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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/30144?offset=1240</link>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/21893/postdoctoral-fellowship-in-bioinformatics-and-evolutionary-genomics</guid>
  <pubDate>Wed, 01 Apr 2015 21:36:42 -0500</pubDate>
  <link></link>
  <title><![CDATA[Postdoctoral Fellowship in Bioinformatics and Evolutionary Genomics]]></title>
  <description><![CDATA[
<p>Postdoctoral Fellowship in Bioinformatics and Evolutionary Genomics<br />Organization<br />National Human Genome Research Institute, National Institutes of Health<br />http://genome.gov/Staff/Baxevanis<br />Job Location<br />Bethesda, MD<br />Job Description</p>

<p>A postdoctoral training position is currently available in the Computational and Statistical Genomics Branch (CSGB) of the National Human Genome Research Institute (NHGRI). The position is located in the laboratory of Andy Baxevanis, Ph.D., whose research group uses comparative genomics approaches to better-understand the molecular innovations that drove the surge of diversity in early animal evolution. The overarching theme of Dr. Baxevanis’ research program is focused on how non-traditional animal models convey critical insights into human disease research.</p>

<p>Candidates should have or be close to obtaining a Ph.D. or equivalent degree in bioinformatics, computational biology, computer science, molecular biology, or a closely related field. Candidates with a background in evolutionary biology are particularly encouraged to apply. Programming skills and experience in the application of computational methods to genomic data are highly desirable. Applicants must possess good communication skills and be fluent in both spoken and written English. The ability to learn how to use new software and quickly become expert in its use, critical thinking, problem-solving abilities, and the ability to work semi-independently are required.<br />How to Apply</p>

<p>Interested applicants should submit a curriculum vitae, a detailed letter of interest, and the names of three potential referees to Dr. Baxevanis at andy@mail.nih.gov.<br />About Our Organization</p>

<p>The NIH Intramural Research Program is on the Bethesda, Maryland campus and offers a wide array of training opportunities for scientists early in their careers. The funding for this position is stable and offers the trainee wide latitude in the design and pursuit of their research project. The successful candidate will have access to NHGRI’s established and robust bioinformatics infrastructure, as well as resources made available through NIH’s Center for Information Technology (CIT) and the National Center for Biotechnology Information (NCBI).</p>

<p>For more information on CSGB and NHGRI’s Intramural Research Program, please see http://genome.gov/DIR/.</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37737/rebaler-program-for-conducting-reference-based-assemblies-using-long-reads</guid>
	<pubDate>Tue, 18 Sep 2018 07:52:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37737/rebaler-program-for-conducting-reference-based-assemblies-using-long-reads</link>
	<title><![CDATA[Rebaler: program for conducting reference-based assemblies using long reads.]]></title>
	<description><![CDATA[<p>Rebaler is a program for conducting reference-based assemblies using long reads. It relies mainly on&nbsp;<a href="https://github.com/lh3/minimap2">minimap2</a>&nbsp;for alignment and&nbsp;<a href="https://github.com/isovic/racon">Racon</a>&nbsp;for making consensus sequences.</p>
<p>I made Rebaler for bacterial genomes (specifically for the task of&nbsp;<a href="https://github.com/rrwick/Basecalling-comparison">testing basecallers</a>). It should in principle work for non-bacterial genomes as well, but I haven't tested it.</p><p>Address of the bookmark: <a href="https://github.com/rrwick/Rebaler" rel="nofollow">https://github.com/rrwick/Rebaler</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/21934/ra-bioinformatics-at-bose-institute</guid>
  <pubDate>Tue, 07 Apr 2015 03:30:25 -0500</pubDate>
  <link></link>
  <title><![CDATA[RA Bioinformatics at Bose Institute]]></title>
  <description><![CDATA[
<p>Bose Institute, Kolkata, invites online applications from Indian Citizens for recruitment of Research Associate (05 posts) under Institute Plan Programmes : Improvement of Plants : Biotechnological, Genomic and Proteomic Approaches (programme No. – I), Bioinformatics and Computational Biology (programme No. – III), Microbial Genomics and Infection Biology (programme No. – V) and Basic &amp; Applied Problems in Physical and Environmental Sciences (programme No. – VII). All the posts are tenable for one (01) year.</p>

