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<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/29280?offset=1170</link>
	<atom:link href="https://bioinformaticsonline.com/related/29280?offset=1170" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43661/maftools</guid>
	<pubDate>Fri, 17 Dec 2021 03:18:28 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43661/maftools</link>
	<title><![CDATA[maftools]]></title>
	<description><![CDATA[<p>With advances in Cancer Genomics, <a href="https://docs.gdc.cancer.gov/Data/File_Formats/MAF_Format/">Mutation Annotation Format</a> (MAF) is being widely accepted and used to store somatic variants detected. <a href="http://cancergenome.nih.gov">The Cancer Genome Atlas</a> Project has sequenced over 30 different cancers with sample size of each cancer type being over 200. <a href="https://wiki.nci.nih.gov/display/TCGA/TCGA+MAF+Files">Resulting data</a> consisting of somatic variants are stored in the form of <a href="https://docs.gdc.cancer.gov/Data/File_Formats/MAF_Format/">Mutation Annotation Format</a>. This package attempts to summarize, analyze, annotate and visualize MAF files in an efficient manner from either TCGA sources or any in-house studies as long as the data is in MAF format.</p>
<p>https://www.bioconductor.org/packages/devel/bioc/vignettes/maftools/inst/doc/maftools.html</p><p>Address of the bookmark: <a href="https://github.com/PoisonAlien/maftools" rel="nofollow">https://github.com/PoisonAlien/maftools</a></p>]]></description>
	<dc:creator>Surabhi Chaudhary</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/19556/genome-origami</guid>
	<pubDate>Fri, 12 Dec 2014 22:48:17 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/19556/genome-origami</link>
	<title><![CDATA[Genome Origami]]></title>
	<description><![CDATA[<p>There are several interesting factoid about our genomes, one of them is their folding. If we stretched out the DNA in a single cell, which is only a few millionths of an inch wide, it would span more than six feet. In other word, the size of six feet DNA fold themself to fit in a few millionths of an inch wide space. These DNA folding is a dynamic process that changes over time (!!). Researchers around the world have been trying to understand how DNA folds itself up so efficiently, and a recent post on the NIH Director&rsquo;s Blog highlights new research illustrating how the human genome folds inside the cell&rsquo;s nucleus, as well as how DNA folding affects gene regulation. The research team created this delightful video that demonstrates the principles involved using origami art.</p><p>http://bioinformaticsonline.com/videolist/watch/19555/a-3d-map-of-the-human-genome<br /><br />Researchers have been working to determine how cells regulate gene expression for nearly as long as we&rsquo;ve known about DNA. How, for example, do nerve cells know to turn off only nerve cell genes and turn off bone cell genes? DNA folding loops are part of the answer. This research team, which published their findings in a paper in Cell http://www.cell.com/cell/abstract/S0092-8674%2814%2901497-4 , found that the number of loops is much lower than expected. There are only 10,000 loops instead of the predicted millions, and they form on/off switches in DNA.<br /><br /></p><p>More at http://www.eurekalert.org/pub_releases/2014-12/ru-3mr121114.php</p><p>Reference http://www.cell.com/cell/abstract/S0092-8674%2814%2901497-4</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/43728/short-read-assembly-using-spades</guid>
	<pubDate>Mon, 31 Jan 2022 07:18:16 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/43728/short-read-assembly-using-spades</link>
	<title><![CDATA[Short-read assembly using Spades !]]></title>
	<description><![CDATA[<h2 id="short-read-assembly-a-comparison">If we only had Illumina reads, we could also assemble these using the tool Spades.</h2><p>You can try this here, or try it later on your own data.</p><h2 id="get-data">Get data</h2><p>We will use the same Illumina data as we used above:</p><ul>
<li>illumina_R1.fastq.gz: the Illumina forward reads</li>
<li>illumina_R2.fastq.gz: the Illumina reverse reads</li>
</ul><h2 id="assemble">Assemble</h2><p>Run Spades:</p><div><pre>spades.py -1 illumina_R1.fastq.gz -2 illumina_R2.fastq.gz --careful --cov-cutoff auto -o spades_assembly_all_illumina
</pre></div><ul>
<li><code>-1</code>&nbsp;is input file of forward reads</li>
<li><code>-2</code>&nbsp;is input file of reverse reads</li>
<li><code>--careful</code>&nbsp;minimizes mismatches and short indels</li>
<li><code>--cov-cutoff auto</code>&nbsp;computes the coverage threshold (rather than the default setting, &ldquo;off&rdquo;)</li>
<li><code>-o</code>&nbsp;is the output directory</li>
</ul><h2 id="results">Results</h2><p>Move into the output directory and look at the contigs:</p><div><pre>infoseq contigs.fasta</pre></div>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/19545/walk-%E2%80%93-in-%E2%80%93-interview-agricultural-knowledge-management-unit-indian-agricultural-research-institute-new-delhi-110012</guid>
  <pubDate>Fri, 12 Dec 2014 21:33:02 -0600</pubDate>
  <link></link>
  <title><![CDATA[WALK – IN – INTERVIEW @ Agricultural Knowledge Management Unit Indian Agricultural Research Institute, New Delhi-110012]]></title>
  <description><![CDATA[
<p>Walk-in-interview for the following temporary positions will be conducted on 20th December 2014 (between 10:00 AM to 01:00 PM) at Agricultural Knowledge Management Unit, A0 block (Ground Floor), LBS Building, Indian Agricultural Research Institute, New Delhi-110012:</p>

