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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/27696?offset=440</link>
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	<description><![CDATA[]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/29407/live-webinar-on-rna-seq-data-analysis-on-9-nov-2016</guid>
	<pubDate>Wed, 19 Oct 2016 05:25:27 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/29407/live-webinar-on-rna-seq-data-analysis-on-9-nov-2016</link>
	<title><![CDATA[Live Webinar on RNA-Seq Data Analysis on 9 Nov 2016]]></title>
	<description><![CDATA[<p><strong><a href="http://www.strand-ngs.com/webinar_registration">Live Webinar on RNA-Seq Data Analysis</a></strong></p><p><a href="http://www.strand-ngs.com/webinar_registration">Abstract: </a>Strand NGS supports an extensive workflow for the analysis and visualization of RNA-Seq data. The workflow includes Transcriptome / Genome alignment, Differential expression analysis with Statistical approach and Splicing events detection. Strand NGS also supports novel discovery like identification of novel genes, exons and Novel splice junctions, alongside it can also detect gene fusion events. Further downstream analysis such as GO and pathway analysis can be performed on the set of interesting genes. The product has an option to create pipelines for time consuming jobs which automates analysis and leaves more time for end data interpretation. This webinar will give an overview of the features in the RNA-Seq data analysis workflow in Strand NGS and also highlights on parameters within each feature that can be optimized depending on datasets and analysis needs.</p><p><a href="http://www.strand-ngs.com/webinar_registration">Speaker:</a> Mr. Sugandan Sivamani, Senior Application Scientist, Strand Life Sciences</p><p>Date: 9th Nov, <a href="http://www.strand-ngs.com/webinar_registration">Session 1</a> for SAPK/ APFO: 2:30 PM IST Date: 9th Nov, <a href="http://www.strand-ngs.com/webinar_registration">Session 2</a> for AFO/ EMEA: 9:00 AM PST</p><p>Register here <a href="http://www.strand-ngs.com/webinar_registration">http://www.strand-ngs.com/webinar_registration</a></p>]]></description>
	<dc:creator>Strand</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/20015/illumina-smartphone-chip</guid>
	<pubDate>Tue, 30 Dec 2014 23:19:54 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/20015/illumina-smartphone-chip</link>
	<title><![CDATA[Illumina Smartphone Chip !!!]]></title>
	<description><![CDATA[<p>Illumina, the company that claims it brought human genome sequencing down to $1000 prices, has now turned its attention to a consumer product - a chip that you can plug into your smartphone and have it read your genetic information.<br /><br />The biggest challenge ahead of Illumina is simplifying the process of genetic sequencing. Currently, Illumina&rsquo;s DNA sequencers are gigantic machines that use techinques like colorimetry to work, but while the core technology is computational, it takes some 30 steps to extract genetic data and run it through. This process will likely have to be hugely simplified on mobile devices, given the fact that some studies require extracting 10 mililiters of blood. Illumina researchers are also working on finding the optimal technology for this on-chip DNA sequencing - be it electrical, optical, or other.<br /><br />Illumina is one of the most prominent names in genetics, often said to be the Intel of genetic sequencing, as just like Intel it provides the algorithms, the processing brain that runs a DNA reading task.<br /><br />In other recent smartphone-related biotech news, drug company Pfizer launched its REMOTE project, a new type of clinical trial that does not require going to a hospital for checks - targeted at patients with overactive bladder problems, the FDA-approved REMOTE project allowed to gather data from patients from over 10 states remotely, via mobile devices.<br /><br /></p><p>This is indeed the Illumina answer to Apple's Health app, HealthBook, Google HealthFit.</p>]]></description>
	<dc:creator>Robert M Willioms</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/33486/quick-next-generation-sequencing-ngs-terms-definition</guid>
	<pubDate>Fri, 09 Jun 2017 04:52:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/33486/quick-next-generation-sequencing-ngs-terms-definition</link>
	<title><![CDATA[Quick next generation sequencing (NGS) terms definition]]></title>
	<description><![CDATA[<p><strong>fragment size:</strong><span>&nbsp;the Illumina WGS protocol generates paired-end reads from both ends of longer fragments. The lengths of these fragments are assumed to be sampled from a normal distribution. Therefore, in the absence of structural variants, mapping locations of the paired ends span within an interval [&delta;min,&delta;max]. Most (&gt;90%) of paired-end reads are sampled from no-SV regions, therefore the fragment size distribution can be learned empirically for each WGS data set separately.</span><br /><br /><strong>concordant reads:</strong><span>&nbsp;a read pair is called concordant if they can be mapped to the reference genome as &ldquo;expected&rdquo;: (a) mapped to opposing strands where the upstream read is mapped to the forward strand and the downstream read is mapped to the reverse strand2, (b) the distance between ends is between the minimum and maximum expected fragment size.</span><br /><br /><strong>discordant reads:</strong><span>&nbsp;briefly, any non-concordant read pair is considered discordant. Note that, by definition, the discordant read pairs signal potential SVs. The sequence signature produced by these type of reads is known as read-pair signature.</span><br /><br /><strong>split reads:</strong><span>&nbsp;a read that can only be mapped to the reference genome by breaking into two sub-reads is called a split-read. These types of reads also indicate a potential SV or a short insertion or deletion (indel).</span><br /><br /><strong>read depth:</strong><span>&nbsp;number of reads that map within a region of the genome. Overall genome-wide read depth is also referred to as depth of coverage. It is expected that the number of reads that &ldquo;cover&rdquo; each base-pair to follow a Poisson distribution. Therefore, if the read depth over a certain region deviates significantly from this distribution, it signals for a potential copy number variation (CNV).</span></p>]]></description>
	<dc:creator>Neel</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/20449/walk-in-interview-for-the-post-of-jrf-and-project-assistant-cift</guid>
  <pubDate>Tue, 20 Jan 2015 23:03:20 -0600</pubDate>
  <link></link>
  <title><![CDATA[WALK-IN-INTERVIEW for the post of JRF and Project Assistant @ CIFT]]></title>
  <description><![CDATA[
<p>Eligible candidates are invited to attend a walk-in-Interview with all relevant documents for the following positions of Project Fellows (on contractual basis) to work in the Project “ Genetic Diversity of Clostridium botulinum in seafood and Development of Lateral Flow Immuno Assay (LFIA) for toxinotyping  funded by Department of Biotechnology.   The duration of the project is 3 years / co-terminus with the scheme.</p>

