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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/29576?offset=320</link>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/29263/srf-bioinformatics-at-bose-institute-india</guid>
  <pubDate>Thu, 29 Sep 2016 09:39:13 -0500</pubDate>
  <link></link>
  <title><![CDATA[SRF Bioinformatics at Bose Institute, India]]></title>
  <description><![CDATA[
<p>Advt. No. S/DPB(CB)/17/2016-17 <br />Junior Research Assistant/ Senior Research Assistant  Job vacancies in Bose Institute on temporary basis<br />Project Title : “Genome wide transcriptome analysis to identity MYMIV-stress related genomic resources of blackgram”<br />Junior Research Assistant <br />Qualification : Good academic record in B.Sc. and M.Sc. in Botany or Biotechnology from reputed Universities. Must have good practical hand, this should be certified by two Senior/reputed PG teachers on a scale of 10. <br />Desirable : Preference will be given to those who already have some research experience (for at least 2 months). <br />Consolidated Pay : Rs. 16,400/- p.m. <br />Age Limit : Below 28 years (relaxable in case of SC/ST/OBC/Women candidates only as per rules).<br />Senior Research Assistant <br />Qualification : B.Sc. in Biotechnology and M.Sc. in Biotechnology or Bioinformatics. Hands on training in Bioinformatics. At least two Research Publications with Bioinformatics components. <br />Desirable : Preference will be given to the candidates who have previous experience in Next Gen Sequencing data analysis of genomic/transcriptome/miRNA. <br />Consolidated Pay : Rs. 18,700/- p.m.  <br />Age Limit : Below 30 years (relaxable in case of SC/ST/OBC/Women candidates only as per rules).</p>

<p>http://www.boseinst.ernet.in/advertisement.html</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29276/murasaki</guid>
	<pubDate>Fri, 30 Sep 2016 10:22:30 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29276/murasaki</link>
	<title><![CDATA[Murasaki]]></title>
	<description><![CDATA[<p>Murasaki is an anchor alignment program that is</p>
<ul style="margin-left: 16px;">
<li>exteremely fast (17 CPU hours for whole Human x Mouse genome (with 40 nodes: 35 wall minutes), or 8 mammals in 21 CPU hours (42 wall minutes))</li>
<li>scalable (Arbitrarily parallelizable across multiple nodes using MPI)</li>
<li>memory efficient. (Even a single node with 16GB of ram can handle over 1Gbp of sequence)</li>
<li>unlimited by pattern length or selection</li>
<li>repeat tolerant</li>
</ul>
<p><img src="http://murasaki.dna.bio.keio.ac.jp/9mammals-small.png" width="500" height="375" alt="image" style="border: 0px;"></p><p>Address of the bookmark: <a href="http://murasaki.dna.bio.keio.ac.jp/wiki/index.php?Murasaki" rel="nofollow">http://murasaki.dna.bio.keio.ac.jp/wiki/index.php?Murasaki</a></p>]]></description>
	<dc:creator>Anjana</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29305/miro-mirna-omics</guid>
	<pubDate>Tue, 04 Oct 2016 14:50:48 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29305/miro-mirna-omics</link>
	<title><![CDATA[MIRO : miRNA omics]]></title>
	<description><![CDATA[<p><span>The MIRO (the miRNA omics) pipeline is a flexible and powerful tool for the analysis of miRNA (or more generall short RNA) expression using short-read deep sequencing data. In its present implementation MIRO is especially adapted for the analysis of reads generated with the Illumina sequencing platform. MIRO allows to preprocess the Solexa-reads, map them flexibly to several reference genomes using one of four different mappers, create differential gene (miRNA) expression profiles and cluster reads using one of several algorithm. MIRO output is furthermore compatible with software such as genome browsers and miRDeep.</span></p><p>Address of the bookmark: <a href="http://seq.crg.es/download/software/Miro/" rel="nofollow">http://seq.crg.es/download/software/Miro/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29410/entrez-direct-e-utilities-on-the-unix-command-line</guid>
	<pubDate>Wed, 19 Oct 2016 08:06:24 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29410/entrez-direct-e-utilities-on-the-unix-command-line</link>
	<title><![CDATA[Entrez Direct: E-utilities on the UNIX Command Line]]></title>
	<description><![CDATA[<p>Entrez Direct (EDirect) is an advanced method for accessing the NCBI's suite of interconnected databases (publication, sequence, structure, gene, variation, expression, etc.) from a UNIX terminal window. Functions take search terms from command-line arguments. Individual operations are combined to build multi-step queries. Record retrieval and formatting normally complete the process.</p>