<p>ESSENTIAL QUALIFICATION: PH.D. DEGREE IN LIFE SCIENCES / PHYSICAL SCIENCE.</p>

<p>Research Associate for Programme No. –I Specialization in the area of plant molecular biology or plant proteomic study or plant pathogen interaction.<br />Research Associate for Programme No. –I Specialization in the area of plant / fungal Biotechnology, tissue culture and molecular biology<br />Research Associate for Programme No. –III Specialization in the area of structural biology and protein crystallography.<br />Research Associate for Programme No. – V Specialization in the area of microbial physiology (metabolism) or environmental microbiology, with experience in microbial genomics and proteomics.<br />Research Associate for Programme No. – VII Specialization in the area of Theoretical High Energy Astrophysics or Astroparticle Physics. Proven record of independent research experience in Astrophysical<br />Radiation Magnetohydrodynamics or Cosmic Ray Astrophysics. Experience in numerical techniques and /or date analysis would be additional advantage.<br />Associateship : 22,000/- p.m., plus admissible H.R.A. and Medical benefit.<br />Age: Below 3 Age : Below 35 years (Relaxable in case of SC/ST/OBC/Women candidates only as per rule).<br />SELECTION PROCEDURE FOR BOSE INSTITUTE- RESEARCH ASSOCIATE POST:</p>

<p>Candidates can apply on or before 13/4/2015.<br />No detailed information about the selection procedure is mentioned in the recruitment notification.<br />HOW TO APPLY FOR RESEARCH ASSOCIATE VACANCY IN BOSE INSTITUTE:</p>

<p>Interested and eligible candidates may read the application procedures and instructions carefully before applying through online as well as submitting the hard copy of the same. Candidates those who has submitted their Ph.D. Thesis and can produce Provisional Ph.D. Certificate at the time of Interview may also apply </p>

