<?xml version='1.0'?><rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:georss="http://www.georss.org/georss" xmlns:atom="http://www.w3.org/2005/Atom" >
<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/27818?offset=790</link>
	<atom:link href="https://bioinformaticsonline.com/related/27818?offset=790" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41046/iseqqc-a-tool-for-expression-based-quality-control-in-rna-sequencing</guid>
	<pubDate>Sun, 16 Feb 2020 08:47:17 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41046/iseqqc-a-tool-for-expression-based-quality-control-in-rna-sequencing</link>
	<title><![CDATA[iSeqQC: a tool for expression-based quality control in RNA sequencing]]></title>
	<description><![CDATA[<p><span>iSeqQC, an expression-based QC tool that detects outliers either produced due to variable laboratory conditions or due to dissimilarity within a phenotypic group. iSeqQC implements various statistical approaches including unsupervised clustering, agglomerative hierarchical clustering and correlation coefficients to provide insight into outliers.</span></p>
<p><a href="http://cancerwebpa.jefferson.edu/iSeqQC/">http://cancerwebpa.jefferson.edu/iSeqQC/</a></p>
<p><a href="https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-020-3399-8">https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-020-3399-8</a></p><p>Address of the bookmark: <a href="https://github.com/gkumar09/iSeqQC" rel="nofollow">https://github.com/gkumar09/iSeqQC</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/17188/jamia-hamdard-bioinformatics-faculty-jobs-2014</guid>
  <pubDate>Sat, 20 Sep 2014 21:00:05 -0500</pubDate>
  <link></link>
  <title><![CDATA[JAMIA HAMDARD Bioinformatics Faculty Jobs 2014]]></title>
  <description><![CDATA[
<p>JAMIA HAMDARD</p>

<p>(Deemed University)</p>

<p>Hamdard Nagar, New Delhi – 110 062</p>

<p>R E C R U I T M E N T</p>

<p>(Advertisement No. 5/2014)</p>

<p>Applications on prescribed form are invited for filling up the following teaching positions in the Department of Biotechnology, Faculty of Science in the university. Eligible candidates may apply on or before 30.09.2014.</p>

<p>1. Professor/Associate Professor - One in Pay Band of Rs. 37400-67000+ AGP Rs.10000/9000</p>

<p>2. Assistant Professor                   -  Two in Pay Band of Rs. 15600-39100+ AGP Rs. 6000/-</p>

<p>ASSISTANT PROFESSOR – 02 (including 01 SFS)</p>

<p>Specialization : Bioinformatics</p>

<p>Qualification and Experience :</p>

<p>Ph.D. in Biotechnology or an allied discipline with M.Sc. in Biotechnology/ Biochemistry in the First division or equivalent grade from a recognized University/ Institute.</p>

<p>NET in Life Science or allied discipline in addition to the above qualification.</p>

<p>Experience : At  least two years of Post-doctoral teaching and/or research experience in Bioinformatics or relevant field in a UGC recognized Institution of repute or international research institute/ University.  Proof of research to be evidenced by publications in SCI-indexed journals of high impact factor as the first or corresponding author.</p>

<p>Note : University may consider exempting candidates from NET, who has been awarded Ph.D. degree from ‘A’ Grade accredited University following the procedure as notified by the UGC in its Regulations of 2009 and adopted by Jamia Hamdard.</p>

