each of these tools takes as its input a BAM file of aligned reads and generates a list of likely variants in VCF format</dd></dl>
<p><strong>Pipelines</strong> are for those who are comfortable with using the UNIX command line; and often allow more control over branching and iteration logic.</p>
<ul>
<li><a href="https://github.com/claresloggett/variant_calling_pipeline">WGS/exome GATK-based variant calling pipeline</a></li>
</ul>
<dl><dd>This is a basic variant-calling and annotation pipeline developed at the Victorian Life Sciences Computation Initiative (VLSCI), University of Melbourne. It is based around BWA, GATK and ENSEMBL and was originally designed for human (or similar) data. The master branch is configured for WGS data; there is an exome branch configured for variant calling in exome data.</dd><dd>To run the pipeline you will need Rubra: <a href="https://github.com/bjpop/rubra">https://github.com/bjpop/rubra</a>. Rubra uses the python Ruffus library: <a href="http://www.ruffus.org.uk/">http://www.ruffus.org.uk/</a>.</dd></dl>
<p><strong>Protocols</strong></p>
<ul>
<li><a href="https://docs.google.com/document/d/1lfDYNzHjfDA1pHTHd-0w3xHhg7L4TipT1gRfzgiV8es/pub">Familial Variant Calling</a></li>
</ul>
<dl><dd>In this protocol we discuss and outline the process of calling familial related mutations.</dd></dl>
<ul>
<li><a href="https://docs.google.com/document/d/1PIhm8NrFGaSK0hxpDcp8wUOz11ZkOaHIrpnJshMgDec/pub">Somatic Variant Calling</a></li>
</ul>
<dl><dd>In this protocol we discuss and outline the process of identifying somatic variants or mutations.</dd></dl>
<h2><span> Assembly </span></h2>
<p><strong> Basic Galaxy Tutorial </strong></p>
<ul>
<li><a href="https://docs.google.com/document/pub?id=1N3AB9ptISUu4zULqe1kXpVF0BDyGb5f5yzxWSJd_WNM">Genome assembly tutorial</a></li>
</ul>
<dl><dd>In this tutorial we carry out de novo assembly of a microbial genome. We have also written a <a href="https://docs.google.com/document/d/1xs-TI5MejQARqo0pcocGlymsXldwJbJII890gnmjI0o/pub">De novo Genome Assembly for Illumina Data</a> Protocol for a more generic description of the method.</dd></dl>
<p><strong> Protocol </strong></p>
<ul>
<li><a href="https://docs.google.com/document/d/1xs-TI5MejQARqo0pcocGlymsXldwJbJII890gnmjI0o/pub">De novo Genome Assembly for Illumina Data</a></li>
</ul>
<dl><dd>In this protocol we discuss and outline the process of de novo assembly for small to medium sized genomes. Use our <a href="https://docs.google.com/document/pub?id=1N3AB9ptISUu4zULqe1kXpVF0BDyGb5f5yzxWSJd_WNM">Genome assembly tutorial</a> to learn a specific case of using Galaxy to carry out de novo assembly of a microbial genome.</dd></dl>
<h2><span> Small RNAs </span></h2>
<p><strong> Basic Galaxy Tutorial </strong></p>
<ul>
<li><a href="https://docs.google.com/document/d/1WAObJr7M0m8U-2ku-0Y0Sdt_IHmqd1h8WaJHPhnJ1lM/pub">Quality control for small RNA</a></li>
</ul>
<dl><dd>This tutorial covers initial steps of the workflow for analysis of short RNA expression such as a quality control of the raw reads, processing of the raw reads for the subsequent analysis and initial quality assessment of the library.</dd></dl>
<h2><span> ChIP Seq </span></h2>
<p><strong> Protocol </strong></p>
<ul>
<li><a href="https://docs.google.com/document/d/1UPJC8dsiDeP5R9MH9U0IvoDgPF2Q3EOstAuzS3e6WCE/pub">ChIP-Seq</a></li>
</ul>
