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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/32730?offset=390</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35762/genome-assembly-stats-plotting</guid>
	<pubDate>Wed, 28 Feb 2018 03:45:39 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35762/genome-assembly-stats-plotting</link>
	<title><![CDATA[Genome assembly stats plotting]]></title>
	<description><![CDATA[<p>A&nbsp;<em>de novo</em>&nbsp;genome assembly can be summarised b</p>
<p>y a number of metrics, including:</p>
<ul>
<li>Overall assembly length</li>
<li>Number of scaffolds/contigs</li>
<li>Length of longest scaffold/contig</li>
<li>Scaffold/contig N50 and N90Assembly base composition, in particular percentage GC and percentage Ns</li>
<li>CEGMA completeness</li>
<li>Scaffold/contig length/count distribution</li>
</ul>
<p>assembly-stats supports two widely used presentations of these values, tabular and cumulative length plots, and introduces an additional circular plot that summarises most commonly used assembly metrics in a single visualisation. Each of these presentations is generated using javascript from a common (JSON) data structure, allowing toggling between alternative views, and each can be applied to a single or multiple assemblies to allow direct comparison of alternate assemblies.</p>
<p>Tabular presentation allows direct comparison of exact values between assemblies, the limitations of this approach lie in the necessary omission of distributions and the challenge of interpreting ratios of values that may vary by several orders of magnitude.</p><p>Address of the bookmark: <a href="https://github.com/rjchallis/assembly-stats" rel="nofollow">https://github.com/rjchallis/assembly-stats</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/31520/research-associate-openings-at-iasri-india</guid>
  <pubDate>Fri, 10 Mar 2017 03:53:03 -0600</pubDate>
  <link></link>
  <title><![CDATA[Research Associate openings at IASRI, India]]></title>
  <description><![CDATA[
<p>Research Associate (RA) Two (2) </p>

<p>Ph.D. in Bioinformatics/ Agricultural Statistics/ Statistics/ Computer Science/ Computer Application or equivalent or Master’s in Bioinformatics/ Agricultural Statistics/ Statistics/ Computer Science/ Computer Application or equivalent with 4 years or 5 years of Bachelor’s degree having 1st Division or 60% marks or equivalent overall grade point average, with at least two years of research experience as evidenced from fellowship/ associateship/ training/ other engagements. </p>

<p>Knowledge in System Biology/ Statistical and computational Genomics/ Bioinformatics <br />Knowledge in computer programming, LINUX OS. <br />Expertise in use of R/other Bioinformatics software </p>

<p>More at http://iasri.res.in/employment/2017/cabin_advertisement_RA_SRF_YP_Mar2017.pdf</p>

<p>Phenomics of Moisture Deficit Stress Tolerance and Nitrogen Use December 31, 2019 </p>

<p>Research Associate (RA) Two (2) </p>

<p>Ph.D. in Bioinformatics/ Agricultural Statistics/ Statistics/ Computer Science/ Computer Application or equivalent or System Administrator/ Computer expert for database development, development of phenome data bank and virtual phenomics facility, data archiving and Efficiency in Rice and Wheat-Phase II (Funded by National Agricultural Science Fund, ICAR) Master’s in Bioinformatics/ Agricultural Statistics/ Statistics/ Computer Science/ Computer Application or equivalent with 4 years or 5 years of Bachelor’s degree having 1st Division or 60% marks or equivalent overall grade point average, with at least two years of research experience as evidenced from fellowship/ associateship/ training/ other engagements. maintenance; Development of image analysis algorithms, APIs and IAPs. </p>

<p>Knowledge in System Biology/ Statistical and computational Genomics/ Bioinformatics <br />Knowledge of programming in LINUX/R/Perl/JAVA/PHP/JSP and use of various software &amp; tools. <br />December 31, 2019 </p>

<p>Ph.D. in Bioinformatics/ Agricultural Statistics/ Statistics/ Computer Science / Computer Application or equivalent or Master’s in Bioinformatics/ Agricultural Statistics/ Statistics/ Computer Science/ Computer Application or equivalent with 4 years or 5 years of Bachelor’s degree having 1st Division or 60% marks or equivalent overall grade point average, with at least two years of research experience as evidenced from fellowship/ associateship/ training/ other engagements. </p>

