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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/44720?offset=10</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/17176/arvados</guid>
	<pubDate>Sat, 20 Sep 2014 16:54:21 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/17176/arvados</link>
	<title><![CDATA[Arvados]]></title>
	<description><![CDATA[<p>Arvados is a free and open&nbsp;source bioinformatics&nbsp;platform for genomic and&nbsp;biomedical data. User can&nbsp;Store | Organize | Compute | Share the data for free.&nbsp;</p>
<p><img src="https://arvados.org/images/dax.png" width="400" height="535" alt="image" style="border: 0px;"></p><p>Address of the bookmark: <a href="https://arvados.org/" rel="nofollow">https://arvados.org/</a></p>]]></description>
	<dc:creator>Martin Jones</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28121/kaiju</guid>
	<pubDate>Mon, 27 Jun 2016 11:23:04 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28121/kaiju</link>
	<title><![CDATA[Kaiju]]></title>
	<description><![CDATA[<p>Kaiju is a program for the taxonomic classification of metagenomic high-throughput sequencing reads. Each read is directly assigned to a taxon within the NCBI taxonomy by comparing it to a reference database containing microbial and viral protein sequences.</p>
<p>By default, Kaiju uses either the available complete genomes from NCBI RefSeq or the microbial subset of the non-redundant protein database <em>nr</em> used by NCBI BLAST, optionally also including fungi and microbial eukaryotes.</p>
<p>Kaiju translates reads into amino acid sequences, which are then searched in the database using a modified backward search on a memory-efficient implementation of the Burrows-Wheeler transform, which finds maximum exact matches (MEMs), optionally allowing mismatches in the protein alignment. The search can process up to millions of reads per minute using, for example, only 10 GB RAM with a protein database comprising 4821 microbial genomes. Kaiju can also be used for querying any other protein database without taxonomic classification, using either protein or nucleotide queries.</p>
<p>Kaiju is described in <a href="http://www.nature.com/ncomms/2016/160413/ncomms11257/full/ncomms11257.html">Menzel, P. et al. (2016) Fast and sensitive taxonomic classification for metagenomics with Kaiju. <em>Nat. Commun.</em> 7:11257</a> (open access).</p><p>Address of the bookmark: <a href="http://kaiju.binf.ku.dk/" rel="nofollow">http://kaiju.binf.ku.dk/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/41905/research-associate-bioinformatics-in-iisc-recruitment-2020</guid>
  <pubDate>Tue, 23 Jun 2020 21:53:34 -0500</pubDate>
  <link></link>
  <title><![CDATA[Research Associate Bioinformatics in IISc Recruitment 2020]]></title>
  <description><![CDATA[
<p>Research Associate Bioinformatics in IISc Recruitment 2020</p>

<p>Essential Qualifications: Ph.D. (Bioinformatics/ Biophysics/ Biotechnology or any other stream of biological/ physical sciences) with a minimum of two publications in reputed peer reviewed journals in the area of structural bioinformatics or biophysics or biomolecular modeling/ simulation.</p>

<p>Job description: Development of bioinformatics tools and algorithms/software for structure based analysis of biomolecular systems. Programmatic access to major biomolecular databases using APIs Knowledge based prediction and analysis of biomolecular structure, function and interactions. Docking/simulations for inhibitor design.</p>

<p>Desirable Qualifications (Research Associate/s): i)  Strong computer programming skills (in Python/PERL/PHP or C++ or object oriented database management systems like MySQL etc or scripting languages under LINUX/UNIX environment). </p>

<p>ii) Extensive experience in computational analysis of biomolecular structure/interactions and usage of advanced biomolecular simulation softwares. iii) Adequate knowledge of major databases, webservers and softwares in the area of biomolecular structure/function and drug design. iv)  Familiarity with Parallel Programming environments and experience in usage of high-end HPC clusters.</p>

