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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/28303?offset=680</link>
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	<description><![CDATA[]]></description>
	
	
<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/8108/jrf-institute-of-cytology-preventive-oncology</guid>
  <pubDate>Sat, 01 Feb 2014 13:47:29 -0600</pubDate>
  <link></link>
  <title><![CDATA[JRF @ Institute of Cytology &amp; Preventive Oncology]]></title>
  <description><![CDATA[
<p>Institute of Cytology &amp; Preventive Oncology (ICPO) which was initially established as Cytology Research Centre ( CRC ) by the Indian Council of Medical Research (ICMR) in 1979, came into the existence in 1989 when CRC was elevated to the level of Institute. ICPO was instituted with the main aim of promoting research in the field of cancers that are most prevalent in India with an emphasis on their early detection and prevention.</p>

<p>Candidates having the below mentioned qualifications may appear for Walk in Interview at ICPO on 5th Feb 2014 between 10.00 AM and 12.00 PM under the NIF project entitled "Prediction of drug tragets of chemical constituents present within non-codified medicinal plants" under Dr Subhash M.Agarwal, Scientist C</p>

<p>    Position : JRF<br />    No of Post : One<br />    Pay : Rs 12000/- + 30% HRA </p>

<p>    Desired Profile : M.Sc in Bioinformatics with good academic record. Candidate with experience in database development and scripting would be preferred<br />    Age Limit : Below 28 years<br />    Period : 2 months</p>

<p>Interested candidates may send their applications with bio-data by email (smagarwal@gmail.com) or post addressed to Dr Subhash M Agarwal, Scientist C, Bioinformatics Division, Institute of Cytology and Preventive Oncology (ICPO) I-7, Sector 39, Noida-201301 so as to reach latest by 04.02.14</p>

<p>Deadline : 04.02.14</p>

<p>http://icmr.nic.in/icmrnews/icpo_jrf.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/37411/my-commonly-used-commands-in-bioinformatics</guid>
	<pubDate>Thu, 26 Jul 2018 04:58:45 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/37411/my-commonly-used-commands-in-bioinformatics</link>
	<title><![CDATA[My commonly used commands in Bioinformatics]]></title>
	<description><![CDATA[<p>FYI, I've found it useful to use MUMmer to extract the specific changes that Racon makes, so I can evaluate them individually:</p><pre><code>minimap -t 24 assembly.fasta long_reads.fastq.gz | racon -t 24 long_reads.fastq.gz - assembly.fasta racon_assembly.fasta
nucmer -p nucmer assembly.fasta racon_assembly.fasta
show-snps -C -T -r nucmer.delta
</code></pre><p>This reports Racon's changes in a table. You can exclude indels with the&nbsp;<code>-I</code>&nbsp;option in&nbsp;<code>show-snps</code>.&nbsp;</p><p>This process (Racon -&gt; MUMmer -&gt; SNP table) solves the problem I originally raised in this issue. So as far as I'm concerned, you can close this issue (or keep it open if you still want to implement some kind of variant table).</p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/8385/peng-lab</guid>
  <pubDate>Tue, 18 Feb 2014 13:53:46 -0600</pubDate>
  <link></link>
  <title><![CDATA[Peng Lab]]></title>
  <description><![CDATA[
<p>Peng Lab at Janelia Farm Research Campus, Howard Hughes Medical Institute focuses on data mining for bioinformatics and computational molecular biology, particularly, bioimage data mining and informatics. These bioimages include cellular and molecular images and related medical images. </p>

<p>* Analysis of Gene Expression Pattern Images: high-performance image analysis and mining for different model organisms, such as fruitfly, C. elegans, and mouse;<br />* Feature/Model Learning: developing algorithms and software</p>