<p>Knowledge of Statistical and Computational Genomics/ Bioinformatics. <br />Knowledge of programming in LINUX/R/Perl/JAVA/PHP/JSP and use of various software &amp; tools. <br />March 31, 2020</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36985/swalo-scaffolding-with-assembly-likelihood-optimization</guid>
	<pubDate>Wed, 20 Jun 2018 02:45:16 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36985/swalo-scaffolding-with-assembly-likelihood-optimization</link>
	<title><![CDATA[SWALO: Scaffolding with assembly likelihood optimization]]></title>
	<description><![CDATA[SWALO (scaffolding with assembly likelihood optimization) is a method for scaffolding based on likelihood of genome assemblies computed using generative models for sequencing.

Please email your questions, comments, suggestions, and bug reports to atif.bd@gmail.com.<p>Address of the bookmark: <a href="https://atifrahman.github.io/SWALO/" rel="nofollow">https://atifrahman.github.io/SWALO/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31714/krona</guid>
	<pubDate>Wed, 22 Mar 2017 04:47:35 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31714/krona</link>
	<title><![CDATA[Krona]]></title>
	<description><![CDATA[<p>Krona allows hierarchical data to be explored with zooming, multi-layered pie charts. Krona charts can be created using an <a href="https://github.com/marbl/Krona/wiki/ExcelTemplate">Excel template</a> or <a href="https://github.com/marbl/Krona/wiki/KronaTools">KronaTools</a>, which includes support for several bioinformatics tools and raw data formats. The interactive charts are self-contained and can be viewed with any modern web browser (see <a href="https://github.com/marbl/Krona/wiki/Browser%20support">Browser support</a>).</p>
<p><a href="http://marbl.github.io/Krona/img/screen_mgrast.png"><img src="https://camo.githubusercontent.com/27b71b1f1832523723c3d14dec764e7ad098438c/687474703a2f2f6d6172626c2e6769746875622e696f2f4b726f6e612f696d672f7468756d625f6d67726173742e706e67" width="210" height="167" alt="image" style="border: 0px;"></a></p><p>Address of the bookmark: <a href="https://github.com/marbl/Krona/wiki" rel="nofollow">https://github.com/marbl/Krona/wiki</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32018/tmap-torrent-mapping-alignment-program-general-notes</guid>
	<pubDate>Sun, 02 Apr 2017 15:53:47 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32018/tmap-torrent-mapping-alignment-program-general-notes</link>
	<title><![CDATA[TMAP - torrent mapping alignment program General Notes]]></title>
	<description><![CDATA[<p>TMAP - torrent mapping alignment program <a href="https://github.com/iontorrent/TS/tree/master/Analysis/TMAP#general-notes"></a>General Notes</p>
<p>TMAP is a fast and accurate alignment software for short and long nucleotide sequences produced by next-generation sequencing technologies.</p>
<ul>
<li>
<p>The latest TMAP is unsupported. To use a supported version, please see the TMAP version associated with a Torrent Suite release below.</p>
</li>
<li>
<p>Get the latest source code:</p>
<div>
<pre>git clone git://github.com/iontorrent/TMAP.git
 <span>cd</span> TMAP
 git submodule init
 git submodule update</pre>
</div>
</li>
</ul>
<p>https://github.com/iontorrent/TS/tree/master/Analysis/TMAP</p><p>Address of the bookmark: <a href="https://github.com/iontorrent/TS/tree/master/Analysis/TMAP" rel="nofollow">https://github.com/iontorrent/TS/tree/master/Analysis/TMAP</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38212/megahit-an-ultra-fast-single-node-solution-for-large-and-complex-metagenomics-assembly-via-succinct-de-bruijn-graph</guid>
	<pubDate>Wed, 14 Nov 2018 04:50:27 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38212/megahit-an-ultra-fast-single-node-solution-for-large-and-complex-metagenomics-assembly-via-succinct-de-bruijn-graph</link>