<p>For more information: http://www.jamiahamdard.ac.in/PDF/Online%20application%20form%20_Teaching_1.pdf<br />http://www.jamiahamdard.ac.in/PDF/PBAS.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41571/wego-simple-but-useful-tool-for-visualizing-comparing-and-plotting-go-gene-ontology-annotation-results</guid>
	<pubDate>Sun, 12 Apr 2020 10:02:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41571/wego-simple-but-useful-tool-for-visualizing-comparing-and-plotting-go-gene-ontology-annotation-results</link>
	<title><![CDATA[WEGO : simple but useful tool for visualizing, comparing and plotting GO (Gene Ontology) annotation results]]></title>
	<description><![CDATA[<p><span>WEGO (Web Gene Ontology Annotation Plot) is a simple but useful tool for visualizing, comparing and plotting GO (Gene Ontology) annotation results. As the GO vocabulary became more and more popular, WEGO was widely adopted and used in many researches. Therefore we have updated WEGO 2.0 in 2018. Here are some changes we&rsquo;ve made:</span><br><span>1. The limit of input file numbers was cancelled. Now the users could upload as many files as they want with one operation.</span><br><span>2. We have added the reference data of 9 species for users selection.</span><br><span>3. Besides the traditional WEGO histogram, WEGO 2.0 outputs an additional type of bar graph showing GO terms with significant gene number differences.</span></p><p>Address of the bookmark: <a href="http://wego.genomics.org.cn/" rel="nofollow">http://wego.genomics.org.cn/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/17500/joao-pedro-de-magalhaes-lab</guid>
  <pubDate>Fri, 26 Sep 2014 19:08:34 -0500</pubDate>
  <link></link>
  <title><![CDATA[Joao Pedro de Magalhaes Lab]]></title>
  <description><![CDATA[
<p>Ageing has a profound impact on human society and modern medicine, yet it remains a major puzzle of biology. The goal of my work is to help understand the genetic, cellular, and molecular mechanisms of ageing. In the long term, I would like my work to help ameliorate age-related diseases and preserve health. No other biomedical field has so much potential to improve human health as research on the basic mechanisms of ageing. Please see our lab website for further details about our work and publications. </p>

<p>Functional and Comparative Genomics</p>

<p>http://jp.senescence.info/<br />http://www.senescence.info/<br />http://www.liv.ac.uk/integrative-biology/staff/joao-de-magalhaes/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42139/mixtures-a-novel-tool-for-bacterial-strain-reconstruction-from-reads</guid>
	<pubDate>Fri, 21 Aug 2020 08:23:19 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42139/mixtures-a-novel-tool-for-bacterial-strain-reconstruction-from-reads</link>
	<title><![CDATA[mixtureS: a novel tool for bacterial strain reconstruction from reads]]></title>
	<description><![CDATA[<div>
<p>mixtureS that can de novo identify bacterial strains from shotgun reads of a clonal or metagenomic sample, without prior knowledge about the strains and their variations. Tested on 243 simulated datasets and 195 experimental datasets, mixtureS reliably identified the strains, their numbers and their abundance. Compared with three tools, mixtureS showed better performance in almost all simulated datasets and the vast majority of experimental datasets.</p>
</div>
<div>
<div>Availability</div>
<p>The source code and tool mixtureS is available at&nbsp;<a href="http://www.cs.ucf.edu/~xiaoman/mixtureS/" target="_blank">http://www.cs.ucf.edu/&tilde;xiaoman/mixtureS/</a>.</p>
</div><p>Address of the bookmark: <a href="http://www.cs.ucf.edu/~xiaoman/mixtureS/" rel="nofollow">http://www.cs.ucf.edu/~xiaoman/mixtureS/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/23628/postgraduate-research-associate-bioinformatics-computational-biology-reference-code-59</guid>
  <pubDate>Tue, 04 Aug 2015 20:32:39 -0500</pubDate>
  <link></link>
  <title><![CDATA[Postgraduate Research Associate Bioinformatics / Computational Biology (Reference code: 59)]]></title>
  <description><![CDATA[
<p>The Department of Biotechnology, group “Genome Bioinformatics” is currently seeking a Postgraduate Research Associate Bioinformatics / Computational Biology (Reference code: 59)</p>

<p>Extent of employment: 30 Hours per Week<br />Duration of employment: 1st of October 2015 to 30th of September 2019<br />Gross monthly salary and pay grade in terms of collective agreement for university staff (payable 14 times per year): B1, € 1.997,20</p>