<dl><dd>In this protocol we discuss ChIP-Seq: a method to analyze the interaction between proteins and DNA.</dd></dl>
<h2><span> Amplicons </span></h2>
<p><strong>Protocol</strong></p>
<ul>
<li><a href="https://docs.google.com/document/d/1uW7JzxG86QzS92hTyeuNsLhX_d1XFbaZPSjh7jWxcSg/pub">Amplicon Alignment</a></li>
</ul>
<dl><dd>In this protocol we discuss and outline the process of aligning custom amplicons using primers for high precision.</dd></dl>
<h2><span> Learn Galaxy </span></h2>
<p><a href="https://docs.google.com/document/d/1wsdJDYfjZVg2uJxm9AHi_j0mY3X1M1F4gB-elkuYL7c/pub">Introduction to Galaxy,</a> for those who are very new to Galaxy.</p>
<p><a href="https://docs.google.com/document/d/1t7vVqa3mdeZYPv5-8hiHBFBYhNiynV_3mWByno9-wUM/pub">Using Histories and Workflows,</a> for those with some Galaxy knowledge.</p>
<p>The Galaxy project website has many <a href="http://wiki.galaxyproject.org/Learn">tutorials</a> and <a href="http://wiki.galaxyproject.org/Learn/Screencasts">screencasts</a> about using Galaxy and the tools, and developing new tools.</p><p>Address of the bookmark: <a href="https://genome.edu.au/wiki/Learn" rel="nofollow">https://genome.edu.au/wiki/Learn</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38646/visnetwork-an-r-package-for-network-visualization-using-visjs-javascript-library</guid>
	<pubDate>Wed, 09 Jan 2019 11:00:32 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38646/visnetwork-an-r-package-for-network-visualization-using-visjs-javascript-library</link>
	<title><![CDATA[visNetwork: an R package for network visualization, using vis.js javascript library]]></title>
	<description><![CDATA[<div id="introduction">
<p><strong>visNetwork</strong>&nbsp;is an R package for network visualization, using&nbsp;<strong>vis.js</strong>&nbsp;javascript library (<a href="http://visjs.org/">http://visjs.org/</a>). All remarks and bugs are welcome on github :&nbsp;<a href="https://github.com/datastorm-open/visNetwork">https://github.com/datastorm-open/visNetwork</a>.</p>
</div>
<div id="features">
<h2>Features</h2>
<p>Based on&nbsp;<a href="http://www.htmlwidgets.org/">htmlwidgets</a>, so :</p>
<ul>
<li>compatible with&nbsp;<a href="http://shiny.rstudio.com/">shiny</a>, R Markdown documents, and RStudio viewer</li>
</ul>
<p>The package proposes all the features available in&nbsp;<strong>vis.js</strong>&nbsp;API, and even more with special features for R :</p>
<ul>
<li>easy to use</li>
<li>custom shapes, styles, colors, sizes, &hellip;</li>
<li>works smooth on any modern browser for up to a few thousand nodes and edges</li>
<li>interactivity controls (highlight, collapsed nodes, selection, zoom, physics, movement of nodes, tooltip, events, &hellip;)</li>
<li>visualize&nbsp;<code>rpart</code>&nbsp;tree</li>
<li></li>
</ul>
</div><p>Address of the bookmark: <a href="https://datastorm-open.github.io/visNetwork/" rel="nofollow">https://datastorm-open.github.io/visNetwork/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/10457/assistant-professor-bio-informatics-at-health-and-family-welfare-department-medical-education-in-raipur</guid>
  <pubDate>Wed, 07 May 2014 00:08:38 -0500</pubDate>
  <link></link>
  <title><![CDATA[Assistant Professor (Bio-Informatics) at Health and Family Welfare Department (Medical Education) in Raipur]]></title>
  <description><![CDATA[
<p>Advertisement No.05/2014/ Exam/Dated 17/04/2014</p>