	<title><![CDATA[MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph]]></title>
	<description><![CDATA[<p><span>MEGAHIT is a single node assembler for large and complex metagenomics NGS reads, such as soil. It makes use of succinct&nbsp;</span><em>de Bruijn</em><span>&nbsp;graph (SdBG) to achieve low memory assembly. MEGAHIT can&nbsp;</span><span>optionally</span><span>&nbsp;utilize a CUDA-enabled GPU to accelerate its SdBG contstruction. The GPU-accelerated version of MEGAHIT has been tested on NVIDIA GTX680 (4G memory) and Tesla K40c (12G memory) with CUDA 5.5, 6.0 and 6.5. MEGAHIT v1.0 or greater also supports IBM Power PC and has been tested on IBM POWER8.</span></p>
<p><span>https://academic.oup.com/bioinformatics/article/31/10/1674/177884</span></p><p>Address of the bookmark: <a href="https://github.com/voutcn/megahit" rel="nofollow">https://github.com/voutcn/megahit</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/32358/list-of-goi-approved-peer-reviewed-bioinformatics-and-computational-biology-journals</guid>
	<pubDate>Tue, 25 Apr 2017 05:03:27 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/32358/list-of-goi-approved-peer-reviewed-bioinformatics-and-computational-biology-journals</link>
	<title><![CDATA[List of GOI approved peer reviewed bioinformatics and computational biology journals]]></title>
	<description><![CDATA[<p>Unfortunately, we now live in a world where the integrity of peer-reviewed journals is being threatened by the rise of the academic version of fake news &ndash; something many call &ldquo;predatory publishing". &nbsp;Mostly in academic publishing world, "predatory open access publishing" is an exploitative open-access publishing business model that involves charging publication fees to authors without providing the editorial and publishing services associated with legitimate journals (open access or not).</p><p>Nearly 20% of the such journals have a flashy impact factor and quick publication time, which are quick give-aways. Interestingly, under contact address, some journal websites do not even provide any address to contact. All of this has led to the emergence of a new and dark market of deceptive publishers that exploit the concept of open access and provide channels for &ldquo;scientific journal&rdquo; publication with little or no peer review. For a fee, they will publish almost anything &ndash; even if the study was fatally flawed. And these journals provide a forum that can be used as a channel to publish fraudulent &ldquo;advocacy research.&rdquo; You can find list of certain such publishers at "Beall's List" http://beallslist.weebly.com/</p><p>Keeping all these in mind, Government of India (GOI) decided to approved certain bioinformatics and computational biology journals for your research publication.<br /> <br />Following are the list of GOI validated and peer reviewed bioinformatics and computational biology journals:</p><p><strong>NOTE:Each journal details are in following order Tittle\nSource\nSubject. </strong><br /><strong>Point to remember: The list of journals are NOT sorted in any ascending or descending order.</strong></p><p><em>If I missed any other GOI validated bioinformatics journal, then please report me in comment section.</em></p><p><strong>Open Bioinformatics Journal</strong> <br />Scopus <br />Computer Science; Engineering; Medicine</p><p><strong>PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS</strong> <br />WoS <br />BIOLOGY &amp; BIOCHEMISTRY</p><p><strong>Advances and Applications in Bioinformatics and Chemistry</strong><br />Scopus<br />Biochemistry, Genetics and Molecular Biology Chemistry; Computer Science</p><p><strong>Advances in Bioinformatics</strong><br />Scopus<br />Biochemistry, Genetics and Molecular Biology; Computer Science; Engineering</p><p><strong>Applied Bioinformatics</strong><br />Scopus<br />Agricultural and Biological