<p>1 Dr. A.K.Mishra Coordinator &amp; PI (BTISnet)</p>

<p>Traineeship (two) for one year</p>

<p>Rs. 5000/- (consolidated)</p>

<p>M.Sc. (Bioinformatics) with 60 % marks from a recognized University</p>

<p>20-12-2014 (10:00 AM -11:00 AM)</p>

<p>Studentship (four) for one year</p>

<p>Rs. 2500/- (consolidated)</p>

<p>Final year M.Sc./ M.Tech (Bioinformatics) Students from a recognized University</p>

<p>20-12-2014 (11:00 AM- 1:00 PM)</p>

<p>The positions are purely temporary and co-terminus with the DBT Programme. Eligible candidates are requested to submit the application form in the prescribed format along with original certificates/ documents (Degree, Marks sheets, Work experience, if any) at the time of interview. No TA/DA will be paid. Maximum age limit is 28 years for all positions. Age relaxation of 5 yrs for SC/ST and woman candidates and 3 years for OBC candidates will be given. Canvassing in any form invites disqualification.</p>

<p>Advertisement: http://www.iari.res.in/files/BIC-08122014-20141208-172344.pdf</p>
]]></description>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43801/smudgeplot-inference-of-ploidy-and-heterozygosity-structure-using-whole-genome-sequencing-data</guid>
	<pubDate>Fri, 25 Feb 2022 04:42:09 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43801/smudgeplot-inference-of-ploidy-and-heterozygosity-structure-using-whole-genome-sequencing-data</link>
	<title><![CDATA[Smudgeplot: Inference of ploidy and heterozygosity structure using whole genome sequencing data]]></title>
	<description><![CDATA[<p dir="auto">This tool extracts heterozygous kmer pairs from kmer count databases and performs gymnastics with them. We are able to disentangle genome structure by comparing the sum of kmer pair coverages (CovA + CovB) to their relative coverage (CovB / (CovA + CovB)). Such an approach also allows us to analyze obscure genomes with duplications, various ploidy levels, etc.</p>
<p dir="auto">Smudgeplots are computed from raw or even better from trimmed reads and show the haplotype structure using heterozygous kmer pairs. For example:</p>
<p dir="auto"><a href="https://user-images.githubusercontent.com/8181573/45959760-f1032d00-c01a-11e8-8576-ff0512c33da9.png" target="_blank"><img src="https://user-images.githubusercontent.com/8181573/45959760-f1032d00-c01a-11e8-8576-ff0512c33da9.png" alt="smudgeexample" style="border: 0px;"></a></p><p>Address of the bookmark: <a href="https://github.com/KamilSJaron/smudgeplot" rel="nofollow">https://github.com/KamilSJaron/smudgeplot</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44307/genomenotebook</guid>
	<pubDate>Thu, 20 Apr 2023 13:19:01 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44307/genomenotebook</link>
	<title><![CDATA[genomenotebook]]></title>
	<description><![CDATA[<p><a href="https://dbikard.github.io/genomenotebook/">https://dbikard.github.io/genomenotebook/</a></p>
<h2>Install<a href="https://dbikard.github.io/genomenotebook/#install"></a></h2>
<pre><code>pip install genomenotebook</code></pre>
<h2>How to use<a href="https://dbikard.github.io/genomenotebook/#how-to-use"></a></h2>
<p>Create a simple genome browser with a search bar. The sequence appears when zooming in.</p>
<div>
<div id="cb2">
<pre><code><span><a href="https://dbikard.github.io/genomenotebook/#cb2-1"></a><span>import</span> genomenotebook <span>as</span> gn</span>
<span><a href="https://dbikard.github.io/genomenotebook/#cb2-2"></a></span>
<span><a href="https://dbikard.github.io/genomenotebook/#cb2-3"></a>g<span>=</span>gn.GenomeBrowser(genome_path, gff_path, init_pos<span>=</span><span>10000</span>)</span>
<span><a href="https://dbikard.github.io/genomenotebook/#cb2-4"></a>g.show()</span></code><button title="Copy to Clipboard"></button></pre>
</div>
</div>
<p>Tracks can be added to visualize your favorite genomics data. See&nbsp;<code>Examples</code>&nbsp;for more !!!!</p><p>Address of the bookmark: <a href="https://dbikard.github.io/genomenotebook/" rel="nofollow">https://dbikard.github.io/genomenotebook/</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/19600/studentship-at-nagaland-university</guid>
  <pubDate>Tue, 16 Dec 2014 01:35:00 -0600</pubDate>
  <link></link>
  <title><![CDATA[Studentship at Nagaland University]]></title>
  <description><![CDATA[
<p>Nagaland University<br />(A Central University Estd. By the Act of Parliament No. 35 of 1989)<br />Lumami 798 627, Nagaland<br />DBT Sponsored ‘Bioinformatics Infrastructure Facility’ Centre</p>

