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<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/29638?offset=550</link>
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	<description><![CDATA[]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/28051/convert-ensembl-gtf-to-annotation-table-geneid-genesymbol-genewisechrlocation-geneclass-strand-raw</guid>
	<pubDate>Fri, 24 Jun 2016 18:08:49 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/28051/convert-ensembl-gtf-to-annotation-table-geneid-genesymbol-genewisechrlocation-geneclass-strand-raw</link>
	<title><![CDATA[Convert EnsEMBL GTF to Annotation table (Geneid, GeneSymbol, GeneWiseChrLocation, GeneClass, Strand) Raw]]></title>
	<description><![CDATA[<p><strong>Bash Script source:</strong></p><p>https://gist.github.com/santhilalsubhash/367befcf5216be4b1fd9</p><p>&nbsp;</p><p><strong>Information</strong>:</p><p>This script converts EnsEMBL GTF (Ex:&nbsp;<a href="https://gist.githubusercontent.com/santhilalsubhash/1e7cca357e52a181dc25/raw/cfb803e07900a2baefbb6534f1299fd30cb57a29/sample.GTF">https://gist.githubusercontent.com/santhilalsubhash/1e7cca357e52a181dc25/raw/cfb803e07900a2baefbb6534f1299fd30cb57a29/sample.GTF</a>) file to annotation table format. It generated two files<br />1) Transcript wise chromosome location with information about transcripts (Ex:&nbsp;<a href="https://gist.githubusercontent.com/santhilalsubhash/c7dec516e0338503a4b6/raw/de0af1a39f0005c4ce7321c5ae57fc8b4a14c7f4/sample.GTF_enst_annotation.txt">https://gist.githubusercontent.com/santhilalsubhash/c7dec516e0338503a4b6/raw/de0af1a39f0005c4ce7321c5ae57fc8b4a14c7f4/sample.GTF_enst_annotation.txt</a>)<br />2) Gene wise chromosome location with information about genes (Ex:&nbsp;<a href="https://gist.githubusercontent.com/santhilalsubhash/c92006c5080f0333bec2/raw/d16e0b2440d73b09b486d3c9751cdb248a73fa0b/sample.GTF_ensg_annotation.txt">https://gist.githubusercontent.com/santhilalsubhash/c92006c5080f0333bec2/raw/d16e0b2440d73b09b486d3c9751cdb248a73fa0b/sample.GTF_ensg_annotation.txt</a>)</p><p>Note: You can download GTF files from&nbsp;<a href="http://www.ensembl.org/info/data/ftp/index.html">http://www.ensembl.org/info/data/ftp/index.html</a></p>]]></description>
	<dc:creator>EagleEye</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/7032/computer-experts-in-biotechnology-laboratory</guid>
	<pubDate>Wed, 04 Dec 2013 02:11:43 -0600</pubDate>
	<link>https://bioinformaticsonline.com/file/view/7032/computer-experts-in-biotechnology-laboratory</link>
	<title><![CDATA[Computer experts in biotechnology laboratory]]></title>
	<description><![CDATA[<p>Only bioinformatician can understand that <strong>multiplication</strong> and <strong>division</strong> are different but same thing :)</p><p><span>Disclaimer:</span>&nbsp;This cartoon is solely designed to create humour and fun, not to offend any computer experts.</p>]]></description>
	<dc:creator>Jit</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/7032" length="35726" type="image/gif" />
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	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/37581/comparativegenomics-exercise2</guid>
	<pubDate>Wed, 22 Aug 2018 22:10:56 -0500</pubDate>
	<link>https://bioinformaticsonline.com/file/view/37581/comparativegenomics-exercise2</link>
	<title><![CDATA[ComparativeGenomics Exercise2]]></title>
	<description><![CDATA[<p>COMPARATIVE MICROBIAL GENOMICS ANALYSIS WORKSHOP&nbsp; @&nbsp;cbs.dtu.dk</p><p>Free Bioinformatics workbench https://www.mn.uio.no/ifi/english/research/networks/clsi/earlier_seminars/2012/tammivesth_osloseminarfinal.pdf</p>]]></description>
	<dc:creator>Neel</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/37581" length="139956" type="application/pdf" />
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/6380/hidden-markov-models-viterbi-algorithm-markov-chain-exploration-with-script</guid>
	<pubDate>Thu, 14 Nov 2013 13:36:56 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/6380/hidden-markov-models-viterbi-algorithm-markov-chain-exploration-with-script</link>
	<title><![CDATA[Hidden Markov Models, Viterbi Algorithm, Markov Chain Exploration with script]]></title>