Sciences; Computer Science</p><p><strong>BIOINFORMATICS</strong> <br />WoS &amp; Scopus <br />COMPUTER SCIENCE</p><p><strong>Bioinformatics and Biology Insights</strong> <br />Scopus<br />Biochemistry, Genetics and Molecular Biology; Computer Science; Mathematics</p><p><strong>BMC BIOINFORMATICS</strong> <br />WoS &amp; Scopus <br />COMPUTER SCIENCE</p><p><strong>BRIEFINGS IN BIOINFORMATICS</strong> <br />WoS &amp; Scopus <br />COMPUTER SCIENCE</p><p><strong>Computational systems bioinformatics / Life Sciences Society. Computational Systems Bioinformatics Conference</strong> <br />Scopus <br />Medicine</p><p><strong>Current Bioinformatics</strong> <br />WoS &amp; Scopus <br />COMPUTER SCIENCE</p><p><strong>Current Protocols in Bioinformatics</strong> <br />Scopus <br />Biochemistry, Genetics and Molecular Biology</p><p><strong>JOURNAL OF COMPUTATIONAL INTELLIGENCE IN BIOINFORMATICS</strong> <br />ICI <br />BIOLOGICAL SCIENCE</p><p><strong>Journal of integrative bioinformatics</strong> <br />Scopus <br />Medicine</p><p><strong>Journal of Proteomics and Bioinformatics</strong> <br />Scopus<br />Biochemistry, Genetics and Molecular Biology; Computer Science</p><p><strong>Mathematical Biology and Bioinformatics</strong> <br />Scopus <br />Engineering; Mathematics</p><p><strong>Trends in Bioinfprmatics</strong><br />Scopus <br />Computer Science</p><p><strong>Eurasip Journal on Bioinformatics and Systems Biology</strong> <br />Scopus<br />General; Computer Science; Mathematics; Medicine</p><p><strong>Evolutionary Bioinformatics</strong> <br />WoS &amp; Scopus <br />COMPUTER SCIENCE</p><p><strong>Genomics, Proteomics and Bioinformatics</strong> <br />Scopus<br />Biochemistry, Genetics and Molecular Biology;Mathematics</p><p><strong>IEEE/ACM Transactions on Computational Biology and Bioinformatics</strong> <br />Scopus<br />Biochemistry, Genetics and Molecular Biology;Mathematics</p><p><strong>IEEE-ACM Transactions on Computational Biology and Bioinformatics</strong> <br />WoS <br />COMPUTER SCIENCE</p><p><strong>International Journal of Bioinformatics Research and Application</strong><br />Scopus<br />Biochemistry, Genetics and Molecular Biology; Medicine, Health</p><p><strong>International Journal o f Data M ining and Bioinformatics</strong> <br />WoS &amp; Scopus <br />COMPUTER SCIENCE</p><p><strong>IPSJ Transactions on Bioinformatics</strong> <br />Scopus <br />Biochemistry, Genetics and Molecular Biology;Computer Science</p><p><strong>Journal of Bioinformatics and Computational Biology</strong> <br />WoS &amp; Scopus<br />COMPUTER SCIENCE</p><p><strong>Journal of Clinical Bioinformatics</strong> <br />Scopus <br />Medicine</p><p><strong>PLoS Computational Biology</strong> <br />WoS &amp; Scopus <br />BIOLOGY &amp; BIOCHEMISTRY</p><p><strong>Reviews in Computational Chemistry</strong> <br />WoS &amp; Scopus <br />CHEMISTRY</p><p><strong>RSC Theoretical and Computational Chemistry Series</strong><br />Scopus <br />Chemistry; Computer Science</p><p><strong>Annual Reports in Computational Chemistry</strong> <br />Scopus <br />Chemistry; Mathematics</p><p><strong>Computational and Structural Biotechnology Journal</strong> <br />Scopus<br />Biochemistry, Genetics and Molecular Biology; Computer Science</p><p><strong>Computational and Theoretical Chemistry</strong> <br />WoS &amp; Scopus <br />CHEMISTRY</p><p><strong>COMPUTATIONAL BIOLOGY AND CHEMISTRY</strong> <br />WoS &amp; Scopus<br />COMPUTER SCIENCE</p><p><strong>COMPUTATIONAL CHEMISTRY</strong> <br />WoS <br />CHEMISTRY</p><p><strong>Journal of Theoretical and Computational Chemistry</strong> <br />Scopus<br />Chemistry; Computer Science</p><p><strong>Theoretical and Computational Chemistry</strong> <br />Scopus <br />Chemistry</p><p><strong>Wiley Interdisciplinary Reviews: Computational Molecular Science</strong> <br />Scopus<br />Biochemistry, Genetics and