<p>Applications in plain paper are invited for the posts of (1) Traineeship (2 Nos.) and (2) Studentship – (2 Nos.) in the DBT funded-Bioinformatics Infrastructure Facility (BIF), Nagaland University, Lumami-798627, Nagaland. Details are given below. Interested candidates may submit the application along with self attested copies of certificates in support of the candidature to Prof. Chitta Ranjan Deb, Coordinator or Dr. L. N. Kakati, Deputy Coordinator, BIF Centre, Nagaland University, Lumami-798627, Nagaland on or before 15th January 2015.</p>

<p>The scanned application with relevant documents may be sent by email attachment to bifnulumami@gmail.com. Shortlisted candidates will be informed by email if called for interview. No TA/DA is admissible for attending the interview.</p>

<p>Traineeship (Two nos.)</p>

<p>    Post Graduate degree in any branch of Life Sciences from UGC recognized Universities</p>

<p>    Knowledge of computers and bioinformatics</p>

<p>    Rs.8000/- p.m. fixed.</p>

<p>    6 months</p>

<p>Studentship (Two nos.)</p>

<p>    Pursuing Post Graduate degree in any branch of Life Sciences from UGC recognized Universities</p>

<p>    Knowledge of computers and bioinformatics</p>

<p>    Rs.8000/- p.m. fixed.</p>

<p>    6 months</p>

<p>Terms and Conditions:</p>

<p>i) Applicants need to produce all original documents if call for interview.<br />ii) The posts are purely temporary and the appointment does not confer any entitlement or right over the job and will not be considered as formal service.<br />iii) No TA &amp; DA will be paid for appearing in the walk-in-interview.<br />iv) The stipend/salary amount is subject to the sanction of DBT, New Delhi.</p>

