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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/36476?offset=450</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/5350/introduction-of-epigenomics</guid>
	<pubDate>Sun, 06 Oct 2013 04:59:30 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/5350/introduction-of-epigenomics</link>
	<title><![CDATA[Introduction of Epigenomics]]></title>
	<description><![CDATA[<ul>
<li><a href="http://www.genome.gov/27532724#al-1">What is the epigenome?</a></li>
<li><a href="http://www.genome.gov/27532724#al-2">What does the epigenome do?</a></li>
<li><a href="http://www.genome.gov/27532724#al-3">What makes up the epigenome?</a></li>
<li><a href="http://www.genome.gov/27532724#al-4">Is the epigenome inherited?</a></li>
<li><a href="http://www.genome.gov/27532724#al-5">What is imprinting?</a></li>
<li><a href="http://www.genome.gov/27532724#al-6">Can the epigenome change?</a></li>
<li><a href="http://www.genome.gov/27532724#al-7">What makes the epigenome change?</a></li>
<li><a href="http://www.genome.gov/27532724#al-8">How do changes in the epigenome contribute to cancer?</a></li>
<li><a href="http://www.genome.gov/27532724#al-9">How are researchers exploring the epigenome?</a></li>
</ul><p>Address of the bookmark: <a href="http://www.genome.gov/27532724" rel="nofollow">http://www.genome.gov/27532724</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/6302/a-allele-of-slc24a5-gene-is-found-to-be-responsible-for-variation-in-skin-color-of-south-east-asians-and-europeans</guid>
	<pubDate>Tue, 12 Nov 2013 21:02:27 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/6302/a-allele-of-slc24a5-gene-is-found-to-be-responsible-for-variation-in-skin-color-of-south-east-asians-and-europeans</link>
	<title><![CDATA[A-allele of SLC24A5 gene is found to be responsible for variation in skin color of South-East Asians and Europeans]]></title>
	<description><![CDATA[<p><strong>Key finding</strong>:</p><ol>
<li><span>rs1426654 SNP of <em>SLC24A5</em>&nbsp;gene is decider of skin pigmentation variation in South Asia</span></li>
<li><span><span>rs1426654-A allele is widely spread throughout the Indian subcontinent&nbsp;</span></span></li>
<li><span>Skin pigmentation is also account by the combination of processes like selection and demographic history of populations affected by their language and origin</span></li>
<li><span><span>Sign of positive selection in Europeans, Middle East, Pakistan, Central Asia and North India but not in South India</span></span></li>
<li><span><span>In European , A-allele is almost reached to fixation</span></span></li>
</ol><p><span><span><strong>Paper</strong>:</span></span></p><p><span><span><a href="http://www.plosgenetics.org/article/info%3Adoi%2F10.1371%2Fjournal.pgen.1003912">http://www.plosgenetics.org/article/info%3Adoi%2F10.1371%2Fjournal.pgen.1003912</a></span></span></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/10379/your-stressdepression-came-from-ancestor</guid>
	<pubDate>Sun, 04 May 2014 18:46:20 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/10379/your-stressdepression-came-from-ancestor</link>
	<title><![CDATA[Your stress/depression came from ancestor]]></title>
	<description><![CDATA[<p>"A study published in&nbsp;<em>Nature Neuroscience</em>&nbsp;finds that stress in early life alters the production of small RNAs, called microRNAs, in the sperm of mice. The mice show depressive behaviours that persist in their progeny."</p><p>Source:</p><p>http://www.nature.com/news/sperm-rna-carries-marks-of-trauma-1.15049</p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33826/geneprof-analysis-of-high-throughput-sequencing-experiment</guid>
	<pubDate>Wed, 05 Jul 2017 16:47:05 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33826/geneprof-analysis-of-high-throughput-sequencing-experiment</link>
	<title><![CDATA[GeneProf: analysis of high-throughput sequencing experiment]]></title>
	<description><![CDATA[<div>GeneProf is a web-based, graphical software suite that allows users to analyse data produced using high-throughput sequencing platforms (RNA-seq and ChIP-seq; "Next-Generation Sequencing" or NGS): Next-gen analysis for next-gen data!</div>
<p>Some of GeneProf's highlights include:</p>
<ul>