	<description><![CDATA[<p><strong>Hidden Markov Models, the Viterbi Algorithm, and CpG Islands (in VB6)</strong></p><p><strong>Problem :</strong></p><p>The CG island is a stretch of DNA (usually longer than 200 bases) in which the frequency of the CG sequence is higher than other regions. It is also called the CpG island, where "p" simply indicates that "C" and "G" are connected by a phosphodiester bond.<br /><br />CpG islands are often located around the promoters of housekeeping genes (which are essential for general cell functions) or other genes frequently expressed in a cell. At these locations, the CG sequence is not methylated. By contrast, the CG sequences in inactive genes are usually methylated to suppress their expression. The methylated cytosine may be converted to thymine by accidental deamination. Unlike the cytosine to uracil mutation which is efficiently repaired, the cytosine to thymine mutation can be corrected only by the mismatch repair which is very inefficient. Hence, over evolutionary time scales, the methylated CG sequence will be converted to the TG sequence.</p><p>Find step wise explanationand implementation steps at <a href="http://dna.cs.byu.edu/bio465/Labs/hmm.shtml">http://dna.cs.byu.edu/bio465/Labs/hmm.shtml</a></p><p>Source code with explanation <a href="http://www.tannerhelland.com/1187/hidden-markov-models-viterbi-algorithm-cpg-islands-in-vb6/">http://www.tannerhelland.com/1187/hidden-markov-models-viterbi-algorithm-cpg-islands-in-vb6/</a></p><p>Fore detail understanding of HMM read this excellent tutorial <a href="http://www.cs.ubc.ca/~murphyk/Software/HMM/labman2.pdf">http://www.cs.ubc.ca/~murphyk/Software/HMM/labman2.pdf</a></p><p>Viterbi Algo at <a href="http://en.wikipedia.org/wiki/Viterbi_path">http://en.wikipedia.org/wiki/Viterbi_path</a></p><p>For firther reading Wiki page <a href="http://en.wikipedia.org/wiki/Hidden_Markov_model">http://en.wikipedia.org/wiki/Hidden_Markov_model</a></p><p>On CpG island paper and for indepth understanding <a href="http://www.biomedcentral.com/1471-2164/12/S2/S10">http://www.biomedcentral.com/1471-2164/12/S2/S10</a></p><p>&nbsp;</p><p>If you are more interested in exploring&nbsp;Markov Chain Exploration and understand it with graphical version please visit <a href="http://www.planet-source-code.com/vb/scripts/ShowCode.asp?txtCodeId=75049&amp;lngWId=1">http://www.planet-source-code.com/vb/scripts/ShowCode.asp?txtCodeId=75049&amp;lngWId=1</a></p><p>Reference:</p><p>1.<a href="http://www.planet-source-code.com/vb/scripts/ShowCode.asp?txtCodeId=75049&amp;lngWId=1">http://www.planet-source-code.com</a></p><p>2. <a href="http://www.tannerhelland.com/1187/hidden-markov-models-viterbi-algorithm-cpg-islands-in-vb6/">http://www.tannerhelland.com</a></p>]]></description>
	<dc:creator>Manisha Mishra</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37957/base-a-practical-de-novo-assembler-for-large-genomes-using-long-ngs-reads</guid>
	<pubDate>Fri, 19 Oct 2018 07:25:21 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37957/base-a-practical-de-novo-assembler-for-large-genomes-using-long-ngs-reads</link>
	<title><![CDATA[BASE: a practical de novo assembler for large genomes using long NGS reads]]></title>
	<description><![CDATA[<p><span>new&nbsp;</span><em>de novo</em><span>&nbsp;assembler called BASE. It enhances the classic seed-extension approach by indexing the reads efficiently to generate adaptive seeds that have high probability to appear uniquely in the genome. Such seeds form the basis for BASE to build extension trees and then to use reverse validation to remove the branches based on read coverage and paired-end information, resulting in high-quality consensus sequences of reads sharing the seeds. Such consensus sequences are then extended to contigs.</span></p><p>Address of the bookmark: <a href="https://github.com/dhlbh/BASE" rel="nofollow">https://github.com/dhlbh/BASE</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/6562/molecular-bioinformatics-lab-mbl</guid>
  <pubDate>Tue, 19 Nov 2013 18:23:27 -0600</pubDate>
  <link></link>
  <title><![CDATA[Molecular Bioinformatics Lab (MBL)]]></title>
  <description><![CDATA[
<p>The main subject of interest in our laboratory is the study of the relationship among sequence, structure, and function in proteins and nucleic acids. Our research can be divided in two major topics:</p>

