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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/27463?offset=550</link>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/12988/guest-lecturer-molecular-biology-bioinformatics</guid>
  <pubDate>Wed, 23 Jul 2014 13:34:41 -0500</pubDate>
  <link></link>
  <title><![CDATA[Guest Lecturer - Molecular Biology &amp; Bioinformatics]]></title>
  <description><![CDATA[
<p>Adv. No. F.TU/ACA/GT-APP/01/14 Date: 07.07.2014</p>

<p>Faculty of Science</p>

<p>Essential Qualifications:</p>

<p>(i) Good academic record having 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>(II) Besides fulfilling the above qualifications, the candidates 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>(III) Notwithstanding anything contained in sub-clauses (i) and (ii) of clause 4.4.1 of UGC regulations 2010, 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 engagement of guest Teacher.</p>

<p>(IV) NET/ SLET/ SET shall also not be required for such Master’s Degree Programmes in discipline for which NET/ SLET/ SET is not conducted.</p>

<p>Application form along with detailed instructions can be downloaded from Tripura University website: www.tripurauniv.in. The duly filled in application forms complete in all respects may be sent so as to reach the Office of the Deputy Registrar Academic Branch, Tripura University, Suryamaninagar - 799022, Tripura on or before 31st July, 2014. The Candidates who responded against advertisement No. TU.REG/N-Advt./02/10 dated 20.02.2014 need not apply again.</p>

<p>For more info visit: http://www.tripurauniv.in/images/universitymedia/EmploymentNotification/Guest%20Teacher%20Advt.%20website_09072014.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36905/d-genies-a-tool-for-dotplot-large-genomes-in-an-interactive-efficient-and-simple-way</guid>
	<pubDate>Mon, 11 Jun 2018 09:41:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36905/d-genies-a-tool-for-dotplot-large-genomes-in-an-interactive-efficient-and-simple-way</link>
	<title><![CDATA[D-GENIES: A tool for Dotplot large Genomes in an Interactive, Efficient and Simple way]]></title>
	<description><![CDATA[D-GENIES – for Dotplot large Genomes in an Interactive, Efficient and Simple way – is an online tool designed to compare two genomes. It supports large genome and you can interact with the dot plot to improve the visualisation.

We use minimap version 2 to align the two genomes. Then, the PAF file is parsed and plotted into an interactive plot written with d3.js library.

D-Genies also allows to display dot plots from other aligners by uploading their PAF or MAF alignment file.

http://dgenies.toulouse.inra.fr/<p>Address of the bookmark: <a href="http://dgenies.toulouse.inra.fr/" rel="nofollow">http://dgenies.toulouse.inra.fr/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/14215/the-8000-years-old-tibetian-gene-mutation</guid>
	<pubDate>Wed, 20 Aug 2014 21:57:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/14215/the-8000-years-old-tibetian-gene-mutation</link>
	<title><![CDATA[The 8000 years old Tibetian gene mutation !!!]]></title>
	<description><![CDATA[<p>A new study has provided insight into how gene mutation around 8,000 years ago helped Tibetans' to survive in the thin air on the Tibetan Plateau, where an average elevation is of 14,800 feet.<br /><br />A study led by University of Utah scientists is the first to find a genetic cause for the adaptation, a single DNA base pair change that dates back 8,000 years and demonstrate how it contributes to the Tibetans' ability to live in low oxygen conditions.</p><p>About 8,000 years ago, the gene EGLN1 changed by a single DNA base pair. Today, a relatively short time later on the scale of human history, 88 percent of Tibetans have the genetic variation, and it was virtually absent from closely related lowland Asians. The findings indicate the genetic variation endows its carriers with an advantage.<br /><br />In those without the adaptation, low oxygen caused their blood to become thick with oxygen-carrying red blood cells, an attempt to feed starved tissues, which could cause long-term complications such as heart failure. The researchers found that the newly identified genetic variation protected Tibetans by decreasing the over-response to low oxygen.</p><p>Reference: http://www.nature.com/nature/journal/v512/n7513/abs/nature13408.html</p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37259/epiviz-an-interactive-visualization-tool-for-functional-genomics-data</guid>
	<pubDate>Mon, 09 Jul 2018 05:27:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37259/epiviz-an-interactive-visualization-tool-for-functional-genomics-data</link>
	<title><![CDATA[Epiviz: an interactive visualization tool for functional genomics data.]]></title>
	<description><![CDATA[<p><span>Epiviz is an interactive visualization tool for functional genomics data. It supports genome navigation like other genome browsers, but allows multiple visualizations of data within genomic regions using scatterplots, heatmaps and other user-supplied visualizations. It also includes data from the&nbsp;</span><a href="http://barcode.luhs.org/" target="_blank">Gene Expression Barcode project</a><span>&nbsp;for transcriptome visualization. It has a flexible plugin framework so users can add</span><a href="http://d3js.org/" target="_blank">d3</a><span>&nbsp;visualizations. You can see a video tour&nbsp;</span><a href="http://youtu.be/099c4wUxozA" target="_blank">here</a><span>.</span></p>
<p><span>https://bioconductor.org/packages/release/bioc/html/epivizr.html</span></p>
<p><span>https://github.com/epiviz</span></p>
<p><span>https://github.com/epiviz/epiviz</span></p><p>Address of the bookmark: <a href="https://epiviz.github.io/" rel="nofollow">https://epiviz.github.io/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/12936/assistant-professor-medical-bioinformatics</guid>
  <pubDate>Wed, 23 Jul 2014 05:00:38 -0500</pubDate>
  <link></link>
  <title><![CDATA[Assistant Professor - Medical Bioinformatics]]></title>
  <description><![CDATA[
<p>Advt. No : ME-I/A-IV/03/14</p>