<p>Location :Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, USA.</p>

<p>http://research.janelia.org/peng/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38199/pacasus-correction-of-palindromes-in-long-reads-from-pacbio-and-nanopore</guid>
	<pubDate>Mon, 12 Nov 2018 05:26:48 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38199/pacasus-correction-of-palindromes-in-long-reads-from-pacbio-and-nanopore</link>
	<title><![CDATA[Pacasus: Correction of palindromes in long reads from PacBio and Nanopore]]></title>
	<description><![CDATA[<p><br>Tool for detecting and cleaning PacBio / Nanopore long reads after whole genome amplification. Check the poster from the Revolutionizing Next-Generation Sequencing (2nd edition) conference in the source folder:&nbsp;<a href="https://github.com/swarris/Pacasus/blob/master/vib2017.pdf">https://github.com/swarris/Pacasus/blob/master/vib2017.pdf</a>.</p>
<p>The prepint version is found on&nbsp;<a href="http://www.biorxiv.org/content/early/2017/08/09/173872">http://www.biorxiv.org/content/early/2017/08/09/173872</a></p>
<p>It uses the pyPaSWAS framework for sequence alignment (<a href="https://github.com/swarris/pyPaSWAS">https://github.com/swarris/pyPaSWAS</a>)</p><p>Address of the bookmark: <a href="https://github.com/swarris/Pacasus" rel="nofollow">https://github.com/swarris/Pacasus</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/8442/assistant-professor-king-saud-university-riyadh</guid>
  <pubDate>Fri, 21 Feb 2014 05:57:18 -0600</pubDate>
  <link></link>
  <title><![CDATA[Assistant Professor @ King Saud University Riyadh]]></title>
  <description><![CDATA[
<p>Qualifications: Candidates must have a Ph.D. and a strong background in Molecular and Cellular Biology, protein expression, FACS, or computational biology, and ability to work collaboratively.</p>

<p>This position will have a significant focus on providing analytical support for next generation sequencing data analysis – Exome-sequencing, Targetted sequencing as well as high-throughput genotyping on Illumina platform.</p>

<p>Job location:</p>

<p>Genome Research Chair<br />King Saud University, Riyadh-11451<br />KSA</p>

<p>Interested candidate may forward their CV to grcksu@gmail.com</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40531/shasta-long-read-assembler</guid>
	<pubDate>Tue, 14 Jan 2020 06:47:07 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40531/shasta-long-read-assembler</link>
	<title><![CDATA[Shasta long read assembler]]></title>
	<description><![CDATA[<p>The goal of the Shasta long read assembler is to rapidly produce accurate assembled sequence using as input DNA reads generated by&nbsp;<a href="https://nanoporetech.com/">Oxford Nanopore</a>&nbsp;flow cells.</p>
<p>Computational methods used by the Shasta assembler include:</p>
<ul>
<li>Using a&nbsp;<a href="https://en.wikipedia.org/wiki/Run-length_encoding">run-length</a>&nbsp;representation of the read sequence. This makes the assembly process more resilient to errors in homopolymer repeat counts, which are the most common type of errors in Oxford Nanopore reads.</li>
<li>Using in some phases of the computation a representation of the read sequence based on&nbsp;<em>markers</em>, a fixed subset of short k-mers (k &asymp; 10).</li>
</ul>
<p>More at&nbsp;<a href="https://chanzuckerberg.github.io/shasta/index.html">https://chanzuckerberg.github.io/shasta/index.html</a></p><p>Address of the bookmark: <a href="https://github.com/chanzuckerberg/shasta" rel="nofollow">https://github.com/chanzuckerberg/shasta</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/8466/srf-position-in-computational-systems-biology-computational-biology-group-iiit-delhi</guid>
  <pubDate>Sun, 23 Feb 2014 20:56:08 -0600</pubDate>
  <link></link>
  <title><![CDATA[SRF position in Computational Systems Biology Computational biology Group, IIIT-Delhi]]></title>
  <description><![CDATA[
<p>An opportunity to perform research in DST supported project that involves building of mathematical models to understand the functional relationship between circadian rhythms and memory formation under stressful condition.  In this project, mathematical model of circadian rhythms based on gene regulatory mechanisms will be unified with the mathematical model of calcium signal transduction pathway to understand and predict the formation of fear memory under stressful conditions. The research scholar will spend full time on this project to build new models and expected to contribute significantly to prepare the results for publication and presentation, and to contribute to grant proposals. </p>