<p>EDirect also provides an argument-driven function that simplifies the extraction of data from document summaries or other results that are returned in structured XML format. This can eliminate the need for writing custom software to answer ad hoc questions. Queries can move seamlessly between EDirect commands and UNIX utilities or scripts to perform actions that cannot be accomplished entirely within Entrez.</p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/books/NBK179288/" rel="nofollow">https://www.ncbi.nlm.nih.gov/books/NBK179288/</a></p>]]></description>
	<dc:creator>Anjana</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29500/genomescope-open-source-web-tool-to-rapidly-estimate-the-overall-characteristics-of-a-genome-including-genome-size-heterozygosity-rate-and-repeat-content-from-unprocessed-short-reads</guid>
	<pubDate>Fri, 21 Oct 2016 05:46:43 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29500/genomescope-open-source-web-tool-to-rapidly-estimate-the-overall-characteristics-of-a-genome-including-genome-size-heterozygosity-rate-and-repeat-content-from-unprocessed-short-reads</link>
	<title><![CDATA[GenomeScope: open-source web tool to rapidly estimate the overall characteristics of a genome, including genome size, heterozygosity rate, and repeat content from unprocessed short reads]]></title>
	<description><![CDATA[<div>
<div>
<div>
<div id="content-block-markup">
<div>
<div id="abstract-1">
<p id="p-2">Summary: GenomeScope is an open-source web tool to rapidly estimate the overall characteristics of a genome, including genome size, heterozygosity rate, and repeat content from unprocessed short reads. These features are essential for studying genome evolution, and help to choose parameters for downstream analysis. We demonstrate its accuracy on 324 simulated and 16 real datasets with a wide range in genome sizes, heterozygosity levels, and error rates. Availability and Implementation: http://qb.cshl.edu/genomescope/, https://github.com/schatzlab/genomescope.git</p>
</div>
<span></span></div>
<span></span></div>
</div>
</div>
</div><p>Address of the bookmark: <a href="http://qb.cshl.edu/genomescope/" rel="nofollow">http://qb.cshl.edu/genomescope/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29586/eforgev12</guid>
	<pubDate>Fri, 28 Oct 2016 09:06:59 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29586/eforgev12</link>
	<title><![CDATA[eFORGE.v1.2]]></title>
	<description><![CDATA[<p><span>The eFORGE tool provides a method to view the tissue specific regulatory component of a set of EWAS DMPs. eFORGE analysis takes a set of DMPs, such as those hits above genome-wide significance threshold in an EWAS study, and analyses whether there is enrichment for overlap of putative functional elements compared to matched background DMPs. It assesses enrichment on a per cell type basis, since functional elements are differentially active in different cell types, and hence can expose tissue-specific signals of enrichment for the given test DMP set. This can reveal the sites of action underlying the EWAS signal, and provide confirmation of the validity of the EWAS where a tissue-specific mechanism is known or expected for the phenotype. Conversely unknown tissue involvements can also be revealed.</span></p><p>Address of the bookmark: <a href="http://eforge.cs.ucl.ac.uk/eFORGE.v1.2/?documentation" rel="nofollow">http://eforge.cs.ucl.ac.uk/eFORGE.v1.2/?documentation</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29614/art-set-of-simulation-tools</guid>
	<pubDate>Thu, 03 Nov 2016 08:28:25 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29614/art-set-of-simulation-tools</link>
	<title><![CDATA[ART: Set of Simulation Tools]]></title>
	<description><![CDATA[<p>ART is a set of simulation tools to generate synthetic next-generation sequencing reads. ART simulates sequencing reads by mimicking real sequencing process with empirical error models or quality profiles summarized from large recalibrated sequencing data. ART can also simulate reads using user own read error model or quality profiles. ART supports simulation of single-end, paired-end/mate-pair reads of three major commercial next-generation sequencing platforms: Illumina's Solexa, Roche's 454 and Applied Biosystems' SOLiD. ART can be used to test or benchmark a variety of method or tools for next-generation sequencing data analysis, including read alignment, de novo assembly, SNP and structure variation discovery. ART was used as a primary tool for the simulation study of the <span><a href="http://www.1000genomes.org/" target="_blank">1000 Genomes Project<span></span></a></span> . ART is implemented in C++ with optimized algorithms and is highly efficient in read simulation. ART outputs reads in the FASTQ format, and alignments in the ALN format. ART can also generate alignments in the SAM alignment or UCSC BED file format. ART can be used together with genome variants simulators (e.g. <span><a href="http://bioinform.github.io/varsim/" target="_blank">VarSim<span></span></a></span>) for evaluating variant calling tools or methods.