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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/44352?offset=670</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34867/magic-blast-a-tool-for-mapping-large-next-generation-rna-or-dna-sequencing-runs-against-a-whole-genome-or-transcriptome</guid>
	<pubDate>Tue, 26 Dec 2017 22:23:39 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34867/magic-blast-a-tool-for-mapping-large-next-generation-rna-or-dna-sequencing-runs-against-a-whole-genome-or-transcriptome</link>
	<title><![CDATA[Magic-BLAST: a tool for mapping large next-generation RNA or DNA sequencing runs against a whole genome or transcriptome.]]></title>
	<description><![CDATA[<p>Magic-BLAST is a tool for mapping large next-generation RNA or DNA sequencing runs against a whole genome or transcriptome. Each alignment optimizes a composite score, taking into account simultaneously the two reads of a pair, and in case of RNA-seq, locating the candidate introns and adding up the score of all exons. This is very different from other versions of BLAST, where each exon is scored as a separate hit and read-pairing is ignored.</p>
<p>Magic-BLAST incorporates within the NCBI BLAST code framework ideas developed in the NCBI Magic pipeline, in particular hit extensions by local walk and jump&nbsp;<a href="http://www.ncbi.nlm.nih.gov/pubmed/26109056">(http://www.ncbi.nlm.nih.gov/pubmed/26109056)</a>, and recursive clipping of mismatches near the edges of the reads, which avoids accumulating artefactual mismatches near splice sites and is needed to distinguish short indels from substitutions near the edges.</p><p>Address of the bookmark: <a href="https://ncbi.github.io/magicblast/" rel="nofollow">https://ncbi.github.io/magicblast/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/8174/the-2014-cemm-phd-program</guid>
  <pubDate>Wed, 05 Feb 2014 06:03:15 -0600</pubDate>
  <link></link>
  <title><![CDATA[The 2014 CeMM PhD Program]]></title>
  <description><![CDATA[
<p>For our next PhD Program starting in October 2014 we are looking for exceptionally motivated PhD candidates with a keen interest in genomics and medicine and a strong interest to work in teams.</p>

<p>The 2014 CeMM PhD Program will focus on two thematic areas: INFECTION and CANCER, that are built on the pillars of epigenetics, bioinformatics and systems biology, chemical biology and the mechanism of action of drugs, high-throughput genetics, genomics and proteomics, and molecular and cell biology.</p>

<p>The choice of this strategic focus rests on the synergies between immunology, infection and cancer in pathophysiological and technological terms. It furthermore reflects the strength of the current CeMM faculty, itself built around the historical and contemporary expertise in immunology and cancer of the Medical University of Vienna.</p>

<p>As a CeMM PhD student you will get the chance to work at the cutting edge of interdisciplinary molecular medicine research and be trained by the entire CeMM and associated faculty to become one of the scientists shaping the future of molecular medicine.<br />Requirements</p>

<p>To be eligible to enroll in the CeMM PhD Program all candidates are required to have a bachelor’s or master’s degree in medicine, biology, chemistry, bioinformatics, mathematics or any scientific/technical, subject-relevant degree. Candidates do not need to have completed their degree at the time of application, however they must have obtained their final degree certificate by mid-September. The working language at CeMM is English, so excellent written and oral communication skills in English are required.<br />Timeline</p>

<p>    Applications open on 20th January and close on 20th March 2014.<br />    Two references are required to be submitted through the online system by 31st March 2014.<br />    All complete candidate applications are reviewed by the CeMM Faculty in early April.<br />    Selected candidates are invited to a Skype panel interview in late April.<br />    Shortlisted candidates are then invited to Vienna in May for a full interview process, including an opportunity to introduce yourself through a presentation and interview rounds, meet research group members, and attend an informal dinner to get to know the Faculty members and learn more about their research.<br />    Positions are offered by CeMM Faculty in June.<br />    Start of PhD Program: 1st October 2014 .</p>

<p>Contact</p>

<p>Binia Maria Günther, BEd BA<br />Human Resources Manager<br />bguenther@cemm.oeaw.ac.at</p>

<p>Catherine Lloyd, Ph.D.<br />PhD and Postdoc Program Manager<br />clloyd@cemm.oeaw.ac.at</p>