<p>The candidates must highlight their experience in above mentioned fields/topics in their CV. Initial appointment will be for a period of 1 year, subject to extension after review of performance.</p>

<p>Emoluments: As per DST, GOI norms and commensurate with experience.</p>

<p>More at https://www.iisc.ac.in/positions-open/</p>
]]></description>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/27321/slurm-basics</guid>
	<pubDate>Fri, 13 May 2016 04:42:24 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/27321/slurm-basics</link>
	<title><![CDATA[SLURM basics !]]></title>
	<description><![CDATA[<p><a href="http://bioinformaticsonline.com/bookmarks/view/27238/slurm" target="_blank">SLURM</a> is a queue management system and stands for Simple Linux Utility for Resource Management. SLURM was developed at the Lawrence Livermore National Lab and currently runs some of the largest compute clusters in the world.</p><p>SLURM is similar in many ways to most other queue systems. You write a batch script then submit it to the queue manager. The queue manager then schedules your job to run on the queue (or partition in SLURM parlance) that you designate. Below we will provide an outline of how to submit jobs to SLURM, how SLURM decides when to schedule your job and how to monitor progress.</p><p>SLURM has a number of valuable features compared to other job management systems:</p><ul>
<li><em>Kill and Requeue</em> SLURM&rsquo;s ability to kill and requeue is superior to that of other systems. It waits for jobs to be cleared before scheduling the high priority job. It also does kill and requeue on memory rather than just on core count.</li>
<li><em>Memory</em> Memory requests are sacrosanct in SLURM. Thus the amount of memory you request at run time is guaranteed to be there. No one can infringe on that memory space and you cannot exceed the amount of memory that you request.</li>
<li><em>Accounting Tools</em> SLURM has a back end database which stores historical information about the cluster. This information can be queried by the users who are curious about how much resources they have used.</li>
</ul><p><strong>Summary of SLURM commands</strong></p><p>The table below shows a summary of SLURM commands. These commands are described in more detail below along with links to the SLURM doc site.</p><table>
<tbody>
<tr><th>&nbsp;</th><th>SLURM</th><th>SLURM Example</th></tr>
<tr>
<td>Submit a batch serial job</td>
<td><a href="http://slurm.schedmd.com/sbatch.html">sbatch</a></td>
<td><code>sbatch runscript.sh</code></td>
</tr>
<tr>
<td>Run a script interatively</td>
<td><a href="http://slurm.schedmd.com/srun.html">srun</a></td>
<td><code>srun --pty -p interact -t 10 --mem 1000 /bin/bash /bin/hostname</code></td>
</tr>
<tr>
<td>Kill a job</td>
<td><a href="http://slurm.schedmd.com/scancel.html">scancel</a></td>
<td><code>scancel 999999</code></td>
</tr>
<tr>
<td>View status of queues</td>
<td><a href="http://slurm.schedmd.com/squeue.html">squeue</a></td>
<td><code>squeue -u akitzmiller</code></td>
</tr>
<tr>
<td>Check current job by id</td>
<td><a href="http://slurm.schedmd.com/squeue.html">sacct</a></td>
<td><code>sacct -j 999999</code></td>
</tr>
</tbody>
</table>]]></description>
	<dc:creator>Radha Agarkar</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29384/phymmbl</guid>
	<pubDate>Mon, 10 Oct 2016 08:56:34 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29384/phymmbl</link>
	<title><![CDATA[PHYMMBL]]></title>