<p>No.of Posts:01 (SC)</p>

<p>Pay Scale:</p>

<p>Pay Band of Rs.15600-39100 + Rs.6000/- GP +NPA @ 25% of Basic Pay +Learning Resource Allowance @ Rs.20,000/-P.A.+ Conveyance Allowance @ Rs. 1650/-P.M.+ Academic Allowance @ Rs.2500/- P.M. and other admissible allowances.</p>

<p>Qualifications:</p>

<p>Area of Specialization:-</p>

<p>Bioinformatics/Computational/Biology/Genomics/ Proteomics/ Structural Biology</p>

<p>1. Postgraduate qualification, e.g. Master’s Degree in Biotechnology/Bioinformatics/ Biophysics.</p>

<p>2. A Doctorate Degree of recognized University/Institute in a basic or allied Medical Science subject e.g. Medical Biotechnology/Biophysics. Bioinformatics/X-ray Crystallography/</p>

<p>Immunology/Structural Biology etc</p>

<p>Experience:</p>

<p>1.Minimum three years teaching and/or research experience in a recognized medical/research Institution in an allied medical subject after obtaining doctorate degree and preferably in Medical</p>

<p>Molecular Biology/ Biophysics/Structural Biology/Genomics and Clinical Proteomics/Computational Biology.</p>

<p>2. Minimum two publication with atleast one in international journal and atleast one as first author</p>

<p>Desirable:-</p>

<p>Consistently excellent scholastic/academic record, demonstrated ability to write grant proposal/(s) successfully, Post Doctoral training in a frontier area of medical Bioinformatics Research and of direct relevance to clinical diagnosis or patient care (preferably from a recognized top-ranking medical institution abroad)</p>

<p>Send your applications to O/O, Deputy Registrar, Recruitment &amp; Establishment Cell, University of Health Sciences, Rohtak by 08.7.2014</p>

