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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/30375?offset=240</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36833/bfc-a-standalone-high-performance-tool-for-correcting-sequencing-errors-from-illumina-sequencing-data</guid>
	<pubDate>Thu, 31 May 2018 09:35:23 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36833/bfc-a-standalone-high-performance-tool-for-correcting-sequencing-errors-from-illumina-sequencing-data</link>
	<title><![CDATA[BFC: a standalone high-performance tool for correcting sequencing errors from Illumina sequencing data]]></title>
	<description><![CDATA[BFC is a standalone high-performance tool for correcting sequencing errors from Illumina sequencing data. It is specifically designed for high-coverage whole-genome human data, though also performs well for small genomes.

The BFC algorithm is a variant of the classical spectrum alignment algorithm introduced by Pevzner et al (2001). It uses an exhaustive search to find a k-mer path through a read that minimizes a heuristic objective function jointly considering penalties on correction, quality and k-mer support. This algorithm was first implemented in my fermi assembler and then refined a few times in fermi, fermi2 and now in BFC. In the k-mer counting phase, BFC uses a blocked bloom filter to filter out most singleton k-mers and keeps the rest in a hash table (Melsted and Pritchard, 2011). The use of bloom filter is how BFC is named, though other correctors such as Lighter and Bless actually rely more on bloom filter than BFC.

https://github.com/lh3/bfc<p>Address of the bookmark: <a href="https://github.com/lh3/bfc" rel="nofollow">https://github.com/lh3/bfc</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/11603/ncbi-webinar</guid>
	<pubDate>Sun, 08 Jun 2014 02:47:01 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/11603/ncbi-webinar</link>
	<title><![CDATA[NCBI Webinar]]></title>
	<description><![CDATA[<p>In less than two weeks, NCBI will offer a webinar entitled "Introducing 3 NCBI Resources to Navigate Testing for Disease Linked Variants: MedGen, GTR and ClinVar". This webinar will delve into the lifecycle of genetic testing and teach attendees how to navigate the NIH Genetic Testing Registry, ClinVar, and MedGen resources. These resources can be used to prepare for clinical cases, access detailed information about orderable genetic tests, interpret test results, and more.</p><p>More at https://attendee.gotowebinar.com/register/8452228815737989634</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36907/higlass-a-tool-for-exploring-genomic-contact-matrices-and-tracks</guid>
	<pubDate>Mon, 11 Jun 2018 09:44:49 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36907/higlass-a-tool-for-exploring-genomic-contact-matrices-and-tracks</link>
	<title><![CDATA[HiGlass: a tool for exploring genomic contact matrices and tracks.]]></title>
	<description><![CDATA[HiGlass is a tool for exploring genomic contact matrices and tracks. Please take a look at the examples and documentation for a description of the ways that it can be configured to explore and compare contact matrices. To load private data, HiGlass can be run locally within a Docker container. The HiC data in the examples below is from Rao et al. (2014)

http://higlass.io/<p>Address of the bookmark: <a href="http://higlass.io/" rel="nofollow">http://higlass.io/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/12111/internship-program-with-arraygen-technolgies</guid>
  <pubDate>Sun, 22 Jun 2014 23:18:31 -0500</pubDate>
  <link></link>
  <title><![CDATA[Internship program with ArrayGen Technolgies]]></title>
  <description><![CDATA[
<p>Internship Program for Bioinformatics / Biotechnology Professionals Currently we offer positions to outstanding students interested in Next Generation Sequencing (NGS) data analysis. Applications are accepted throughout the year. Accepted students will be listed on web with their schedules. Accepted students can attend our future workshops and trainings freely at the specified venue.</p>

<p>Interested candidates may email their resume along with a cover letter to careers@arraygen.com</p>