<p>Advertisement: http://www.nagauniv.org.in/files/BIF%20Advt.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/44377/mitochondrial-genome-assembly-tools</guid>
	<pubDate>Wed, 06 Sep 2023 00:37:18 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/44377/mitochondrial-genome-assembly-tools</link>
	<title><![CDATA[Mitochondrial genome assembly tools !]]></title>
	<description><![CDATA[<p>Mitochondrial genome assembly tools are specialized software and algorithms designed to accurately reconstruct the mitochondrial genome (mitogenome) from sequencing data, typically obtained through techniques like next-generation sequencing (NGS). The mitochondrial genome is relatively small compared to the nuclear genome, making it an ideal target for assembly. Here are some commonly used mitochondrial genome assembly tools:</p><p><strong>MitoFinder:</strong> Mitofinder is a pipeline to assemble mitochondrial genomes and annotate mitochondrial genes from trimmed read sequencing data.</p><p><strong>MitoHiFi:</strong> a python pipeline for mitochondrial genome assembly from PacBio high fidelity reads</p><p>MITObim: MITObim is a tool specifically developed for the iterative assembly of mitochondrial genomes. It starts with a reference mitogenome and iteratively refines the assembly using the read data.</p><p><strong>MITOS:</strong> MITOS is a web-based platform that provides a pipeline for annotating mitochondrial genomes. It integrates multiple software tools for assembly, annotation, and visualization of mitogenomes.</p><p><strong>MIRA:</strong> MIRA (Mimicking Intelligent Read Assembly) is a versatile genome assembly tool that can be used for mitochondrial genome assembly. It supports various sequencing technologies and allows for reference-based or de novo assembly.</p><p><strong>NOVOPlasty:</strong> NOVOPlasty is a user-friendly tool designed for de novo assembly of organelle genomes, including mitochondria. It utilizes a seed-and-extend algorithm and is suitable for both short-read and long-read data.</p><p><strong>MITOS2:</strong> MITOS2 is an updated version of the MITOS pipeline, which automates the annotation of mitochondrial genomes. It provides improved accuracy and additional features for mitochondrial genome analysis.</p><p><strong>GetOrganelle:</strong> While primarily designed for chloroplast genome assembly, GetOrganelle can also be used for mitochondrial genome assembly. It is particularly useful for dealing with high-throughput sequencing data.</p><p><strong>SPAdes:</strong> SPAdes (St. Petersburg genome assembler) is a versatile genome assembly tool that can be employed for mitochondrial genome assembly, especially when dealing with complex datasets that may contain nuclear mitochondrial DNA sequences (numts).</p><p><strong>IDBA-UD:</strong> IDBA-UD (Iterative De Bruijn Graph De Novo Assembler) is another de novo assembly tool that can be used for mitochondrial genome assembly, especially in cases with relatively low coverage.</p><p><strong>Velvet:</strong> Velvet is a de novo assembly tool that can be applied to mitochondrial genome assembly, especially when working with short-read data.</p><p>When selecting a mitochondrial genome assembly tool, it's important to consider the specific characteristics of your sequencing data, such as read length and coverage, as well as the complexity of the mitochondrial genome. Additionally, some tools are better suited for specific organisms or research objectives, so choosing the right tool will depend on your particular project requirements.</p>]]></description>
	<dc:creator>Abhi</dc:creator>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/19729/senior-scientist-agricultural-bio-informatics-one-post</guid>
  <pubDate>Wed, 24 Dec 2014 05:01:02 -0600</pubDate>
  <link></link>
  <title><![CDATA[Senior Scientist (Agricultural Bio-informatics) (One post)]]></title>
  <description><![CDATA[
<p>Agricultural Scientists Recruitment Board</p>

<p>Qualifications Essential:<br />Doctoral degree in Bio-informatics/ Biotechnology/Molecular Biology and Biotechnology/Life Sciences/ Computer Sciences with specialization in Bio-informatics including relevant basic sciences with 8 years’ experience in the relevant subject as Scientist/Lecturer or in an equivalent position in the Pay Band- 3 of 15600-39100 with Grade Pay of 5400/6000/7000/8000 having made contribution to research/teachin/extension education as evidenced by published work/innovations and impact. </p>

<p>OR </p>

<p>Doctoral degree in the above subject(s) including relevant basic sciences with minimum 8 years’ experience of high quality post-doctoral research in an institution/organization as evidenced by at least 6 publications in journals with NAAS rating of 7.5 or above.</p>

<p>Desirable:<br />(i) Specialization and experience: Knowledge of software development and its application in crop bioinformatics, experience in handling ‘omies’data. <br />(ii) Teaching experience in relevant subject</p>

<p>The Secretary, Agricultural Scientists Recruitment Board, Indian Council of Agricultural Research Krishi Anusandhan Bhavan-I, Pusa New Delhi –110 012, India</p>

<p>Detailed eligibility criteria with how to apply information can be had at:<br />http://www.indiastudychannel.com/jobs/333467-Indian-Council-of-Agricultural-Research-looking-for-Assistant-Director-General.aspx</p>

<p>More at http://asrb.org.in/administrator/uploads_dir/1418978057english.pdf</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/88/regular-expression-cheat-sheet</guid>
	<pubDate>Tue, 09 Jul 2013 17:38:42 -0500</pubDate>
	<link>https://bioinformaticsonline.com/file/view/88/regular-expression-cheat-sheet</link>
	<title><![CDATA[Regular Expression Cheat Sheet]]></title>
	<description><![CDATA[<p><span>The Regular Expression are the sole of Perl language, and for bioinformatician it is just a magical stick to resolve gingatic string data. We did not find any good and user friendly regular expression cheat sheet, hence write our own cheat sheet.&nbsp;</span><span>The Regular Expressions Cheat Sheet, a quick reference guide for regular expressions, including symbols, ranges, grouping, assertions and some sample patterns to get you started.</span></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/88" length="14944" type="application/pdf" />
</item>

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