<li><strong>Easy-to-use web-based interface:</strong>Access your data at any time from any computer with a working internet connection -- no need to install software! (cp.&nbsp;<a href="https://www.geneprof.org/GeneProf/help_introduction.jsp#section:SystemRequirements">Section 'System Requirements'</a>).</li>
<li><strong>Analysis wizards make your life easy:</strong>Step-by-step workflows make it easy to analyse high-throughput data within a minimum of hands-on time. (cp.&nbsp;<a href="https://www.geneprof.org/GeneProf/help_conceptsexplained.jsp#subconcept:AnalysisWizards">SubConcept 'Analysis Wizards'</a>).</li>
<li><strong>Versatile modules:</strong>Advanced users and data analysis experts benefit from GeneProf's broad range of analysis modules, which can be combined freely into sophisticated workflows (cp.&nbsp;<a href="https://www.geneprof.org/GeneProf/help_conceptsexplained.jsp#concept:Workflows">Concept 'Workflows'</a>).</li>
<li><strong>Integrated Analysis:</strong>Analysis of&nbsp;<em>ChIP-seq</em>&nbsp;and&nbsp;<em>RNA-seq</em>&nbsp;data in one place, plus support for the integration of other external data (e.g. from microarrays).</li>
<li><strong>Comprehensive Resource:</strong>GeneProf provides a comprehensive resource of&nbsp;<em>fully analyzed</em>&nbsp;next-generation sequencing data. Experimental results can be easily accessed and compared and the analysis procedures employed to produce the data are fully transparent (cp.&nbsp;<a href="https://www.geneprof.org/GeneProf/help_tutorials.jsp#tutorial:ExaminingPublicNext-GenDatausingGeneProf">Tutorial 'Examining Public Next-Gen Data..'</a>).</li>
<li><strong>Extensibility:</strong>Algorithm developers and computer programmers can develop their own modules and extend GeneProf. Existing software can be easily wrapped in the workflow framework (cp.&nbsp;<a href="https://www.geneprof.org/GeneProf/help_advancedtopics.jsp#section:ModuleDevelopment:AddingnewFunctionalitytoGeneProf">Section 'Module Development: Adding new..'</a>) and data from GeneProf may be used externally (cp.&nbsp;<a href="https://www.geneprof.org/GeneProf/help_advancedtopics.jsp#section:WebAPI:RetrievingDatafromGeneProf">Section 'Web API: Retrieving Data from ..'</a>).</li>
</ul>
<p>&nbsp;</p>
<p>GeneProf is academic software developed at the&nbsp;<a href="http://www.crm.ed.ac.uk/">Centre for Regenerative Medicine</a>&nbsp;/&nbsp;<a href="http://www.crm.ed.ac.uk/about/institute-stem-cell-research">Institute for Stem Cell Research</a>,&nbsp;<a href="http://www.ed.ac.uk/">University of Edinburgh</a>&nbsp;and has benefited from funding by the&nbsp;<a href="http://www.mrc.ac.uk/">Medical Research Council</a>&nbsp;and the&nbsp;<a href="http://www.eurosystemproject.eu/">EU Framework 7 Project "EuroSyStem"</a>.</p><p>Address of the bookmark: <a href="https://www.geneprof.org/GeneProf/index.jsp" rel="nofollow">https://www.geneprof.org/GeneProf/index.jsp</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<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>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37602/indexcov-fast-coverage-quality-control-for-whole-genome-sequencing</guid>
	<pubDate>Wed, 29 Aug 2018 09:20:46 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37602/indexcov-fast-coverage-quality-control-for-whole-genome-sequencing</link>
	<title><![CDATA[Indexcov: fast coverage quality control for whole-genome sequencing]]></title>
	<description><![CDATA[<p><em>indexcov</em><span>, an efficient estimator of whole-genome sequencing coverage to rapidly identify samples with aberrant coverage profiles, reveal large-scale chromosomal anomalies, recognize potential batch effects, and infer the sex of a sample.&nbsp;</span><em>Indexcov</em><span>&nbsp;is available at&nbsp;</span><a href="https://github.com/brentp/goleft" target="_blank">https://github.com/brentp/goleft</a><span>&nbsp;under the MIT license.</span></p><p>Address of the bookmark: <a href="https://github.com/brentp/goleft" rel="nofollow">https://github.com/brentp/goleft</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37835/variantbam-filtering-and-profiling-of-next-generational-sequencing-data-using-region-specific-rules</guid>
	<pubDate>Thu, 04 Oct 2018 16:30:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37835/variantbam-filtering-and-profiling-of-next-generational-sequencing-data-using-region-specific-rules</link>