	<description><![CDATA[<p><span>Metagenomics sequencing projects collect samples of DNA from uncharacterized environments that may contain hundreds or even thousands of species. One of the main challenges in analyzing a metagenome is phylogenetic classification of raw sequence reads into groups representing the same or similar species. Such classification is a useful prerequisite for genome assembly and for analysis of the biological diversity present in a sample. The newest sequencing technologies have simultaneously made metagenomics easier, by making the sequencing process faster, and more difficult, by producing shorter read lengths than previous technologies. Methods for classifying sequences as short as 100 base pairs (bp) have until now been relatively inaccurate, requiring metagenomics projects to use older, long-read technologies.&nbsp;</span><strong>Phymm</strong><span>, a new classification approach for metagenomics data which uses interpolated Markov models (IMMs) to taxonomically classify DNA sequences, can accurately classify reads as short as 100 bp. Its accuracy for short reads represents a significant leap forward over previous composition-based classification methods.&nbsp;</span><strong>PhymmBL</strong><span>&nbsp;(rhymes with "thimble"), the hybrid classifier included in this distribution which combines analysis from both Phymm and&nbsp;</span><a href="http://www.ncbi.nlm.nih.gov/BLAST">BLAST</a><span>, produces even higher accuracy.</span></p><p>Address of the bookmark: <a href="http://www.cbcb.umd.edu/software/phymm/" rel="nofollow">http://www.cbcb.umd.edu/software/phymm/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29578/plink2</guid>
	<pubDate>Thu, 27 Oct 2016 11:24:45 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29578/plink2</link>
	<title><![CDATA[PLINK2]]></title>
	<description><![CDATA[<p><span>This is a comprehensive update to Shaun Purcell's&nbsp;</span><a href="http://pngu.mgh.harvard.edu/~purcell/plink/">PLINK</a><span>&nbsp;command-line program, developed by&nbsp;</span><a href="mailto:chrchang@alumni.caltech.edu">Christopher Chang</a><span>&nbsp;with support from the&nbsp;</span><a href="http://www.niddk.nih.gov/">NIH-NIDDK</a><span>'s Laboratory of Biological Modeling, the&nbsp;</span><a href="http://research.mssm.edu/statgen/">Purcell Lab</a><span>&nbsp;at Mount Sinai School of Medicine, and others. (</span><a href="https://www.cog-genomics.org/plink2/#new">What's new?</a><span>) (</span><a href="https://www.cog-genomics.org/plink2/credits">Credits.</a><span>) (</span><a href="http://www.gigasciencejournal.com/content/4/1/7">Methods paper.</a><span>)</span></p><p>Address of the bookmark: <a href="https://www.cog-genomics.org/plink2/" rel="nofollow">https://www.cog-genomics.org/plink2/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/29601/statistics-using-r-with-biological-examples</guid>
	<pubDate>Thu, 03 Nov 2016 04:55:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/file/view/29601/statistics-using-r-with-biological-examples</link>
	<title><![CDATA[Statistics Using R   with Biological Examples]]></title>
	<description><![CDATA[<p>This book is a manifestation of my desire to teach researchers in biology a bit more about statistics than an ordinary introductory course covers and to introduce the utilization of R as a tool for analyzing their data. My goal is to reach those with little or no training in higher level statistics so that they can do more of their own data analysis, communicate more with statisticians, and appreciate the great potential statistics has to offer as a tool to answer biological questions. </p><p>This is necessary in light of the increasing use of higher level statistics in biomedical research. I hope it accomplishes this mission and encourage its free distribution and use as a course text or supplement.</p><p>K Seefeld, May 2007</p>]]></description>
	<dc:creator>Neel</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/29601" length="4581031" type="application/pdf" />
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/29624/information-officer-at-iiar-gujarat</guid>
  <pubDate>Fri, 04 Nov 2016 05:19:13 -0500</pubDate>
  <link></link>
  <title><![CDATA[Information Officer at IIAR, Gujarat]]></title>
  <description><![CDATA[
<p>Walk in interview at 10.30 am on Nov 11th, 2016 for the following position at Distributed Information Sub-Centre (DISC) established by Dept. Of Biotechnology, Govt. of India at Indian Institute of Advanced Research, Gandhinagar, Gujarat</p>