<p>the study of the sequence-structure relationship<br />(application -&gt; structure prediction)<br />the study of the structure-function relationship<br />(application -&gt; function prediction)</p>

<p>Therefore, anything related to the configuration (sequence) and conformation (structure) in atomic systems of proteins and nucleic acids, and the interaction of these with other elements (function) is of our major interest.</p>

<p>Lab page @ http://melolab.org/mbl/</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/38618/canu-genome-assembly-parameters</guid>
	<pubDate>Mon, 07 Jan 2019 08:40:37 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/38618/canu-genome-assembly-parameters</link>
	<title><![CDATA[CANU genome assembly parameters !]]></title>
	<description><![CDATA[<p>Choose the appropriate parameters to run Canu and run it. The assembly will take about an hour. You can use two cores (parameter&nbsp;<code>-maxThreads=2</code>) and you would like to disable cluster option, since we compute on a single Amazon server set off the option to compute on cluster&nbsp;<code>useGrid=false</code>. This specifications should be for your project discussed with a local computing guru. The parameters that are in square brackets&nbsp;<code>[]</code>&nbsp;are optional, symbol&nbsp;<code>|</code>&nbsp;stands for "or".</p><pre><code>usage:   canu [-correct | -trim | -assemble | -trim-assemble] \
              [-s ] \
               -p  \
               -d  \
               genomeSize=[g|m|k] \
               -maxThreads=2 \
               useGrid=false \
              [other-options] \
               read_file.fastq.gz
</code></pre><p>A default&nbsp;<code>Canu</code>&nbsp;run produces usually high quality assembly, example of a command that was used for testing can be found below. However, there are still a lot of parameters that are possible to tweak. For example if we desire to assemble haplotypes separately of if we want to smash them together, we can alternate the error correction process.</p><pre><code>canu -p test_asmbl \
     -d asm_test3 \
     genomeSize=2m \
     -maxThreads=2 useGrid=false \
     -pacbio-raw \ ~/pacbio/dna/sample_reads.fastq.gz</code></pre><p>There is a brilliant&nbsp;<a href="http://canu.readthedocs.io/en/latest/faq.html#what-parameters-can-i-tweak">section in documentation</a>&nbsp;about parameter tweaking.</p><p>The output directory contains will contain many files. The most interesting ones are:</p><ul>
<li><code>*.correctedReads.fasta.gz</code>&nbsp;: file containing the input sequences after correction, trim and split based on consensus evidence.</li>
<li><code>*.trimmedReads.fastq</code>&nbsp;: file containing the sequences after correction and final trimming</li>
<li><code>*.layout</code>&nbsp;: file containing informations about read inclusion in the final assembly</li>
<li><code>*.gfa</code>&nbsp;: file containing the assembly graph by Canu</li>
<li><code>*.contigs.fasta</code>&nbsp;: file containing everything that could be assembled and is part of the primary assembly</li>
</ul><p>The basic stats of assembly can be read from reports generated by the assembler, or calculated using standard UNIX command line tools.</p><p>More at&nbsp;https://canu.readthedocs.io/en/latest/faq.html</p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/6818/scientist-positions-gujarat-state-biotechnology-mission</guid>
  <pubDate>Mon, 25 Nov 2013 10:26:39 -0600</pubDate>
  <link></link>
  <title><![CDATA[Scientist Positions @ Gujarat State Biotechnology Mission]]></title>
  <description><![CDATA[
<p>Gujarat State Biotechnology Mission invite applications [Online Only] under various projects* namely Gujarat Biodiversity Gene Bank (BioGene), Gujarat Institute of Genomics (GIG), Gujarat Institute of Bioinformatics [GIBS] and Gujarat Institute of Marine Biotechnology. Eligible candidates can Apply through online application portal.</p>