<p>Ref<br />Bose Institute Recruitment 2015 –  ADVT. NO. : BI/IF/35/2014-15.</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38299/deepbinner-a-signal-level-demultiplexer-for-oxford-nanopore-reads</guid>
	<pubDate>Tue, 27 Nov 2018 03:38:49 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38299/deepbinner-a-signal-level-demultiplexer-for-oxford-nanopore-reads</link>
	<title><![CDATA[Deepbinner: a signal-level demultiplexer for Oxford Nanopore reads]]></title>
	<description><![CDATA[<p>Deepbinner is a tool for demultiplexing barcoded&nbsp;<a href="https://nanoporetech.com/">Oxford Nanopore</a>&nbsp;sequencing reads. It does this with a deep&nbsp;<a href="https://adeshpande3.github.io/adeshpande3.github.io/A-Beginner's-Guide-To-Understanding-Convolutional-Neural-Networks/">convolutional neural network</a>&nbsp;classifier, using many of the&nbsp;<a href="https://towardsdatascience.com/neural-network-architectures-156e5bad51ba">architectural advances</a>&nbsp;that have proven successful in image classification. Unlike other demultiplexers (e.g. Albacore and&nbsp;<a href="https://github.com/rrwick/Porechop">Porechop</a>), Deepbinner identifies barcodes from the raw signal (a.k.a. squiggle) which gives it greater sensitivity and fewer unclassified reads.</p>
<ul>
<li><span>Reasons to use Deepbinner</span>:
<ul>
<li>To minimise the number of unclassified reads (use Deepbinner by itself).</li>
<li>To minimise the number of misclassified reads (use Deepbinner in conjunction with Albacore demultiplexing).</li>
<li>You plan on running signal-level downstream analyses, like&nbsp;<a href="https://github.com/jts/nanopolish">Nanopolish</a>. Deepbinner can&nbsp;<a href="https://github.com/rrwick/Deepbinner#using-deepbinner-before-basecalling">demultiplex the fast5 files</a>which makes this easier.</li>
</ul>
</li>
<li><span>Reasons to&nbsp;<em>not</em>&nbsp;use Deepbinner</span>:
<ul>
<li>You only have basecalled reads not the raw fast5 files (which Deepbinner requires).</li>
<li>You have a small/slow computer. Deepbinner is more computationally intensive than&nbsp;<a href="https://github.com/rrwick/Porechop">Porechop</a>.</li>
<li>You used a sequencing/barcoding kit other than&nbsp;<a href="https://github.com/rrwick/Deepbinner/blob/master/models">the ones Deepbinner was trained on</a>.</li>
</ul>
</li>
</ul><p>Address of the bookmark: <a href="https://github.com/rrwick/Deepbinner" rel="nofollow">https://github.com/rrwick/Deepbinner</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/poll/view/21982/which-bioinformatics-journals-do-you-follow</guid>
	<pubDate>Fri, 10 Apr 2015 12:10:21 -0500</pubDate>
	<link>https://bioinformaticsonline.com/poll/view/21982/which-bioinformatics-journals-do-you-follow</link>
	<title><![CDATA[Which Bioinformatics Journals Do You Follow?]]></title>
	<description><![CDATA[<p><span><span>Which are your favorite bioinformatics journals? The ones that you check every month or so, or that you are subscribed to?</span></span></p>]]></description>
	<dc:creator>Tenzin Paul</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40516/nextdenovo-string-graph-based-de-novo-assembler-for-tgs-long-reads</guid>
	<pubDate>Sun, 05 Jan 2020 04:08:29 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40516/nextdenovo-string-graph-based-de-novo-assembler-for-tgs-long-reads</link>
	<title><![CDATA[NextDenovo: string graph-based de novo assembler for TGS long reads]]></title>
	<description><![CDATA[<p>NextDenovo is a string graph-based<span>&nbsp;</span><em>de novo</em><span>&nbsp;</span>assembler for TGS long reads. It uses a "correct-then-assemble" strategy similar to canu, but requires significantly less computing resources and storages. After assembly, the per-base error rate is about 97-98%, to further improve single base accuracy, please use<span>&nbsp;</span><a href="https://github.com/Nextomics/NextPolish">NextPolish</a>.</p>
<p>NextDenovo contains two core modules: NextCorrect and NextGraph. NextCorrect can be used to correct TGS long reads with approximately 15% sequencing errors, and NextGraph can be used to construct a string graph with corrected reads. It also contains a modified version of<span>&nbsp;</span><a href="https://github.com/lh3/minimap2">minimap2</a><span>&nbsp;</span>for adapting input and output and producing more sensitive and accurate dovetail overlaps, and some useful utilities (see<span>&nbsp;</span><a href="https://github.com/Nextomics/NextDenovo/blob/master/doc/UTILITY.md">here</a><span>&nbsp;</span>for more details).</p><p>Address of the bookmark: <a href="https://github.com/Nextomics/NextDenovo" rel="nofollow">https://github.com/Nextomics/NextDenovo</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/22028/walk-in-for-research-asst-programmer-enterovirus-research-centre-mumbai-india</guid>
  <pubDate>Tue, 14 Apr 2015 12:36:51 -0500</pubDate>
  <link></link>
  <title><![CDATA[Walk in for Research Asst &amp; Programmer Enterovirus Research Centre Mumbai - India]]></title>
  <description><![CDATA[
<p>Enterovirus Research Centre Mumbai Jobs 2015 –</p>

<p>Walk in for Research Asst &amp; Programmer Posts: Enterovirus Research Centre, Mumbai, Indian Council of Medical Research has issued notification for the recruitment of Research Asst &amp; Programmer vacancies on temporary basis for the project entitled “An Atlas of Non-Polio Enterovirus Types Isolated from Cases of Acute Flaccid Paralysis in India”. Eligible candidates may walk in on 20-04-2015 from 10:00 AM to 12:00 Noon. Other details like age limit, educational qualification, how to apply are given below…</p>

<p>Enterovirus Research Centre Mumbai Vacancy Details:<br />Total No. of Posts: 04<br />Name of the Posts:<br />1. Research Assistant: 03 Posts<br />2. Programmer: 01 Post</p>

<p>Age Limit: Candidates age should below 28 years. Age relaxations are applicable as per rules.</p>