<p>Official website: http://www.arraygen.com/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37473/lsc-a-long-read-error-correction-tool</guid>
	<pubDate>Thu, 02 Aug 2018 07:39:46 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37473/lsc-a-long-read-error-correction-tool</link>
	<title><![CDATA[LSC :a long read error correction tool]]></title>
	<description><![CDATA[<h2>Getting Started</h2>
<p>These simple steps will help you integrate LSC into your transcriptomics analysis pipeline.</p>
<ul>
<li>Read the&nbsp;<a href="https://www.healthcare.uiowa.edu/labs/au/LSC/LSC_requirements.asp">LSC_requirements</a>&nbsp;for running LSC.</li>
<li><a href="https://www.healthcare.uiowa.edu/labs/au/LSC/LSC_download.asp">Download</a>&nbsp;and set-up the LSC package.</li>
<li>Follow the&nbsp;<a href="https://www.healthcare.uiowa.edu/labs/au/LSC/LSC_tutorial.asp">tutorial</a>&nbsp;to see how LSC works on some example data.</li>
<li>Read the&nbsp;<a href="https://www.healthcare.uiowa.edu/labs/au/LSC/LSC_manual.asp">manual</a>&nbsp;if anything is unclear.</li>
<li>You're ready, Happy LSCing!</li>
</ul>
<h2>Latest publication</h2>
<p><span>Kin Fai Au, Jason Underwood, Lawrence Lee and Wing Hung Wong&nbsp;</span><br><strong>Improving PacBio Long Read Accuracy by Short Read Alignment&nbsp;</strong><span>[</span><a href="http://journals.plos.org/plosone/article?id=10.1371%2Fjournal.pone.0046679">Manuscript</a><span>]&nbsp;</span><br><em>PLoS ONE</em><span>&nbsp;2012. 7(10): e46679. doi:10.1371/journal.pone.0046679</span></p><p>Address of the bookmark: <a href="https://www.healthcare.uiowa.edu/labs/au/LSC/" rel="nofollow">https://www.healthcare.uiowa.edu/labs/au/LSC/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/12566/jrf-at-national-research-centre-on-plant-biotechnology</guid>
  <pubDate>Fri, 04 Jul 2014 13:36:02 -0500</pubDate>
  <link></link>
  <title><![CDATA[JRF at NATIONAL RESEARCH CENTRE ON PLANT BIOTECHNOLOGY]]></title>
  <description><![CDATA[
<p>NATIONAL RESEARCH CENTRE ON PLANT BIOTECHNOLOGY</p>

<p>New Delhi-110012</p>

<p>Walk in interview</p>

<p>Eligible candidates may appear for Walk-in interview for the temporary positions of JRF/SRF/ RA, in ICAR, DBT funded research projects. Positions are purely temporary in nature and are co-terminus with the projects. The initial appointment will be for maximum one year, which can be extended on the basis of assessment of the candidate performance and need in the project work (PI-Dr. N. K. Singh, National Professor).</p>

<p>Name of the</p>

<p>PI (Project)<br />	</p>

<p>Name of</p>

<p>Position<br />	</p>

<p>Number of</p>

<p>positions<br />	</p>

<p>Emoluments</p>

<p>Fixed per</p>

<p>month (Rs.)<br />	</p>

<p>Essential</p>

<p>Qualifications</p>

<p>DBT-“Physical Mapping and Sample sequencing of Wheat Chromosome 2A- International Wheat Genome Sequencing Consortium (India)”.</p>

<p>(Up to Nov,2014)</p>

<p>DBT- Identification and functional analysis of genes related to yield and biotic stresses (Up to Oct,2014)</p>

<p>NPTC-Central Facility<br />	</p>

<p>RA (Master)</p>

<p>JRF/SRF</p>

<p>Research Associate: One</p>

<p>Essential: MCA or M. Tech. (Bioinformatics and computer Science with 2 years experience in Database Management with</p>

<p>MySQL, Linux)</p>

<p>Desirable: Proficiency in handling of large biological databases</p>

<p>Age limit: Max. Age 35 years (Age of relaxation of 5 years for SC/ST&amp; woman. and 3 years for OBC). The interview will be held on 08 July, 2014 at 11 am at room no. 39, NRCPB, LBS Building, Pusa Campus, New Delhi-110012. The candidates must bring original certificates and four copies of biodata, and recent passport size photograph. No TA/DA would be given for the appearance in interview. Only the candidates having essential qualifications would be entertained for the interviews.</p>

<p>Advertisement:</p>

<p>www.nrcpb.org/sites/default/files/news%20paper%20advirtisment..docx</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37576/lrcstats-a-tool-for-evaluating-long-reads-correction-methods</guid>
	<pubDate>Wed, 22 Aug 2018 11:05:04 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37576/lrcstats-a-tool-for-evaluating-long-reads-correction-methods</link>
	<title><![CDATA[LRCstats: a tool for evaluating long reads correction methods]]></title>
	<description><![CDATA[<p><span>LRCstats is an open-source pipeline for benchmarking DNA long read correction algorithms for long reads outputted by third generation sequencing technology such as machines produced by Pacific Biosciences. The reads produced by third generation sequencing technology, as the name suggests, are longer in length than reads produced by next generation sequencing technologies, such as those produced by Illumina. However, long reads are plagued by high error rates, which can cause issues in downstream analysis. Long read correction algorithms reduce the error rate of long reads either through self-correcting methods or using accurate, short reads outputted by next generation sequencing technologies to correct long reads.</span></p><p>Address of the bookmark: <a href="https://github.com/cchauve/lrcstats" rel="nofollow">https://github.com/cchauve/lrcstats</a></p>]]></description>
	<dc:creator>Aaryan Lokwani</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/12988/guest-lecturer-molecular-biology-bioinformatics</guid>
  <pubDate>Wed, 23 Jul 2014 13:34:41 -0500</pubDate>
  <link></link>
  <title><![CDATA[Guest Lecturer - Molecular Biology &amp; Bioinformatics]]></title>
  <description><![CDATA[
<p>Adv. No. F.TU/ACA/GT-APP/01/14 Date: 07.07.2014</p>