<p>More Info: www.cemm.oeaw.ac.at/phd-program/application/</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35883/arcs-scaffolding-genome-drafts-with-linked-reads</guid>
	<pubDate>Tue, 06 Mar 2018 16:35:26 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35883/arcs-scaffolding-genome-drafts-with-linked-reads</link>
	<title><![CDATA[ARCS: scaffolding genome drafts with linked reads]]></title>
	<description><![CDATA[<p><span>ARCS, an application that utilizes the barcoding information contained in linked reads to further organize draft genomes into highly contiguous assemblies. We show how the contiguity of an ABySS&nbsp;</span><em>H.sapiens</em><span>genome assembly can be increased over six-fold, using moderate coverage (25-fold) Chromium data. We expect ARCS to have broad utility in harnessing the barcoding information contained in linked read data for connecting high-quality sequences in genome assembly drafts.</span></p><p>Address of the bookmark: <a href="https://github.com/bcgsc/ARCS/" rel="nofollow">https://github.com/bcgsc/ARCS/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/8123/jrf-manit</guid>
  <pubDate>Sun, 02 Feb 2014 03:07:58 -0600</pubDate>
  <link></link>
  <title><![CDATA[JRF @ MANIT]]></title>
  <description><![CDATA[
<p>MAULANA AZAD NATIONAL INSTITUTE OF TECHNOLOGY BHOPAL</p>

<p>No. CSE/14/1038</p>

<p>Walk in Interview for the post of JRF under TEQIP-II</p>

<p>SN Department – Qualification Post Graduation – Time</p>

<p>1 Bio-Informatics &amp; Mathematics M.Tech Bio-informatics/M.Sc.* Maths  10.00 AM</p>

<p>2 Biological Sciences M.Sc.* in any branch of Biological Sciences 10.30 AM</p>

<p>3 Chemical Engineering M.Tech Chemical Engineering 11.00 AM</p>

<p>4 Chemistry M.Sc.* Chemistry 11.30 AM</p>

<p>5 Civil Engineering M.Tech Structure/GeoTech. /Water -Resources/Hydraulics/Environment/Transport 12.00 Noon</p>

<p>6 GIS M.Tech GIS/Civil 12.30 PM</p>

<p>7 Computer Science &amp; Engineering M.Tech CSE/Information Security 01.00 PM</p>

<p>8 Electrical Engineering M.Tech Electrical Derives 01.30 PM</p>

<p>9 Electronics &amp; Communication M.Tech Digital Communication 02.00 PM</p>

<p>10 MSME M.Tech Material Science/ Mechanical/Metallurgy 02.30 PM</p>

<p>11 Physics M.Sc.* Physics 03.00 PM</p>

<p>* M.Sc. with NET/GATE qualified</p>

<p>Resume along with one passport size photograph and relevant documents are required at the time of interview</p>

<p>Amount of Fellowship: Rs 18000/-month+ HRA</p>

<p>Duration: 31st Dec 2014 (End of TEQIP-II project)</p>

<p>Date of Interview: 7th  February 2014</p>

<p>Venue Institute Committee Room</p>

<p>Advertisement:</p>

<p>http://www.manit.ac.in/manitbhopal/Year2014/Recruitment/Advertisement%20JRF.pdf</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36830/crossmap-a-program-for-convenient-conversion-of-genome-coordinates</guid>
	<pubDate>Thu, 31 May 2018 06:00:47 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36830/crossmap-a-program-for-convenient-conversion-of-genome-coordinates</link>
	<title><![CDATA[CrossMap: a program for convenient conversion of genome coordinates]]></title>
	<description><![CDATA[CrossMap is a program for convenient conversion of genome coordinates (or annotation files) between different assemblies (such as Human hg18 (NCBI36) &lt;&gt; hg19 (GRCh37), Mouse mm9 (MGSCv37) &lt;&gt; mm10 (GRCm38)).

It supports most commonly used file formats including SAM/BAM, Wiggle/BigWig, BED, GFF/GTF, VCF.

CrossMap is designed to liftover genome coordinates between assemblies. 

It’s not a program for aligning sequences to reference genome.

We do not recommend using CrossMap to convert genome coordinates between species.<p>Address of the bookmark: <a href="http://crossmap.sourceforge.net" rel="nofollow">http://crossmap.sourceforge.net</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/8287/post-doc-in-computational-genetics-and-genomics-at-ceinge-biotecnologie-avanzate-naples-italy</guid>
  <pubDate>Tue, 11 Feb 2014 08:06:47 -0600</pubDate>
  <link></link>
  <title><![CDATA[Post doc in Computational Genetics and Genomics at CEINGE Biotecnologie Avanzate, Naples, Italy]]></title>
  <description><![CDATA[
<p>We are seeking one motivated scientist to analyze genomics and transcriptomics data of a large collection of neuroblastoma tumors. The successful candidate will be part of a team of researchers with extensive expertise in genome cancer study. He/she will be involved in the analysis of DNA-seq, RNA-seq, ChIP-seq data using available methods running in R and UNIX environment.</p>