<p>No of vacancies: 01</p>

<p>Pay scale:Rs. 15600 – 39100 + 6600/-</p>

<p>Essential Academic Qualifications / Experience : Good academic record as defined by the concerned university with at least 55% marks (or an equivalent grade in a point scale wherever grading system is followed) at the Master's Degree level in a relevant subject from an Indian University, or an equivalent degree from an accredited foreign university.</p>

<p>Besides fulfilling the above qualifications, the candidate must have cleared the National Eligibility Test (NET) conducted by the UGC, CSIR or similar test accredited by the UGC like SLET/ SET.</p>

<p>Notwithstanding anything contained in sub-clauses (a) and (b) to this Clause, candidates, who are, or have been awarded a Ph.D. Degree in accordance with the University Grants Commission (Minimum Standards and Procedure for Award of Ph.D. Degree) Regulations, 2009, shall be exempted from the requirement of the minimum eligibility condition of NET/SLET/SET for recruitment and appointment of Assistant Professor or equivalent positions in Universities/Colleges/Institutions.</p>

<p>NET/SLET/SET shall also not be required for such Masters Programmes in disciplines for which NET/SLET/SET is not conducted.</p>

<p>Apply online: http://www.psc.cg.gov.in/htm/OA_ME2014.html</p>

<p>Last Date for Online Registration: 22/05/2014</p>

<p>For more details: http://www.psc.cg.gov.in/pdf/Advertisement/ADV_ME2014.pdf</p>
]]></description>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40964/panev-an-r-package-for-a-pathway-based-network-visualization</guid>
	<pubDate>Sun, 09 Feb 2020 12:41:52 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40964/panev-an-r-package-for-a-pathway-based-network-visualization</link>
	<title><![CDATA[PANEV: an R package for a pathway-based network visualization]]></title>
	<description><![CDATA[<p><span>PANEV (PAthway NEtwork Visualizer) is an R package set for gene/pathway-based network visualization. Based on information available on KEGG, it visualizes genes within a network of multiple levels (from 1 to&nbsp;</span><em>n</em><span>) of interconnected upstream and downstream pathways. The network graph visualization helps to interpret functional profiles of a cluster of genes.</span></p>
<p><span><a href="https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-020-3371-7">https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-020-3371-7</a></span></p><p>Address of the bookmark: <a href="https://github.com/vpalombo/PANEV" rel="nofollow">https://github.com/vpalombo/PANEV</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/10659/gps-dna-tracking-university-of-sheffield</guid>
	<pubDate>Sat, 10 May 2014 04:33:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/10659/gps-dna-tracking-university-of-sheffield</link>
	<title><![CDATA[GPS DNA tracking - University of Sheffield]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/Aap-s1kle4Q" frameborder="0" allowfullscreen></iframe>University of Sheffield geneticist and bioinformatics expert Dr Eran Elhaik demonstrates the power of his new DNA research, which allows people to discover their genetic homeland from 1000 years ago. Find out more about our biological research here http://www.sheffield.ac.uk/aps]]></description>
	
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44318/proksee-in-depth-characterization-and-visualization-of-bacterial-genomes</guid>
	<pubDate>Tue, 09 May 2023 19:38:52 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44318/proksee-in-depth-characterization-and-visualization-of-bacterial-genomes</link>
	<title><![CDATA[Proksee: in-depth characterization and visualization of bacterial genomes]]></title>
	<description><![CDATA[<p><span>Proksee is an expert system for genome assembly, annotation and visualization. To begin using Proksee, provide a complete genome sequence, sequencing reads or a CGView/Proksee map JSON file.</span></p><p>Address of the bookmark: <a href="https://proksee.ca/" rel="nofollow">https://proksee.ca/</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44655/ngenomesyn-an-easy-to-use-and-flexible-tool-for-publication-ready-visualization-of-syntenic-relationships-across-multiple-genomes</guid>
	<pubDate>Tue, 10 Sep 2024 04:54:55 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44655/ngenomesyn-an-easy-to-use-and-flexible-tool-for-publication-ready-visualization-of-syntenic-relationships-across-multiple-genomes</link>
	<title><![CDATA[NGenomeSyn: an easy-to-use and flexible tool for publication-ready visualization of syntenic relationships across multiple genomes]]></title>
	<description><![CDATA[<p>NGenomeSyn: an easy-to-use and flexible tool for publication-ready visualization of syntenic relationships across multiple genomes&nbsp;</p>
<p><img src="https://github.com/hewm2008/NGenomeSyn/raw/main/Example/example2/OUT3.png" alt="image" style="border: 0px;"></p>
<p><span>NGenomeSyn [multiple (N) Genome Synteny], for publication-ready visualization of syntenic relationships of the whole genome or local region and genomic features (e.g. repeats, structural variations, genes) across multiple genomes with a high customization. NGenomeSyn provides an easy way for its users to visualize a large amount of data with a rich layout by simply adjusting options for moving, scaling, and rotation of target genomes. Moreover, NGenomeSyn could be applied on the visualization of relationships on non-genomic data with similar input formats.</span></p>
<p>https://academic.oup.com/bioinformatics/article/39/3/btad121/7072460</p><p>Address of the bookmark: <a href="https://github.com/hewm2008/NGenomeSyn" rel="nofollow">https://github.com/hewm2008/NGenomeSyn</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>

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