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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/30149?offset=1090</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44581/biokit-a-set-of-tools-dedicated-to-bioinformatics-data-visualisation</guid>
	<pubDate>Tue, 18 Jun 2024 02:04:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44581/biokit-a-set-of-tools-dedicated-to-bioinformatics-data-visualisation</link>
	<title><![CDATA[BioKit: a set of tools dedicated to bioinformatics, data visualisation]]></title>
	<description><![CDATA[<p><span>BioKit is a set of tools dedicated to bioinformatics, data visualisation (</span><a href="https://biokit.readthedocs.io/en/latest/references.html#module-biokit.viz" title="biokit.viz"><code><span>biokit.viz</span></code></a><span>), access to online biological data (e.g. UniProt, NCBI thanks to bioservices). It also contains more advanced tools related to data analysis (e.g.,&nbsp;</span><a href="https://biokit.readthedocs.io/en/latest/references.html#module-biokit.stats" title="biokit.stats"><code><span>biokit.stats</span></code></a><span>). Since R is quite common in bioinformatics, we also provide a convenient module to run R inside your Python scripts or shell (:mod:biokit.rtools module).</span></p><p>Address of the bookmark: <a href="https://biokit.readthedocs.io/en/latest/index.html" rel="nofollow">https://biokit.readthedocs.io/en/latest/index.html</a></p>]]></description>
	<dc:creator>Neel</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>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/4590/tigers-genome-sequenced</guid>
	<pubDate>Tue, 17 Sep 2013 16:48:24 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/4590/tigers-genome-sequenced</link>
	<title><![CDATA[Tigers genome sequenced]]></title>
	<description><![CDATA[<p>Fifteen scientists led by Dr Jong Bhak of Genome Research Foundation, South Korea, decoded as many as 3 billion nucleotides (organic molecules that form the basic building blocks of nucleic acids, such as DNA). They identified 20,000 genes related to various functions of the tiger.&nbsp;</p><p>The biggest and perhaps most fearsome of the world's big cats, the tiger, shares 95.6 percent of its DNA with humans' cute and furry companions, domestic cats.</p><p>The new research showed that big cats have genetic mutations that enabled them to be carnivores. The team also identified mutations that allow snow leopards to thrive at high altitudes.</p><p>Reference:</p><p><a href="http://www.nbcnews.com/science/your-cat-ferocious-tigers-share-lot-95-6-percent-their-4B11182690">http://www.nbcnews.com/science/your-cat-ferocious-tigers-share-lot-95-6-percent-their-4B11182690</a></p><p><a href="http://timesofindia.indiatimes.com/home/environment/flora-fauna/Gene-mapping-of-tiger-completed/articleshow/22671681.cms">http://timesofindia.indiatimes.com/home/environment/flora-fauna/Gene-mapping-of-tiger-completed/articleshow/22671681.cms</a></p><p>Paper:</p><p><a href="http://www.nature.com/ncomms/2013/130917/ncomms3433/full/ncomms3433.html">http://www.nature.com/ncomms/2013/130917/ncomms3433/full/ncomms3433.html</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
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	<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>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34443/opera-an-optimal-genome-scaffolding-program</guid>
	<pubDate>Mon, 27 Nov 2017 10:18:20 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34443/opera-an-optimal-genome-scaffolding-program</link>
	<title><![CDATA[Opera: An optimal genome scaffolding program]]></title>
	<description><![CDATA[<p><span>Opera (Optimal Paired-End Read Assembler) is a sequence assembly program (</span><a href="http://en.wikipedia.org/wiki/Sequence_assembly" target="_blank">http://en.wikipedia.org/wiki/Sequence_assembly&nbsp;<img src="https://a.fsdn.com/con/img/icons/external_asset.png" alt="image" style="border: 0px;"></a><span>). It uses information from paired-end or long reads to optimally order and orient contigs assembled from shotgun-sequencing reads.</span><br><br><span>An updated version called OPERA-LG has been re-engineered with features for the assembly of large and complex genomes.</span><br><br><span>Song Gao, Denis Bertrand, Burton K. H. Chia and Niranjan Nagarajan. OPERA-LG: efficient and exact scaffolding of large, repeat-rich eukaryotic genomes with performance guarantees. Genome Biology, May 2016, doi: 10.1186/s13059-016-0951-y.</span><br><br><span>Song Gao, Wing-Kin Sung, Niranjan Nagarajan. Opera: reconstructing optimal genomic scaffolds with high-throughput paired-end sequences. Journal of Computational Biology, Sept. 2011, doi:10.1089/cmb.2011.0170.</span></p>
<p><span>https://genomebiology.biomedcentral.com/articles/10.1186/s13059-016-0951-y</span></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/operasf/" rel="nofollow">https://sourceforge.net/projects/operasf/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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<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>
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	<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/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>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34567/jobtree-based-python-wrapper-to-run-the-genome-simulation-tool-suite-evolver</guid>
	<pubDate>Fri, 08 Dec 2017 16:26:32 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34567/jobtree-based-python-wrapper-to-run-the-genome-simulation-tool-suite-evolver</link>
	<title><![CDATA[jobTree based python wrapper to run the genome simulation tool suite Evolver]]></title>
	<description><![CDATA[<p><span>evolverSimControl</span><span>&nbsp;(</span><span>eSC</span><span>) can be used to simulate multi-chromosome genome evolution on an arbitrary phylogeny (</span><a href="http://evolution.genetics.washington.edu/phylip/newicktree.html">Newick format</a><span>). In addition to simply running evolver,&nbsp;</span><span>eSC</span><span>&nbsp;also automatically creates statistical summaries of the simulation as it runs including text and image files. Also included are convenience scripts to: check on a running simulation and see detailed status and logging information; extract fasta sequence files from the leaf nodes of a completed simulation; extract pairwise multiple alignment files (</span><a href="http://genome.ucsc.edu/FAQ/FAQformat.html#format5">.maf</a><span>) from leaf and branch nodes from a completed simulation and with the help of&nbsp;</span><a href="https://github.com/dentearl/mafTools/">mafJoin</a><span>, join them together into a single maf covering the entire simulation.</span></p><p>Address of the bookmark: <a href="https://github.com/dentearl/evolverSimControl" rel="nofollow">https://github.com/dentearl/evolverSimControl</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/10741/managing-and-analyzing-next-generation-sequence-data</guid>
	<pubDate>Sat, 10 May 2014 06:28:06 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/10741/managing-and-analyzing-next-generation-sequence-data</link>
	<title><![CDATA[Managing and Analyzing Next-Generation Sequence Data]]></title>
	<description><![CDATA[<p>Centralized Bioinformatics Core Facilities provide shared resources for the computational and IT requirements of the investigators in their department or institution. As such, they must be able to effectively react to new types of experimental technology. Recently faced with an unprecedented flood of data generated by the next generation of DNA sequencers, these groups found it necessary to respond quickly and efficiently to the informatics and infrastructure demands. Centralized Facilities newly facing this challenge need to anticipate time and design considerations of necessary components, including infrastructure upgrades, staffing, and tools for data analyses and management ...</p>
<p>More at http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1000369</p><p>Address of the bookmark: <a href="http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1000369" rel="nofollow">http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1000369</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
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