	<title><![CDATA[VariantBam: Filtering and profiling of next-generational sequencing data using region-specific rules]]></title>
	<description><![CDATA[<p>VariantBam is a tool to extract/count specific sets of sequencing reads from next-generational sequencing files. To save money, disk space and I/O, one may not want to store an entire BAM on disk. In many cases, it would be more efficient to store only those read-pairs or reads who intersect some region around the variant locations. Alternatively, if your scientific question is focused on only one aspect of the data (e.g. breakpoints), many reads can be removed without losing the information relevant to the problem.</p>
<h5>&nbsp;</h5><p>Address of the bookmark: <a href="https://github.com/broadinstitute/VariantBam" rel="nofollow">https://github.com/broadinstitute/VariantBam</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38535/nanopack-visualizing-and-processing-long-read-sequencing-data</guid>
	<pubDate>Tue, 25 Dec 2018 21:20:50 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38535/nanopack-visualizing-and-processing-long-read-sequencing-data</link>
	<title><![CDATA[NanoPack: visualizing and processing long-read sequencing data]]></title>
	<description><![CDATA[The NanoPack tools are written in Python3 and released under the GNU GPL3.0 License. The source code can be found at https://github.com/wdecoster/nanopack, together with links to separate scripts and their documentation. The scripts are compatible with Linux, Mac OS and the MS Windows 10 subsystem for Linux and are available as a graphical user interface, a web service at http://nanoplot.bioinf.be and command line tools.<p>Address of the bookmark: <a href="https://github.com/wdecoster/nanopack" rel="nofollow">https://github.com/wdecoster/nanopack</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/39827/prof-dr-med-andreas-ramming</guid>
  <pubDate>Wed, 07 Aug 2019 03:25:48 -0500</pubDate>
  <link></link>
  <title><![CDATA[Prof. Dr. med. Andreas Ramming]]></title>
  <description><![CDATA[
<p>In many autoimmune diseases, a misdirected immune response leads to chronic inflammation and subsequently to fibrotic and degenerative tissue remodeling. Therapeutic options are available for inflammatory joint diseases, but only about 40% of patients respond to these existing therapies on a permanent basis. In the remaining cases, these therapies miss their target from the beginning or later during the course of treatment failure. There are currently no causal therapies available for the treatment of fibrotic autoimmune diseases such as systemic sclerosis. Therefore, there is an urgent need to develop new therapeutic options for the treatment of fibrotic and synovitic autoimmune diseases. His group is therefore deal with the molecular mechanisms of these misdirected signaling pathways for the development of novel, targeted therapies</p>

<p>http://www.medizin3.uk-erlangen.de/forschung/arbeitsgruppen/matrixbiologie-entzuendliche-signalwege-in-arthritis-und-fibrose/</p>
]]></description>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/41039/phd-position-in-translational-medicine</guid>
  <pubDate>Sat, 15 Feb 2020 06:07:19 -0600</pubDate>
  <link></link>
  <title><![CDATA[PhD position in Translational Medicine]]></title>
  <description><![CDATA[
<p>https://www.jobvector.de/jobs-stellenangebote/biologie-life-sciences/wissenschaftliche-r-mitarbeiter-in/phd-position-translational-medicine-129981.html?suid=1b510358c7578e8f75cf04a464fc21a404a574ca</p>

<p>Essential experience / qualifications:<br />Master / Diploma in Biology, Biochemistry, Molecular Medicine or similar; solid knowledge of molecular and cell biological techniques; good English knowledge</p>

<p>Applications:<br />Please send your application (including CV, letter of motivation, contact information of two references, and list of publication) by 13.03.2020 at the latest to:</p>

<p>Universitätsklinikum Erlangen<br />Chirurgische Klinik<br />Translational Research Center<br />Prof. Dr. rer. nat. Michael Stürzl<br />Schwabachanlage 12<br />91054 Erlangen<br />E-Mail: michael.stuerzl@uk-erlangen.de</p>
]]></description>
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