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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/32154?offset=810</link>
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	<description><![CDATA[]]></description>
	
	
<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/22416/rosenberg-lab</guid>
  <pubDate>Wed, 27 May 2015 17:52:24 -0500</pubDate>
  <link></link>
  <title><![CDATA[Rosenberg lab]]></title>
  <description><![CDATA[
<p>Research. Research in the lab focuses on mathematical, statistical, and computational problems in evolutionary biology and human genetics. Long-term interests of the lab include topics such as:</p>

<p>    Human genetic variation<br />    Inference of human evolutionary history from genetic markers<br />    Statistical analysis of population-genetic data<br />    Mathematical models of gene genealogies<br />    Theoretical population genetics<br />    Combinatorics of evolutionary trees<br />    The relationship between gene trees and species trees<br />    The role of human evolutionary genetics in the search for genes that contribute to disease-susceptibility <br />More at https://web.stanford.edu/group/rosenberglab/index.html</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43376/hisat2-index-files-download</guid>
	<pubDate>Wed, 15 Sep 2021 22:17:49 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43376/hisat2-index-files-download</link>
	<title><![CDATA[HISAT2 Index Files Download !]]></title>
	<description><![CDATA[<p>Resource for downloading all the HISAT2 related files&nbsp;</p>
<p>Please cite:</p>
<blockquote>
<p>Kim, D., Paggi, J.M., Park, C.&nbsp;<em>et al.</em>&nbsp;Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype.&nbsp;<em>Nat Biotechnol</em>&nbsp;<strong>37</strong>, 907&ndash;915 (2019).&nbsp;<a href="https://doi.org/10.1038/s41587-019-0201-4" target="_blank">https://doi.org/10.1038/s41587-019-0201-4</a></p>
</blockquote><p>Address of the bookmark: <a href="http://daehwankimlab.github.io/hisat2/download/#h-sapiens" rel="nofollow">http://daehwankimlab.github.io/hisat2/download/#h-sapiens</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/22437/jrf-bioinformatics-icar-national-research-centre-for-orchids-pakyong</guid>
  <pubDate>Thu, 28 May 2015 19:33:19 -0500</pubDate>
  <link></link>
  <title><![CDATA[JRF Bioinformatics @ ICAR - National Research Centre for Orchids  Pakyong]]></title>
  <description><![CDATA[
<p>ICAR - National Research Centre for Orchids</p>

<p>Pakyong</p>

<p>F.No:NRCO/Admn/DBT /136 /</p>

<p>Walk-in-Interviews will be held at 737106, Sikkim for the post of 01 (One Project ‘DBT’s Twinning programme for the NE’ titled “Assessment of some fragrant orchids of north-east India for sustainable improvement of community livelihood”, indicated below. The appointment will be on contractual basis and the incumbents shall not have any regular appointment in ICAR.</p>

<p>‘DBT’s Twinning programme for the NE’ titled “Assessment of chemical and genetic divergence of some fragrant orchids of north-east India for sustainable improvement of community livelihood”</p>

<p>Junior Research Fellow (One post)</p>

<p>Essential Qualification : a. MSc (with NET qualification) / M.Tech degree (with or without NET) with minimum 55% marks in Biotechnology/ Bioinformatics/ Molecular Biology or any other related field.</p>

<p>Desirable Qualification: Computer Skills (Linux, Perl, Java, MySQL) with experience in advanced molecular Biology techniques</p>