<p>Educational Qualification: Candidates should have M.Sc (1st Class) in Microbiology/ Bioinformatics/ Biotechnology/ Life Science for post 1, BE/ B.Tech/ MCA for post 2.</p>

<p>Selection Process: Candidates are selected based on their performance in interview.</p>

<p>How to Apply: Eligible candidates may attend for interview along with original certificates, CV, attested copies of relevant certificates, one recent passport size photograph duly affixed on right side of application at Enterovirus Research Centre, Mumbai, Indian Council of Medical Research, Haffkine Institute Cmpound, Acharya Donde Marg, Parel, Mumbai-400012 on 20-04-2015 from 10:00 AM to 12:00 Noon.</p>

<p>Important Dates:<br />Date &amp; Time of Interview: 20-04-2015 from 10:00 AM to 12:00 Noon.<br />Registration Time: 12:00 Noon.</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40972/deepbinner-a-signal-level-demultiplexer-for-oxford-nanopore-reads</guid>
	<pubDate>Mon, 10 Feb 2020 02:45:53 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40972/deepbinner-a-signal-level-demultiplexer-for-oxford-nanopore-reads</link>
	<title><![CDATA[Deepbinner: a signal-level demultiplexer for Oxford Nanopore reads]]></title>
	<description><![CDATA[<p>Deepbinner is a tool for demultiplexing barcoded <a href="https://nanoporetech.com/">Oxford Nanopore</a> sequencing reads. It does this with a deep <a href="https://adeshpande3.github.io/adeshpande3.github.io/A-Beginner's-Guide-To-Understanding-Convolutional-Neural-Networks/">convolutional neural network</a> classifier, using many of the <a href="https://towardsdatascience.com/neural-network-architectures-156e5bad51ba">architectural advances</a> that have proven successful in image classification. Unlike other demultiplexers (e.g. Albacore and <a href="https://github.com/rrwick/Porechop">Porechop</a>), Deepbinner identifies barcodes from the raw signal (a.k.a. squiggle) which gives it greater sensitivity and fewer unclassified reads.</p><p>Address of the bookmark: <a href="https://github.com/rrwick/Deepbinner" rel="nofollow">https://github.com/rrwick/Deepbinner</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/22050/binc-sample-question-paper</guid>
	<pubDate>Thu, 16 Apr 2015 09:15:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/file/view/22050/binc-sample-question-paper</link>
	<title><![CDATA[BINC Sample Question Paper !!!]]></title>
	<description><![CDATA[<p>BINC sample question paper round THREE ...</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/22050" length="316" type="text/plain" />
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42132/squeezemeta-a-fully-automated-metagenomics-pipeline-from-reads-to-bins</guid>
	<pubDate>Mon, 17 Aug 2020 05:25:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42132/squeezemeta-a-fully-automated-metagenomics-pipeline-from-reads-to-bins</link>
	<title><![CDATA[SqueezeMeta: a fully automated metagenomics pipeline, from reads to bins]]></title>
	<description><![CDATA[<p>SqueezeMeta is a full automatic pipeline for metagenomics/metatranscriptomics, covering all steps of the analysis. SqueezeMeta includes multi-metagenome support allowing the co-assembly of related metagenomes and the retrieval of individual genomes via binning procedures. Thus, SqueezeMeta features several unique characteristics:</p>
<ol>
<li>Co-assembly procedure with read mapping for estimation of the abundances of genes in each metagenome</li>
<li>Co-assembly of a large number of metagenomes via merging of individual metagenomes</li>
<li>Includes binning and bin checking, for retrieving individual genomes</li>
<li>The results are stored in a database, where they can be easily exported and shared, and can be inspected anywhere using a web interface.</li>
<li>Internal checks for the assembly and binning steps inform about the consistency of contigs and bins, allowing to spot potential chimeras.</li>
<li>Metatranscriptomic support via mapping of cDNA reads against reference metagenomes</li>
</ol><p>Address of the bookmark: <a href="https://github.com/jtamames/SqueezeMeta" rel="nofollow">https://github.com/jtamames/SqueezeMeta</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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