<p>Responsibilities<br />The successful candidate (f/m) will pursue a Ph.D. project related to the interpretation of plant genome and transcriptome sequencing data from next-generation sequencing (NGS) platforms. In particular, the candidate will characterize the unexplored genome of quinoa, a crop plant of long-standing tradition in Latin America. We collaborate with research partners in Austria and abroad, and the candidate’s project will be of central importance in the context of this research network.</p>

<p>Required skills and qualifications<br />We are looking for a graduate student (f/m) with a Master’s degree in bioinformatics or in a related field, solid programming skills (e.g. developing sequence analysis tools), experience with the analysis of NGS data sets, understanding of lab methods and knowledge of genomics/transcriptomics. The group has successfully performed several projects using NGS technology. We have recently published the reference genome sequence of sugar beet (Dohm et al., Nature, 2014), a crop plant closely related to quinoa (same family, but different genus). Not yet published is a quinoa genome assembly that we have generated, and which will serve as the starting point of the candidate’s project. We are a multidisciplinary team and offer work in a lively and friendly atmosphere, and state-of-the-art computing infrastructure. We are looking forward to expanding our team by a dedicated and strongly motivated person with a distinct interest in the challenges of plant genomics.</p>

<p>Applications can be submitted until: 16th of August 2015</p>

<p>University of Natural Resources and Life Sciences Vienna seeks to increase the number of its female faculty and staff members. Therefore qualified women are strongly encouraged to apply. In case of equal qualification, female candidates will be given preference unless reasons specific to an individual male candidate tilt the balance in his favour.</p>

<p>Please send your job application (incl. letter of motivation, CV, summary of Master’s thesis and contact details for two referees) to Personnel department, University of Natural Resources and Life Sciences, 1190 Vienna, Peter-Jordan-Straße 70; E-Mail: kerstin.buchmueller@boku.ac.at. (Reference code: 59)</p>

<p>We regret that we cannot reimburse applicants travel and lodging expenses incurred as part of the selection and hiring process.</p>