<p>1 Scientist E 3</p>

<p>50,000/-</p>

<p>M.Sc. in Life sciences or Plant Sciences or Biotechnology or Microbiology or Bioinformatics or Ph.D. from a recognized university in any of above subject.</p>

<p>Minimum 8 Yrs. of experience after M.Sc. or 5 Yrs. of experience after Ph.D. in responsible position of work in R &amp; D in the area of genomics/ conservation biotechnology/bioinformatics/Planning/Scientific Administration in Science and technology organization. Highly qualified in the area of modern biology, as evidenced through research experience and proven ability to carry out work in the area of conservation biotechnology. Age limit not exceeding 40yrs.</p>

<p>2 Scientist B 6</p>

<p>30,000/-</p>

<p>M.Sc. in Life sciences or Plant Sciences or Biotechnology or Microbiology or Bioinformatics or Ph.D. from a recognized university in any of above subject shall be preferred.</p>

<p>Minimum 3 Yrs. of experience after M.Sc. in responsible position of work in R &amp; D in the area of genomics/ conservation biotechnology/ bioinformatics /Planning/Scientific Administration in Science and technology organization. Highly qualified in the area of modern biology, as evidenced through research experience and proven ability to carry out work in the area of conservation biotechnology. Age limit not exceeding 35yrs.</p>

<p>The positions are purely on contractual basis for 11 months. Interested candidates can apply online in specified format available at "http://leogen.in/recruit/" The last date of applying is 24th December, 2013. Applications must be submitted online only. Applications submitted in any other format except online prescribed performa will be rejected. Candidates in service must apply through proper channel. Candidates will be required to provide original documents along with duly filled and signed application Performa, as and when called for interview.</p>

<p>For more details please visit the website URL : http://leogen.in/recruit</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40208/ragoo-fast-reference-guided-scaffolding-of-genome-assembly-contigs</guid>
	<pubDate>Sun, 27 Oct 2019 00:57:23 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40208/ragoo-fast-reference-guided-scaffolding-of-genome-assembly-contigs</link>
	<title><![CDATA[RaGOO: Fast Reference-Guided Scaffolding of Genome Assembly Contigs]]></title>
	<description><![CDATA[<p>Alonge M, Soyk S, Ramakrishnan S, Wang X, Goodwin S, Sedlazeck FJ, Lippman ZB, Schatz MC:&nbsp;<a href="https://www.biorxiv.org/content/early/2019/01/13/519637">Fast and accurate reference-guided scaffolding of draft genomes</a>.&nbsp;<em>bioRxiv</em>&nbsp;2019.</p>
<p>RaGOO is a tool for coalescing genome assembly contigs into pseudochromosomes via minimap2 alignments to a closely related reference genome. The focus of this tool is on practicality and therefore has the following features:</p>
<ol>
<li>Good performance. On a MacBook Pro using Arabidopsis data, pseudochromosome construction takes less than a minute and the whole pipeline with SV calling takes ~2 minutes.</li>
<li>Intact ordering and orienting of contigs.</li>
<li><a href="https://github.com/malonge/RaGOO/wiki/Misassembly-Correction">Misassembly correction</a></li>
<li><a href="https://github.com/malonge/RaGOO/wiki/GFF-File-Lift-Over">GFF lift-over</a></li>
<li><a href="https://github.com/malonge/RaGOO/wiki/Calling-Structural-Variants">Structural variant calling with and integrated version of Assemblytics</a></li>
<li>Confidence scores associated with the grouping, localization, and orientation for each contig.</li>
</ol><p>Address of the bookmark: <a href="https://github.com/malonge/RaGOO" rel="nofollow">https://github.com/malonge/RaGOO</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/7214/lapti-lab</guid>
  <pubDate>Thu, 12 Dec 2013 18:19:12 -0600</pubDate>
  <link></link>
  <title><![CDATA[LAPTI Lab]]></title>
  <description><![CDATA[
<p>The main theme of our research is the understanding of how genetic information is decoded from DNA into RNA and proteins. Someone may find this topic a little strange and argue that we already know how this is happening.</p>

<p>Translational recoding. </p>

<p>RNA editing. </p>

<p>Evolution of the genetic code and translation.</p>

<p>More at http://lapti.ucc.ie/research.html</p>

<p>Lab page http://lapti.ucc.ie/index.html</p>
]]></description>
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