<p>Jr. Research Fellow – 2 posts</p>

<p>    Fellowship    :   Rs. 25000/- + 20% HRA pm  for Ist &amp; 2nd year and Rs.28000/- + HRA on 3rd year</p>

<p>    Qualification :    Ist class Masters Degree in Microbiology/Fishery Microbiology/Bio-technology.</p>

<p>    Desirable        :  </p>

<p>    1. CSIR/UGC NET/JRF qualified</p>

<p>    2. Excellent analytical skills and computer documentation</p>

<p>    3. Prior experience in handling microbial cultures and molecular techniques</p>

<p>Project Assistant – 1 post</p>

<p>Fellowship    :    Rs.8000/- p.m (consolidated)</p>

<p>Qualification:   Masters degree in Microbiology/Biotechnology with skill in Bioinformatics</p>

<p>Desirable:   Excellent analytical skills in Bioinformatics and computer documentation</p>

<p>Terms &amp; Conditions:</p>

<p>Registration will begin at 8.30 a.m and will close at 11.00 am<br />Age limit (as on 29.1.2015):  Below 35 years for men and 40 years for women.<br />Age relaxation of 3 year for OBC candidates and 5 years for SC/ST candidates is permissible.<br />Candidates are required to submit self-attested copies of all the Certificates in support of their claims    regarding age, educational qualifications, scheduled caste/scheduled tribe/OBC etc.  The original certificates shall be produced for verification before the interview.<br />Candidates should bring detailed bio-data (in the enclosed format)  affixing a recent passport size photograph.<br />The selected candidate will be recruited on contract basis under ICAR norms.  The post is purely temporary and is co-terminus with the project.<br />The candidates attending the interview should ensure that they fulfil all the eligibility conditions.  No correspondence will be entertained from the candidates for selection/test/appointment.<br />No TA/DA will be paid to attend the interview.<br />Canvassing in any form will render the candidate disqualified for the post.<br />The Director’s decision will be final and binding in all aspects regarding the selection to the post.</p>