<p>Required Qualifications: Masters in physics/chemistry/mathematics (or) MTech in bioengineering, chemical (or) Masters in any traditional field of science with outstanding performance throughout the program. Candidate should have cleared GATE/UGC-CSIR examinations. Applicant should have done basic mathematics courses like calculus, differential equations, numerical analysis etc in their degree program and have obtained good grades in those courses. Knowledge of MATLAB and C or at least one traditional programming language is absolutely necessary. Strong inclination to understand biological concepts is a must for this research work as this project is about modeling biological systems.     </p>

<p>Salary: A fixed salary of Rs 18000 PM including HRA will be paid. </p>

<p>Last date for application: This advertisement is open until suitable candidate is found for the project. </p>

<p>Preferred Qualifications:  - Expertise in dynamical systems theory, bifurcation theory, numerical simulations, parameter estimation. </p>

<p>Independence and high motivation for carrying out interdisciplinary research. - Excellent communication skills and ability to work independently. - Good working habits. </p>

<p>Interested candidates should submit both curriculum vitae and statement of interest in PDF format to sriramk@iiitd.ac.in and should clearly mention in the subject "Application for SRF".</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40715/mutatrix-a-population-genome-simulator-which-generates-simulated-genomes</guid>
	<pubDate>Tue, 28 Jan 2020 04:06:58 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40715/mutatrix-a-population-genome-simulator-which-generates-simulated-genomes</link>
	<title><![CDATA[mutatrix: a population genome simulator which generates simulated genomes.]]></title>
	<description><![CDATA[<p><span>genome simulation across a population with zeta-distributed allele frequency, snps, insertions, deletions, and multi-nucleotide polymorphisms</span></p>
<p><span>More at&nbsp;<a href="https://github.com/ekg/mutatrix">https://github.com/ekg/mutatrix</a></span></p>
<pre>./mutatrix -S sample -P test/ -p 2 -n 10 reference.fasta</pre><p>Address of the bookmark: <a href="https://github.com/ekg/mutatrix" rel="nofollow">https://github.com/ekg/mutatrix</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/12868/landry-lab</guid>
  <pubDate>Thu, 17 Jul 2014 14:33:57 -0500</pubDate>
  <link></link>
  <title><![CDATA[Landry Lab]]></title>
  <description><![CDATA[
<p>EVOLUTIONARY AND INTEGRATIVE CELL BIOLOGY</p>

<p>Our research is at the crossroad between cell biology, ecological genomics, systems biology, molecular evolution and population genetics. We study the architecture and evolution of protein and signalling networks.</p>

<p>More at http://landrylab.ibis.ulaval.ca/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/8481/des-higgins-visualizing-multiple-sequence-alignments</guid>
	<pubDate>Wed, 26 Feb 2014 00:50:08 -0600</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/8481/des-higgins-visualizing-multiple-sequence-alignments</link>
	<title><![CDATA[Des Higgins: Visualizing Multiple Sequence Alignments]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/IQkOK3dsWs4" frameborder="0" allowfullscreen></iframe>Copyright Broad Institute, 2013. All rights reserved.
Des Higgins (http://www.bioinf.ucd.ie) gives a very entertaining introduction to the visualization of multiple sequence alignment, and to his widely-used Clustal tool. He highlights the emerging challenge of managing alignments with a very large number of sequences, and presents several approaches to this challenge, including faster algorithms and abstract views of clusters of alignments. This talk was presented at VIZBI 2011, an international conference series on visualizing biological data (http://www.vizbi.org) funded by NIH & EMBO.

For information about data visualization efforts at the Broad Institute, please visit:
http://www.broadinstitute.org/node/1363/]]></description>
	
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