<p>Position (scale), qualifications and experience</p>

<p>1. Information Officer (Rs 8000-275-13500): one post <br />Qualifications and experience: MCA, Post-Graduate in any field of biosciences, bioinformatics with at least two years of experience in working in a bioinformatics setup and good knowledge of linux operating system and computer networking.</p>

<p>General terms and conditions: <br />1. The above engagements is presently till March 31st, 2017. However on extension of project grant and satisfactory performance of the candidate, your services can be extended beyond March 31st, 2017 based on the terms and conditions of extension of project grant.</p>

<p>2. It is not an appointment with the institute and will not confer any right to the incumbent to any claim implicit or explicit on any position.</p>

<p>3.No TA/DA will be paid for attending the interview. Outstation candidates have to make their own arrangement for their stay.</p>

<p>4.Candidates, appearing in the walk-in interview are requested to bring the hard copy of application addressed to Dr. Anju Pappachan with latest photograph, CV mentioning qualifications, work experience and name of two referees and one page write up as to why you would like to join the project.</p>

<p>Address: <br />Dr. Anju Pappachan <br />Indian Institute of Advanced Research (IIAR), <br />University  and Institute of Advanced Research, <br />The Puri Foundation for Education in India, <br />Koba Institutional Area, <br />Gandhinagar- 382 007, Gujarat, India. Contact no. 079-30514152 <br />e-mail- anju@iiar.res.in</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29957/record</guid>
	<pubDate>Fri, 25 Nov 2016 08:23:36 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29957/record</link>
	<title><![CDATA[RECORD]]></title>
	<description><![CDATA[<p>Background. Next-generation sequencing technologies are now producing multiple times the genome size in total reads from a single experiment. This is enough information to reconstruct at least some of the differences between the individual genome studied in the experiment and the reference genome of the species. However, in most typical protocols, this information is disregarded and the reference genome is used. Results. We provide a new approach that allows researchers to reconstruct genomes very closely related to the reference genome (e.g., mutants of the same species) directly from the reads used in the experiment. Our approach applies de novo assembly software to experimental reads and so-called pseudoreads and uses the resulting contigs to generate a modified reference sequence. In this way, it can very quickly, and at no additional sequencing cost, generate new, modified reference sequence that is closer to the actual sequenced genome and has a full coverage. In this paper, we describe our approach and test its implementation called RECORD. We evaluate RECORD on both simulated and real data. We made our software publicly available on sourceforge. Conclusion. Our tests show that on closely related sequences RECORD outperforms more general assisted-assembly software.</p>
<p>More at&nbsp;https://sourceforge.net/projects/record-genome-assembler/files/</p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/pubmed/26558255" rel="nofollow">https://www.ncbi.nlm.nih.gov/pubmed/26558255</a></p>]]></description>
	<dc:creator>Bulbul</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29656/statistics-and-probability</guid>
	<pubDate>Tue, 08 Nov 2016 07:34:25 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29656/statistics-and-probability</link>
	<title><![CDATA[Statistics and probability]]></title>
	<description><![CDATA[<h3><span>Topics</span></h3>
<div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/displaying-describing-data">Displaying and describing data</a></div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/modeling-distributions-of-data">Modeling distributions of data</a></div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/describing-relationships-quantitative-data">Describing relationships in quantitative data</a></div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/designing-studies">Designing studies</a></div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/probability-library">Probability</a></div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/random-variables-stats-library">Random variables</a></div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/sampling-distributions-library">Sampling distributions</a></div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/confidence-intervals-one-sample">Confidence intervals (one sample)</a></div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/significance-tests-one-sample">Significance tests (one sample)</a></div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/significance-tests-confidence-intervals-two-samples">Significance tests and confidence intervals (two samples)</a></div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/inference-categorical-data-chi-square-tests">Inference for categorical data (chi-square tests)</a></div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/advanced-regression-inference-transforming">Advanced regression (inference and tran</a></div>
</div><p>Address of the bookmark: <a href="https://www.khanacademy.org/math/statistics-probability" rel="nofollow">https://www.khanacademy.org/math/statistics-probability</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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