<p>2nd June 2015</p>

<p>Advertisement: www.nrcorchids.nic.in/Employments/Vacancy%20-%20JRF.pdf</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43658/uniquekmer-generate-unique-kmers-for-every-contig-in-a-fasta-file</guid>
	<pubDate>Fri, 17 Dec 2021 00:08:15 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43658/uniquekmer-generate-unique-kmers-for-every-contig-in-a-fasta-file</link>
	<title><![CDATA[UniqueKmer: Generate unique KMERs for every contig in a FASTA file]]></title>
	<description><![CDATA[<p dir="auto">Generate unique k-mers for every contig in a FASTA file.</p>
<p dir="auto">Unique k-mer is consisted of k-mer keys (i.e. ATCGATCCTTAAGG) that are only presented in one contig, but not presented in any other contigs (for both forward and reverse strands).</p>
<p dir="auto">This tool accepts the input of a FASTA file consisting of many contigs, and extract unique k-mers for each contig.</p>
<p dir="auto">The output unique k-mer file and Genome file can be used for fastv:&nbsp;<a href="https://github.com/OpenGene/fastv">https://github.com/OpenGene/fastv</a>, which is an ultra-fast tool to identify and visualize microbial sequences from sequencing data.</p>
<p>https://github.com/OpenGene/UniqueKMER</p><p>Address of the bookmark: <a href="https://github.com/OpenGene/UniqueKMER" rel="nofollow">https://github.com/OpenGene/UniqueKMER</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/22570/frequent-words-problem-solution-by-perl</guid>
	<pubDate>Tue, 09 Jun 2015 23:38:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/22570/frequent-words-problem-solution-by-perl</link>
	<title><![CDATA[Frequent words problem solution by Perl]]></title>
	<description><![CDATA[<div><p>Solved with perl <a href="http://rosalind.info/problems/1a/">http://rosalind.info/problems/1a/</a></p><p>#Find the most frequent k-mers in a string.<br />#Given: A DNA string Text and an integer k.<br />#Return: All most frequent k-mers in Text (in any order).<br /><br />use strict;<br />use warnings;<br /><br />my $string="ACGTTGCATGTCGCATGATGCATGAGAGCT";<br />my $kmer=4; <br />my %myHash;<br />my $max=0;<br /><br />for (my $aa=0; $aa&lt;=(length($string)-4); $aa++) {<br />&nbsp;&nbsp; &nbsp;my $myStr=substr&nbsp; $string, $aa,$kmer;<br />&nbsp;&nbsp; &nbsp;#print "$myStr\n";<br />&nbsp;&nbsp; &nbsp;my $km=kmerMatch ($string, $myStr, $kmer);<br />&nbsp;&nbsp; &nbsp;if ($km &gt; $max) { $max = $km;}<br />&nbsp;&nbsp; &nbsp;#print "$km\t$myStr\n";<br />&nbsp;&nbsp; &nbsp;$myHash{$myStr}=$km;<br />&nbsp;&nbsp; &nbsp;<br />}<br /><br />#Print all key which have matching values<br />foreach my $name (keys %myHash){<br />&nbsp;&nbsp;&nbsp; print "$name " if $myHash{$name} == $max;<br />}<br /><br />sub kmerMatch { #Check the exact matching kmers with sliding window<br />my ($string, $myStr, $kmer)=@_;<br />my $count=0;<br />for (my $aa=0; $aa&lt;=(length($string)-4); $aa++) {<br />&nbsp;&nbsp; &nbsp;my $myWin=substr&nbsp; $string, $aa,$kmer;<br />&nbsp;&nbsp; &nbsp;if ($myWin eq $myStr) {<br />&nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;#print "$myWin eq $myStr\n";<br />&nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;$count++;<br />&nbsp;&nbsp; &nbsp;}<br />}<br />return $count;<br />}</p></div>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43799/kast</guid>
	<pubDate>Wed, 23 Feb 2022 08:28:36 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43799/kast</link>
	<title><![CDATA[KAST]]></title>
	<description><![CDATA[<p><span>Perform Alignment-free k-tuple frequency comparisons from sequences. This can be in the form of two input files (e.g. a reference and a query) or a single file for pairwise comparisons to be made.</span></p><p>Address of the bookmark: <a href="https://github.com/martinjvickers/KAST" rel="nofollow">https://github.com/martinjvickers/KAST</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/22572/clump-finding-problem-solved-with-perl</guid>
	<pubDate>Wed, 10 Jun 2015 00:17:17 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/22572/clump-finding-problem-solved-with-perl</link>
	<title><![CDATA[Clump Finding Problem Solved with Perl]]></title>
	<description><![CDATA[<p>The question at http://rosalind.info/problems/1d/</p><p>Script are moved to&nbsp;http://bioinformaticsonline.com/snippets/view/34633/clump-finding-problem-solved-with-perl</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44223/ale-assembly-likelihood-estimator</guid>
	<pubDate>Wed, 08 Mar 2023 01:39:33 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44223/ale-assembly-likelihood-estimator</link>
	<title><![CDATA[ALE: Assembly Likelihood Estimator]]></title>
	<description><![CDATA[<p>Just import the assembly, bam and ALE scores. You can convert the .ale file to a set of .wig files with ale2wiggle.py and IGV can read those directly.&nbsp; Depending on your genome size you may want to convert the .wig files to the BigWig format.</p><p>Address of the bookmark: <a href="https://github.com/sc932/ALE" rel="nofollow">https://github.com/sc932/ALE</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/44371/steps-to-find-all-the-repeats-in-the-genome</guid>