<p>Qualifications</p>

<p>PhD or Post-Graduated Master degree is required. Successful candidates will have some expertise in data analysis of NGS data by using methods running in R and UNIX environment. Familiarity with genome databases and browsers is required.</p>

<p>Application</p>

<p>Candidates should send a CV and a brief personal statement focusing on their skills and interests related to the research project.</p>

<p>Contacts</p>

<p>Start date: 1° April 2014<br />Salary on grant: 25,000 euros per year.<br />Contact Person (Referent): Mario Capasso<br />Ref. Email: mario.capasso@unina.it and achille.iolascon@unina.it<br />Tel: +39 081 3737889</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/36952/getoptspl-file</guid>
	<pubDate>Fri, 15 Jun 2018 04:43:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/file/view/36952/getoptspl-file</link>
	<title><![CDATA[getopts.pl file]]></title>
	<description><![CDATA[
<p>SSPACE_longread complain for getopts.pl file. </p>

<p>To resolve this, download and have in SSPACED-Longreads folder. </p>

<p>Cheers :)</p>
]]></description>
	<dc:creator>Jit</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/36952" length="942" type="text/plain" />
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/8317/new-version-of-modeller-913</guid>
	<pubDate>Thu, 13 Feb 2014 09:07:57 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/8317/new-version-of-modeller-913</link>
	<title><![CDATA[New version of Modeller, 9.13]]></title>
	<description><![CDATA[<p>The new version of Modeller, 9.13, is now available for download! Please see the download page at <a href="http://www.facebook.com/l.php?u=http%3A%2F%2Fsalilab.org%2Fmodeller%2F&amp;h=mAQG5wo_Z&amp;enc=AZOoq2B7BxT95AT3Mw3za3VlbmRFke43YMI5vAjCAbBlIcf3bptn8pmFC1Idxrssy98117S03IgdcNmEWcQBi9bmi8Or_ut1D1yybt1ZonvPoCT3_LOglcYV7o6bEaa442_6LhbjefEaelkq0aq6dl0w&amp;s=1" target="_blank">http://salilab.org/modeller/</a> for more information.</p><p><img src="http://salilab.org/modeller/gifs/modeller.jpg" alt="image" width="848" height="272" style="border: 0px; border: 0px;"><br /> <br /> If you have a license key for Modeller 8 or 9, there is no need to reregister for Modeller 9.13 - the same license key will work. (It won't <span>do any harm to reregister if you want to, though!)<br /> <br /> 9.13 is primarily a bugfix release relative to the last public release(9.12). Major user-visible changes include:<br /> <br /> # Modeller now includes a variety of SOAP (statistically optimized atomic potential) scores for assessing proteins, loops, and interfaces.<br /> <br /> # The Lennard-Jones interaction energy is now artificially truncated at very short distance; this makes simulations with poor starting conditions much less likely to 'blow up'.<br /> <br /> # model.get_insertions(), model.get_deletions() and model.loops() now have an include_termini option; if False, residue ranges that include chain termini are excluded from the output.<br /> <br /> See the Modeller manual for a full change log: <a href="http://salilab.org/modeller/9.13/manual/node39.html" target="_blank">http://salilab.org/modeller/9.13/manual/node39.html</a><br /> <br /> If you encounter bugs in Modeller 9.13, please see <a href="http://salilab.org/modeller/9.13/manual/node10.html" target="_blank">http://salilab.org/modeller/9.13/manual/node10.html</a> for information on how to report them.</span></p><p><span>Reference:</span></p><p><span>http://salilab.org/modeller/</span></p>]]></description>
	<dc:creator>Radha Agarkar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37239/kat-a-k-mer-analysis-toolkit-to-quality-control-ngs-datasets-and-genome-assemblies</guid>
	<pubDate>Fri, 06 Jul 2018 03:36:45 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37239/kat-a-k-mer-analysis-toolkit-to-quality-control-ngs-datasets-and-genome-assemblies</link>
	<title><![CDATA[KAT: a K-mer analysis toolkit to quality control NGS datasets and genome assemblies]]></title>
	<description><![CDATA[<p>KAT is a suite of tools that analyse jellyfish hashes or sequence files (fasta or fastq) using kmer counts. The following tools are currently available in KAT:</p>
<ul>
<li><span>hist</span>: Create an histogram of k-mer occurrences from a sequence file. Adds metadata in output for easy plotting.</li>
<li><span>gcp:</span>&nbsp;K-mer GC Processor. Creates a matrix of the number of K-mers found given a GC count and a K-mer count.</li>