<p>Faculty of Science</p>

<p>Essential Qualifications:</p>

<p>(i) Good academic record having at least 55% marks (or an equivalent grade in a point scale wherever grading system is followed) at the Master’s Degree level in a relevant subject, from an Indian University, or an equivalent degree from an accredited foreign University.</p>

<p>(II) Besides fulfilling the above qualifications, the candidates must have cleared the National Eligibility Test (NET) conducted by the UGC, CSIR or similar test accredited by the UGC like SLET/SET.</p>

<p>(III) Notwithstanding anything contained in sub-clauses (i) and (ii) of clause 4.4.1 of UGC regulations 2010, candidates, who are, or have been awarded a Ph.D. Degree in accordance with the University Grants Commission (Minimum Standards and Procedure for Award of Ph.D. Degree) Regulations, 2009, shall be exempted from the requirement of the minimum eligibility condition of NET/ SLET/ SET for engagement of guest Teacher.</p>

<p>(IV) NET/ SLET/ SET shall also not be required for such Master’s Degree Programmes in discipline for which NET/ SLET/ SET is not conducted.</p>

<p>Application form along with detailed instructions can be downloaded from Tripura University website: www.tripurauniv.in. The duly filled in application forms complete in all respects may be sent so as to reach the Office of the Deputy Registrar Academic Branch, Tripura University, Suryamaninagar - 799022, Tripura on or before 31st July, 2014. The Candidates who responded against advertisement No. TU.REG/N-Advt./02/10 dated 20.02.2014 need not apply again.</p>

<p>For more info visit: http://www.tripurauniv.in/images/universitymedia/EmploymentNotification/Guest%20Teacher%20Advt.%20website_09072014.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37837/clipcrop-a-tool-for-detecting-structural-variations-with-single-base-resolution-using-soft-clipping-information</guid>
	<pubDate>Thu, 04 Oct 2018 16:39:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37837/clipcrop-a-tool-for-detecting-structural-variations-with-single-base-resolution-using-soft-clipping-information</link>
	<title><![CDATA[ClipCrop: a tool for detecting structural variations with single-base resolution using soft-clipping information]]></title>
	<description><![CDATA[<p>This is a tool for detecting structural variations using soft-clipping information From&nbsp;<a href="http://samtools.sourceforge.net/SAM1.pdf">SAM</a>&nbsp;files.</p>
<p>https://github.com/shinout/clipcrop</p><p>Address of the bookmark: <a href="https://github.com/shinout/clipcrop" rel="nofollow">https://github.com/shinout/clipcrop</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/14215/the-8000-years-old-tibetian-gene-mutation</guid>
	<pubDate>Wed, 20 Aug 2014 21:57:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/14215/the-8000-years-old-tibetian-gene-mutation</link>
	<title><![CDATA[The 8000 years old Tibetian gene mutation !!!]]></title>
	<description><![CDATA[<p>A new study has provided insight into how gene mutation around 8,000 years ago helped Tibetans' to survive in the thin air on the Tibetan Plateau, where an average elevation is of 14,800 feet.<br /><br />A study led by University of Utah scientists is the first to find a genetic cause for the adaptation, a single DNA base pair change that dates back 8,000 years and demonstrate how it contributes to the Tibetans' ability to live in low oxygen conditions.</p><p>About 8,000 years ago, the gene EGLN1 changed by a single DNA base pair. Today, a relatively short time later on the scale of human history, 88 percent of Tibetans have the genetic variation, and it was virtually absent from closely related lowland Asians. The findings indicate the genetic variation endows its carriers with an advantage.<br /><br />In those without the adaptation, low oxygen caused their blood to become thick with oxygen-carrying red blood cells, an attempt to feed starved tissues, which could cause long-term complications such as heart failure. The researchers found that the newly identified genetic variation protected Tibetans by decreasing the over-response to low oxygen.</p><p>Reference: http://www.nature.com/nature/journal/v512/n7513/abs/nature13408.html</p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>

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