</p><p>Address of the bookmark: <a href="http://www.niehs.nih.gov/research/resources/software/biostatistics/art/" rel="nofollow">http://www.niehs.nih.gov/research/resources/software/biostatistics/art/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29635/r-graphs</guid>
	<pubDate>Fri, 04 Nov 2016 10:48:00 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29635/r-graphs</link>
	<title><![CDATA[R Graphs !!]]></title>
	<description><![CDATA[<p><span>The blog is a collection of script examples with example data and output plots. R produce excellent quality graphs for data analysis, science and business presentation, publications and other purposes. Self-help codes and examples are provided. Enjoy nice graphs !!</span></p><p>Address of the bookmark: <a href="http://rgraphgallery.blogspot.be/" rel="nofollow">http://rgraphgallery.blogspot.be/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/29652/bioistats-ppt</guid>
	<pubDate>Tue, 08 Nov 2016 07:09:01 -0600</pubDate>
	<link>https://bioinformaticsonline.com/file/view/29652/bioistats-ppt</link>
	<title><![CDATA[Bioistats PPT]]></title>
	<description><![CDATA[<p>Basics concepts of&nbsp;Probability: The Study of Randomness</p><p>Biostatistics is the application of statistics to a wide range of topics in biology. The science of biostatistics encompasses the design of biological experiments, especially in medicine, pharmacy, agriculture and fishery; the collection, summarization, and analysis of data from those experiments; and the interpretation of, and inference from, the results. A major branch of this is medical biostatistics, which is exclusively concerned with medicine and health.</p>]]></description>
	<dc:creator>Jit</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/29652" length="1663809" type="application/pdf" />
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29679/comparative-genomics-educational-material-and-papers-bookmarks</guid>
	<pubDate>Wed, 09 Nov 2016 16:23:30 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29679/comparative-genomics-educational-material-and-papers-bookmarks</link>
	<title><![CDATA[Comparative genomics educational material and papers bookmarks]]></title>
	<description><![CDATA[<p><span>Alignment of the porcine genome against seven other mammalian genomes (</span><a href="http://www.nature.com/nature/journal/v491/n7424/full/nature11622.html#supplementary-information">Supplementary Information</a><span>) identified homologous synteny blocks (HSBs). Using porcine HSBs and stringent filtering criteria, 192 pig-specific evolutionary breakpoint regions (EBRs) were located. The number of porcine EBRs </span><span>is comparable to the number of bovine-lineage-specific EBRs (100) reported earlier using a slightly lower resolution (500</span><span><span>&thinsp;</span></span><span>kilobases (kb)), indicating that both lineages evolved with an average rate of ~2.1 large-scale rearrangements per million years after the divergence from a common cetartiodactyl ancestor ~60</span><span><span>&thinsp;</span></span><span>Myr ago</span><sup><a href="http://www.nature.com/nature/journal/v491/n7424/full/nature11622.html#ref2" title="Meredith, R. W. et al. Impacts of the Cretaceous Terrestrial Revolution and KPg extinction on mammal diversification. Science 334, 521-524 (2011)">2</a></sup><span>. This rate compares to ~1.9 rearrangements per million years within the primate lineage (</span><a href="http://www.nature.com/nature/journal/v491/n7424/full/nature11622.html#supplementary-information">Supplementary Table 11</a><span>). A total of 20 and 18 cetartiodactyl EBRs (shared by pigs and cattle) were detected using the pig and human genomes as a reference, respectively.</span></p><p>Address of the bookmark: <a href="http://www.nature.com/nature/journal/v491/n7424/abs/nature11622.html" rel="nofollow">http://www.nature.com/nature/journal/v491/n7424/abs/nature11622.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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