<p>Venue: CIFT, Matsyapuri.P.O, Cochin                  Date of interview:  29.01.2015          Time:  10.00 am</p>

<p>http://www.cift.res.in/uploads/userfiles/file/file/srf%20appn.doc</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36518/mix-combining-multiple-assemblies-from-ngs-data</guid>
	<pubDate>Tue, 08 May 2018 04:58:05 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36518/mix-combining-multiple-assemblies-from-ngs-data</link>
	<title><![CDATA[MIX: Combining multiple assemblies from NGS data]]></title>
	<description><![CDATA[<p>Mix is a tool that combines two or more draft assemblies, without relying on a reference genome and has the goal to reduce contig fragmentation and thus speed-up genome finishing. The proposed algorithm builds an extension graph where vertices represent extremities of contigs and edges represent existing alignments between these extremities. These alignment edges are used for contig extension. The resulting output assembly corresponds to a path in the extension graph that maximizes the cumulative contig length.</p>
<p>The Mix algorithm, approach and results were published in BMC bioinformatics :&nbsp;<a href="http://www.biomedcentral.com/1471-2105/14/S15/S16">http://www.biomedcentral.com/1471-2105/14/S15/S16</a>.</p><p>Address of the bookmark: <a href="https://github.com/cbib/MIX" rel="nofollow">https://github.com/cbib/MIX</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/20387/walk-in-interview-for-project-assistant-bharathidasan-university</guid>
  <pubDate>Mon, 12 Jan 2015 21:54:10 -0600</pubDate>
  <link></link>
  <title><![CDATA[WALK-IN-INTERVIEW FOR PROJECT ASSISTANT @ BHARATHIDASAN UNIVERSITY]]></title>
  <description><![CDATA[
<p>BHARATHIDASAN UNIVERSITY<br />DEPARTMENT OF BIOINFORMATICS, SCHOOL OF LIFE SCIENCES, TIRUCHIRAPPALLI – 620024</p>

<p>Project title: “Genome-scale metabolic modeling and simulation of rumen methanogens An in silico attempt to methane attenuation”</p>

<p>Funding Agency: University Grants Commission, New Delhi</p>

<p>Tenure of the project: Two years or till the end of the project period.</p>

<p>Position: Project Assistant (1 no.)</p>

<p>Essential qualification: First class M.Sc. in Bioinformatics/Microbiology/ Biotechnology and other related discipline.</p>

<p>Desirable qualification: Experience in an area relevant (Molecular Systems Engineering) to the project.</p>

<p>Fellowship: Rs. 5000 per month as per the UGC norms.</p>

<p>Upper age limit: 28 years</p>

<p>Date of Venue of interview: 22.01.2015, Department of Bioinformatics, School of Life Sciences, Bharathidasan University, Tiruchirappalli -620 024, Tamil Nadu</p>

<p>The above post is purely temporary and will be terminated with three month notice.</p>

<p>The Terms and the condition of the appointment shall be governed according to UGC, Govt. of India. The eligible candidates will bring their original certificates and documents at the time of interview. No TA/DA will be paid for attending the interview.</p>

<p>Dr. P. CHELLAPANDI<br />UGC-Research Awardee,<br />Department of Bioinformatics,<br />School of Life Sciences,<br />Bharathidasan University,<br />Tiruchirappalli -620 024, Tamil Nadu</p>