<p>For more details,please visit website:http://pgimsrohtak.nic.in/2014%20AP%20Advt.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37524/fmlrc-a-long-read-error-correction-tool-using-the-multi-string-burrows-wheeler-transform</guid>
	<pubDate>Fri, 10 Aug 2018 13:29:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37524/fmlrc-a-long-read-error-correction-tool-using-the-multi-string-burrows-wheeler-transform</link>
	<title><![CDATA[FMLRC: a long-read error correction tool using the multi-string Burrows Wheeler Transform]]></title>
	<description><![CDATA[<p><span>FMLRC, or FM-index Long Read Corrector, is a tool for performing hybrid correction of long read sequencing using the BWT and FM-index of short-read sequencing data. Given a BWT of the short-read sequencing data, FMLRC will build an FM-index and use that as an implicit de Bruijn graph. Each long read is then corrected independently by identifying low frequency k-mers in the long read and replacing them with the closest matching high frequency k-mers in the implicit de Bruijn graph. In contrast to other de Bruijn graph based implementations, FMLRC is not restricted to a particular k-mer size and instead uses a two pass method with both a short "k-mer" and a longer "K-mer". This allows FMLRC to correct through low complexity regions that are computational difficult for short k-mers.</span></p><p>Address of the bookmark: <a href="https://github.com/holtjma/fmlrc" rel="nofollow">https://github.com/holtjma/fmlrc</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/13025/the-5-reasons-to-mistakes-at-bioinformatics-work</guid>
	<pubDate>Thu, 24 Jul 2014 02:51:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/13025/the-5-reasons-to-mistakes-at-bioinformatics-work</link>
	<title><![CDATA[The 5 reasons to mistakes at bioinformatics work !!!]]></title>
	<description><![CDATA[<p>When you're just starting out with biological programming, it's easy to run into complex problems that make you wonder how anyone has ever managed to write a program. There are some problems that trip up nearly every bioinformatician--everything from getting started understanding the biological problems to dealing with program design. Some random mistakes are so prominent that even experienced biological programmers do it. The 8 years in bioinformatics and my few random observations, most of them are snarky. These reasons will always take longer than expected and compel you to postpone your project deadline.</p><p><strong>1.Stupid for biologist:</strong> Biology is so complex that it will make bioinformatician feel stupid. There are no any universal fixed rules; it can surprise you any time. So be nice to biologists who ask questions and resolve your biological puzzles. Sometime you will have no idea what the hell you were doing either.<br /><br /><strong>2.Puzzling why:</strong> Do not hesitate to ask question. Especially. at the beginning of project you will have to ask a lot of questions. Instead of puzzling it out at end check out and clear your doubt even for a single error. It may can leads to wrong conclusion.<br /><br /><strong>3.Running marathon:</strong> The most of the biological software&rsquo;s documentation is always incomplete. In other word they are no more than 95 percent complete. Sometime a single problem can halt your entire project for months. Compilation and running the pipelines in tedious because almost all are interdependent and need proper configuration. I face the same kind of problem with Evolver :( &hellip; <br /><br /><strong>4.Folders missing:</strong> The pipelines generate lots of data, and we keep them in several folders for future use. But sometime we delete them by mistake and move to recovery&hellip;<br /><br /><strong>5.Digging deeper:</strong> Digging deeper is fruitful, but some time it can be catastrophic. You may get frustrated or direction less. So keep a biologist with you for rescue &hellip;. Sometime an expert computer programmer to handle your server. Remember, the server will always go down when you need it the most.<br /><br />The most common frustrating&nbsp; common line: Why do we do this again?</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37672/seqmonka-tool-to-visualise-and-analyse-high-throughput-mapped-sequence-data</guid>
	<pubDate>Tue, 11 Sep 2018 04:39:38 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37672/seqmonka-tool-to-visualise-and-analyse-high-throughput-mapped-sequence-data</link>
	<title><![CDATA[SeqMonk:A tool to visualise and analyse high throughput mapped sequence data]]></title>
	<description><![CDATA[<p>SeqMonk is a program to enable the visualisation and analysis of mapped sequence data. It was written for use with mapped next generation sequence data but can in theory be used for any dataset which can be expressed as a series of genomic positions. It's main features are:</p>
<ul>
<li>Import of mapped data from mapped data (BAM/SAM/bowtie etc)</li>
<li>Creation of data groups for visualisation and analysis</li>
<li>Visualisation of mapped regions against an annotated genome.</li>
<li>Flexible quantitation of the mapped data to allow comparisons between data sets</li>
<li>Statistical analysis of data to find regions of interest</li>
<li>Creation of reports containing data and genome annotation</li>
</ul><p>Address of the bookmark: <a href="http://www.bioinformatics.babraham.ac.uk/projects/seqmonk/" rel="nofollow">http://www.bioinformatics.babraham.ac.uk/projects/seqmonk/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/13337/phd-opportunity-at-universite-de-liege-belgium</guid>
  <pubDate>Sat, 02 Aug 2014 01:12:43 -0500</pubDate>
  <link></link>
  <title><![CDATA[PhD opportunity at Université de Liège - Belgium]]></title>
  <description><![CDATA[
<p>PhD opportunity at Université de Liège - Belgium</p>

<p>The Bioinformatics and Systems Biology Unit of Université de Liège (Belgium) is looking for a highly motivated master student with programming skills for a PhD thesis project (4 years, fully funded) with the goal of designing computational tools that use literature, genomic and structural data in order to infer regulatory and metabolic networks.  </p>

<p>Applicants are invited to send their resume and a recommendation letter to Prof. Patrick Meyer (more details at   www.biosys.ulg.ac.be )</p>

<p>For more information : www.biosys.ulg.ac.be</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37837/clipcrop-a-tool-for-detecting-structural-variations-with-single-base-resolution-using-soft-clipping-information</guid>
	<pubDate>Thu, 04 Oct 2018 16:39:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37837/clipcrop-a-tool-for-detecting-structural-variations-with-single-base-resolution-using-soft-clipping-information</link>
	<title><![CDATA[ClipCrop: a tool for detecting structural variations with single-base resolution using soft-clipping information]]></title>
	<description><![CDATA[<p>This is a tool for detecting structural variations using soft-clipping information From&nbsp;<a href="http://samtools.sourceforge.net/SAM1.pdf">SAM</a>&nbsp;files.</p>
<p>https://github.com/shinout/clipcrop</p><p>Address of the bookmark: <a href="https://github.com/shinout/clipcrop" rel="nofollow">https://github.com/shinout/clipcrop</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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