	<pubDate>Thu, 31 Aug 2023 02:43:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/44371/steps-to-find-all-the-repeats-in-the-genome</link>
	<title><![CDATA[Steps to find all the repeats in the genome !]]></title>
	<description><![CDATA[<div><p>To find repeats in a genome from 2 to 9 length using a Perl script, you can use the RepeatMasker tool with the "--length" option<a href="https://mobilednajournal.biomedcentral.com/articles/10.1186/1759-8753-5-13" target="_blank">[0]</a>. Here's a step-by-step guide:</p></div><div><ol>
<li>Install RepeatMasker: First, you need to install RepeatMasker on your system. You can download it from the RepeatMasker website<a href="https://mobilednajournal.biomedcentral.com/articles/10.1186/1759-8753-5-13" target="_blank">[0]</a>.</li>
</ol></div><div><ol>
<li>Prepare the genome sequence: Make sure you have the genome sequence in a FASTA file format. Let's assume the file is named "genome.fasta".</li>
</ol><blockquote><p>./RepeatMasker -pa &lt;number_of_processors&gt; -nolow -norna -no_is -div &lt;divergence_value&gt; -lib RepeatMaskerLib.embl -gff -xsmall -small -poly -species &lt;species_name&gt; -dir &lt;output_directory&gt; -length &lt;min_length&gt;-&lt;max_length&gt; genome.fasta</p></blockquote><div><p>Replace the following placeholders with appropriate values:</p><ul>
<li><code>&lt;number_of_processors&gt;</code>: The number of processors/threads you want to use for parallel processing.</li>
<li><code>&lt;divergence_value&gt;</code>: The divergence value for the species you are analyzing. You can find divergence values for different species in the RepeatMasker documentation<a href="https://mobilednajournal.biomedcentral.com/articles/10.1186/1759-8753-5-13" target="_blank">[0]</a>.</li>
<li><code>&lt;species_name&gt;</code>: The name of the species you are analyzing.</li>
<li><code>&lt;output_directory&gt;</code>: The directory where you want the output files to be saved.</li>
<li><code>&lt;min_length&gt;</code>&nbsp;and&nbsp;<code>&lt;max_length&gt;</code>: The minimum and maximum lengths of the repeats you want to find (in this case, 2 and 9).</li>
</ul></div><div><ol>
<li>Analyze the output: RepeatMasker will generate several output files, including a .out file. You can parse this file to extract the information you need. There is a Perl tool called "one_code_to_find_them_all.pl" that can help you parse RepeatMasker output files<a href="https://mobilednajournal.biomedcentral.com/articles/10.1186/1759-8753-5-13" target="_blank">[0]</a>. You can download it from the source provided.</li>
</ol></div><div><ol>
<li>Use the provided Perl script: Once you have the "one_code_to_find_them_all.pl" script, you can run it to conveniently parse the RepeatMasker output files. Here's an example of how to use it:</li>
</ol><blockquote><p>perl one_code_to_find_them_all.pl --rm &lt;RepeatMasker_out_file&gt; --length &lt;length_file&gt;</p></blockquote></div><p>&nbsp;</p></div><div><div><p>Replace&nbsp;<code>&lt;RepeatMasker_out_file&gt;</code>&nbsp;with the path to your RepeatMasker .out file, and&nbsp;<code>&lt;length_file&gt;</code>&nbsp;with the path to a file containing the lengths of the reference elements.</p></div><div><p>This script will generate several output files, including .log.txt and .copynumber.csv, which contain quantitative information about the identified repeat elements.</p></div><div><p>Remember to adjust the parameters and options according to your specific needs and the characteristics of your genome.</p></div></div>]]></description>
	<dc:creator>Neel</dc:creator>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/22786/ra-at-university-of-delhi</guid>
  <pubDate>Wed, 17 Jun 2015 20:35:35 -0500</pubDate>
  <link></link>
  <title><![CDATA[RA at University of Delhi]]></title>
  <description><![CDATA[
<p>Research Scientist Jobs opportunity in University of Delhi on temporary basis</p>

<p>Qualifications : Ph. D.</p>

<p>Desirable : Experience on DNA Markers, plant genome mapping and bioinformatics</p>

<p>No. of Post : 03</p>

<p>Department : Genetics</p>

<p>Salary : Rs. 60,000/-<br />How to apply</p>

<p>The applicants are requested to register their names on the day of interview in the First Floor, Biotech Centre, Centre for Genetic Manipulation of Crop Plants, Department of Genetics before the stipulated time for the interview. Only the registered eligible candidates will be interviewed on the day in the Committee Room. Applicants are requested to bring all related documents, in original and a set of photocopy, for verification. Date and time of the interview : 25.06.2015 at 10:30 AM.</p>

<p>Click Here for Job Details http://www.du.ac.in/du/index.php?mact=News,cntnt01,detail,0&amp;cntnt01articleid=5492&amp;cntnt01returnid=83</p>
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