<li><span>comp</span>: K-mer comparison tool. Creates a matrix of shared K-mers between two (or three) sequence files or hashes.</li>
<li><span>sect</span>: SEquence Coverage estimator Tool. Estimates the coverage of each sequence in a file using K-mers from another sequence file.</li>
<li><span>blob</span>: Given, reads and an assembly, calculates both the read and assembly K-mer coverage along with GC% for each sequence in the assembly.SEquence Coverage estimator Tool.</li>
<li><span>filter</span>: Filtering tools. Contains tools for filtering k-mer hashes and FastQ/A files:
<ul>
<li><span>kmer</span>: Produces a k-mer hash containing only k-mers within specified coverage and GC tolerances.</li>
<li><span>seq</span>: Filters a sequence file based on whether or not the sequences contain k-mers within a provided hash.</li>
</ul>
</li>
<li><span>plot</span>: Plotting tools. Contains several plotting tools to visualise K-mer and compare distributions. The following plot tools are available:
<ul>
<li><span>density</span>: Creates a density plot from a matrix created with the "comp" tool. Typically this is used to compare two K-mer hashes produced by different NGS reads.</li>
<li><span>profile</span>: Creates a K-mer coverage plot for a single sequence. Takes in fasta coverage output coverage from the "sect" tool</li>
<li><span>spectra-cn</span>: Creates a stacked histogram using a matrix created with the "comp" tool. Typically this is used to compare a jellyfish hash produced from a read set to a jellyfish hash produced from an assembly. The plot shows the amount of distinct K-mers absent, as well as the copy number variation present within the assembly.</li>
<li><span>spectra-hist</span>: Creates a K-mer spectra plot for a set of K-mer histograms produced either by jellyfish-histo or kat-histo.</li>
<li><span>spectra-mx</span>: Creates a K-mer spectra plot for a set of K-mer histograms that are derived from selected rows or columns in a matrix produced by the "comp".</li>
</ul>
</li>
</ul>
<p>In addition, KAT contains a python script for analysing the mathematical distributions present in the K-mer spectra in order to determine how much content is present in each peak.</p>
<p>This README only contains some brief details of how to install and use KAT. For more extensive documentation please visit:&nbsp;<a href="https://kat.readthedocs.org/en/latest/">https://kat.readthedocs.org/en/latest/</a></p>
<p><a href="https://academic.oup.com/bioinformatics/article/33/4/574/2664339">https://academic.oup.com/bioinformatics/article/33/4/574/2664339&nbsp;</a></p><p>Address of the bookmark: <a href="https://github.com/TGAC/KAT" rel="nofollow">https://github.com/TGAC/KAT</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/fun/view/8509/the-best-bioinformatics-computational-biology-quotes</guid>
	<pubDate>Wed, 26 Feb 2014 17:50:59 -0600</pubDate>
	<link>https://bioinformaticsonline.com/fun/view/8509/the-best-bioinformatics-computational-biology-quotes</link>
	<title><![CDATA[The Best Bioinformatics / Computational Biology Quotes]]></title>
	<description><![CDATA[<p><img src="http://bioinformaticsonline.com/mod//photo/hahaha.png" style="border: 0; border: 0px;" alt="image"></p><p>Bioinformatician are not anti-social; We are just genome friendly.</p><p>Bioinformatician would love to change the biological world, but they won't give us the genetic code :P</p><p>If at first you don't succeed; call it version 1.0</p><p>The glass is neither half-full nor half-empty: it's actually have several genomes.</p><p>I'm BioGeek.</p><p>Fedup with LIPS, try God script.</p><p>Idiot, Go ahead, make my data!</p><p>Thank god, my genome just compiled.</p><p>Error message: "Out of space on genome drive:"</p><p>Shut up mobile elements, or i'll flush you out.</p><p>Never underestimate the internet bandwidth, u gotta incomplete.</p><p>Applied fuzzy logic to understand God's logic?</p><p>Warning! Overflow, delete chromosome !</p><p>Be nice to the BioGeek, for all you know they might be the next curator!</p><p>Beware of computational biologist they screw genes and protein.</p><p>Warning! Your genome is full of garbage, delete it !</p><p>Bad or missing mouse genome. Spank the cat? (Y/N)</p><p>Genome make very fast, very accurate mistakes.</p><p>Let's BLAST it.</p><p>Some genome never has transposons. It just develops random features.</p><p>Go watch CINEMA and have BLAST.</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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