Molecular Biology;Chemistry; Computer Science; Materials Science; Mathematics</p><p><strong>Wiley Interdisciplinary Reviews- Computational Molecular Science</strong> <br />WoS <br />CHEMISTRY</p><p><strong>Interdisciplinary sciences, computational life sciences</strong><br />Scopus<br />Medicine</p><p><strong>Interdisciplinary Sciences-Computational Life Science</strong><br />WoS<br />Biology and Biochemistry</p><p><strong>International Journal of Computational Biology and Drug Design</strong><br />Scopus<br />Computer Science; Pharmacology, Toxicology and Pharmaceutics</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38792/nxrepair-error-correction-in-de-novo-assemblies-using-nextera-mate-pair-reads</guid>
	<pubDate>Thu, 24 Jan 2019 10:35:12 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38792/nxrepair-error-correction-in-de-novo-assemblies-using-nextera-mate-pair-reads</link>
	<title><![CDATA[NxRepair: error correction in de novo assemblies using Nextera Mate Pair Reads]]></title>
	<description><![CDATA[<p>NxRepair is a python module that automatically detects large structural errors in de novo assemblies using Nextera mate pair reads. The decector will break a contig at the site of an identified misassembly and will generate a new fasta file containing both the corrected contigs and the correct, unaffected contigs.</p>
<p>https://nxrepair.readthedocs.io/en/latest/tutorial.html</p>
<div>
<div>
<div id="js-repo-pjax-container">
<div>
<div>
<div id="readme">
<div>
<div>
<pre>nxrepair aligned_matepairs.bam assemblyfasta.fasta error_locations.csv new_fasta.fasta</pre>
</div>
</div>
</div>
</div>
</div>
</div>
</div>
</div>
<div>&nbsp;</div><p>Address of the bookmark: <a href="https://github.com/rebeccaroisin/nxrepair" rel="nofollow">https://github.com/rebeccaroisin/nxrepair</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32631/barrnap-bacterial-ribosomal-rna-predictor</guid>
	<pubDate>Fri, 12 May 2017 09:24:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32631/barrnap-bacterial-ribosomal-rna-predictor</link>
	<title><![CDATA[Barrnap: Bacterial ribosomal RNA predictor]]></title>
	<description><![CDATA[<p>Barrnap predicts the location of ribosomal RNA genes in genomes. It supports bacteria (5S,23S,16S), archaea (5S,5.8S,23S,16S), mitochondria (12S,16S) and eukaryotes (5S,5.8S,28S,18S).</p>
<p>It takes FASTA DNA sequence as input, and write GFF3 as output. It uses the new NHMMER tool that comes with HMMER 3.1 for HMM searching in RNA:DNA style. NHMMER binaries for 64-bit Linux and Mac OS X are included and will be auto-detected. Multithreading is supported and one can expect roughly linear speed-ups with more CPUs.&nbsp;</p><p>Address of the bookmark: <a href="https://github.com/tseemann/barrnap" rel="nofollow">https://github.com/tseemann/barrnap</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39098/sda-long-read-sequence-and-assembly-of-segmental-duplications</guid>
	<pubDate>Tue, 05 Mar 2019 10:00:57 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39098/sda-long-read-sequence-and-assembly-of-segmental-duplications</link>
	<title><![CDATA[SDA: Long-read sequence and assembly of segmental duplications]]></title>
	<description><![CDATA[<p><span><span>Segmental Duplication Assembler (SDA; https://github.com/mvollger/SDA) constructs graphs in which paralogous sequence variants define the nodes and long-read sequences provide attraction and repulsion edges, enabling the partition and assembly of long reads corresponding to distinct paralogs.<br></span></span></p>
<p><span><span>https://github.com/mvollger/SDA</span></span></p><p>Address of the bookmark: <a href="https://www.nature.com/articles/s41592-018-0236-3" rel="nofollow">https://www.nature.com/articles/s41592-018-0236-3</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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