<p>www.boku.ac.at</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42362/magic-a-tool-for-predicting-transcription-factors-and-cofactors-driving-gene-sets-using-encode-data</guid>
	<pubDate>Thu, 26 Nov 2020 11:05:04 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42362/magic-a-tool-for-predicting-transcription-factors-and-cofactors-driving-gene-sets-using-encode-data</link>
	<title><![CDATA[MAGIC: A tool for predicting transcription factors and cofactors driving gene sets using ENCODE data]]></title>
	<description><![CDATA[<p><span>The algorithm presented herein,&nbsp;</span><strong>M</strong><span>ining&nbsp;</span><strong>A</strong><span>lgorithm for&nbsp;</span><strong>G</strong><span>enet</span><strong>I</strong><span>c&nbsp;</span><strong>C</strong><span>ontrollers (MAGIC), uses ENCODE ChIP-seq data to look for statistical enrichment of TFs and cofactors in gene bodies and flanking regions in gene lists without an&nbsp;</span><em>a priori</em><span>&nbsp;binary classification of genes as targets or non-targets. When compared to other TF mining resources, MAGIC displayed favourable performance in predicting TFs and cofactors that drive gene changes in 4 settings: </span></p>
<p><span>1) A cell line expressing or lacking single TF, </span></p>
<p><span>2) Breast tumors divided along PAM50 designations </span></p>
<p><span>3) Whole brain samples from WT mice or mice lacking a single TF in a particular neuronal subtype </span></p>
<p><span>4) Single cell RNAseq analysis of neurons divided by Immediate Early Gene expression levels. </span></p>
<p><span>In summary, MAGIC is a standalone application that produces meaningful predictions of TFs and cofactors in transcriptomic experiments.</span></p>
<p><span>More at&nbsp;https://uwmadison.app.box.com/s/8j90e5h2rjrsz3bacaxnq8kor2o64vyg</span></p><p>Address of the bookmark: <a href="https://github.com/asroopra/MAGIC" rel="nofollow">https://github.com/asroopra/MAGIC</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/17898/ensembl-77-has-been-released</guid>
	<pubDate>Sun, 05 Oct 2014 16:38:58 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/17898/ensembl-77-has-been-released</link>
	<title><![CDATA[Ensembl 77 has been released!]]></title>
	<description><![CDATA[<h3>New updates in e!77 !!</h3><ul>
<li>Updated&nbsp;<a href="http://e77.ensembl.org/Homo_sapiens/Info/Index" title="Human species page">human</a>&nbsp;gene set (GENCODE 21)</li>
<li>Updated <a href="http://e77.ensembl.org/Rattus_norvegicus/Info/Index">rat</a> gene set&nbsp;including manual annotation from HAVANA</li>
<li>New species:&nbsp;<a href="http://e77.ensembl.org/Chlorocebus_sabaeus/Info/Index">Vervet-African green monkey</a></li>
<li>Imported Transcript Support Levels (TSLs) from UCSC&nbsp;for&nbsp;<a href="http://e77.ensembl.org/Homo_sapiens/Info/Index">human</a>&nbsp;and&nbsp;<a href="http://e77.ensembl.org/Mus_musculus/Info/Index">mouse</a></li>
<li>Imported <a href="http://appris.bioinfo.cnio.es/" target="_blank" title="APPRIS">APPRIS</a> flag for&nbsp;<a href="http://e77.ensembl.org/Homo_sapiens/Info/Index">human</a> and <a href="http://e77.ensembl.org/Mus_musculus/Info/Index">mouse</a></li>
<li>Updated <a href="http://e77.ensembl.org/Poecilia_formosa/Info/Index" title="Amazon molly">Amazon molly</a> gene set</li>
</ul><p>Find more at http://www.ensembl.info/blog/2014/10/02/ensembl-77-has-been-released/</p>]]></description>
	<dc:creator>Seema Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43867/genomeqc-a-quality-assessment-tool-for-genome-assemblies-and-gene-structure-annotations</guid>
	<pubDate>Thu, 19 May 2022 04:29:05 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43867/genomeqc-a-quality-assessment-tool-for-genome-assemblies-and-gene-structure-annotations</link>
	<title><![CDATA[GenomeQC: a quality assessment tool for genome assemblies and gene structure annotations]]></title>
	<description><![CDATA[<p><span>The GenomeQC web application is implemented in R/Shiny version 1.5.9 and Python 3.6 and is freely available at&nbsp;</span><a href="https://genomeqc.maizegdb.org/">https://genomeqc.maizegdb.org/</a><span>&nbsp;under the GPL license. All source code and a containerized version of the GenomeQC pipeline is available in the GitHub repository&nbsp;</span><a href="https://github.com/HuffordLab/GenomeQC">https://github.com/HuffordLab/GenomeQC</a><span>.</span></p>
<p>https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-020-6568-2</p><p>Address of the bookmark: <a href="https://github.com/HuffordLab/GenomeQC" rel="nofollow">https://github.com/HuffordLab/GenomeQC</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44501/minda-a-tool-for-evaluating-structural-variant-sv-callers</guid>
	<pubDate>Sun, 31 Mar 2024 02:43:50 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44501/minda-a-tool-for-evaluating-structural-variant-sv-callers</link>
	<title><![CDATA[Minda: a tool for evaluating structural variant (SV) callers]]></title>
	<description><![CDATA[<p dir="auto">Minda is a tool for evaluating structural variant (SV) callers that</p>
<ul dir="auto">
<li>standardizes VCF records for compatibility with both germline and somatic SV callers,</li>
<li>benchmarks against a single VCF input file, or</li>
<li>benchmarks against an ensemble call set created from multiple VCF input files.</li>
</ul><p>Address of the bookmark: <a href="https://github.com/KolmogorovLab/minda" rel="nofollow">https://github.com/KolmogorovLab/minda</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>

</channel>
</rss>