<p>Advertisement: www.bdu.ac.in/adv/PA_UGC_Bioinformatics.pdf</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36884/halc-high-throughput-algorithm-for-long-read-error-correction</guid>
	<pubDate>Fri, 08 Jun 2018 10:47:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36884/halc-high-throughput-algorithm-for-long-read-error-correction</link>
	<title><![CDATA[HALC: High throughput algorithm for long read error correction]]></title>
	<description><![CDATA[HALC, a high throughput algorithm for long read error correction. HALC aligns the long reads to short read contigs from the same species with a relatively low identity requirement so that a long read region can be aligned to at least one contig region, including its true genome region’s repeats in the contigs sufficiently similar to it (similar repeat based alignment approach)

HALC was able to obtain 6.7-41.1% higher throughput than the existing algorithms while maintaining comparable accuracy. The HALC corrected long reads can thus result in 11.4-60.7% longer assembled contigs than the existing algorithms.<p>Address of the bookmark: <a href="https://github.com/lanl001/halc" rel="nofollow">https://github.com/lanl001/halc</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/20440/linux-operating-system-aimed-at-scientists</guid>
	<pubDate>Mon, 19 Jan 2015 08:30:49 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/20440/linux-operating-system-aimed-at-scientists</link>
	<title><![CDATA[Linux operating system aimed at scientists]]></title>
	<description><![CDATA[<p>The Bio-Linux operating system is based on Ubuntu 14.04 LTS (Trusty Tahr), and the previous version was using Ubuntu 12.04 LTS. The developers only use LTS releases and that means that upgrades for this distro don't come along all that often.<br /> <br /> This Linux distribution is aimed at scientists and it comes with more than 250 bioinformatics packages, 50 graphical applications and several hundred command line tools. And this is just skimming the surface of what the OS can do. Users have access to even more apps from the official repositories.</p><h3>Bio-Linux is using an Ubuntu LTS version as its base</h3><p>The fact that it uses Ubuntu LTS versions for the base is a good thing because it means its users won't have to worry about the support. Ubuntu 14.04 LTS is supported until 2019, so people who are using Bio-Linux shouldn't have a problem.<br /> <br /> "An updated Bio-Linux 8 version is now on the website in ISO and OVA versions. As usual, there is no need to download this version if you are an existing user. All updates to existing packages will be applied to your system through the update manager and new packages are all available via apt-get or Synaptic," reads the <a href="http://nebclists.nerc.ac.uk/pipermail/bio-linux-announce/2015-January/000020.html" target="_blank">announcement</a>.<br /> <br /> The changelog also states that a problem that was preventing the desktop to not start on VirtualBox has been fixed, the QIIME and Bowtie-Bio tools have been upgraded, the pandaseq paired end assembler has been added, and the beginners tutorial specific to Bio-Linux 8 has been improved.<br /> <br /> Check out the official announcement for a complete list of changes and updates. You can <a href="http://linux.softpedia.com/get/System/Operating-Systems/Linux-Distributions/Bio-Linux-45495.shtml" target="_blank"><strong>download Bio-Linux 8.0.5</strong></a> right now from Softpedia and give it a spin. It has the Unity desktop and now it runs very well in virtual environments.</p><p>Reference @ http://news.softpedia.com/news/Bioinformatics-Distro-Bio-Linux-8-0-5-Now-Available-for-Download-469867.shtml</p>]]></description>
	<dc:creator>Pranjali Yadav</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37457/nanofilt-filtering-and-trimming-of-long-read-sequencing-data</guid>
	<pubDate>Mon, 30 Jul 2018 12:01:52 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37457/nanofilt-filtering-and-trimming-of-long-read-sequencing-data</link>
	<title><![CDATA[nanofilt: Filtering and trimming of long read sequencing data]]></title>
	<description><![CDATA[<p>Filtering on quality and/or read length, and optional trimming after passing filters.<br>Reads from stdin, writes to stdout.</p>
<p>Intended to be used:</p>
<ul>
<li>directly after fastq extraction</li>
<li>prior to mapping</li>
<li>in a stream between extraction and mapping</li>
</ul>
<p>https://github.com/wdecoster/nanofilt</p><p>Address of the bookmark: <a href="https://github.com/wdecoster/nanofilt" rel="nofollow">https://github.com/wdecoster/nanofilt</a></p>]]></description>
	<dc:creator>Jit</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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