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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/32485?offset=1420</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38378/gwaspro-a-high-performance-genome-wide-association-analysis-server</guid>
	<pubDate>Fri, 07 Dec 2018 08:04:57 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38378/gwaspro-a-high-performance-genome-wide-association-analysis-server</link>
	<title><![CDATA[GWASpro: A High-Performance Genome-Wide Association Analysis Server]]></title>
	<description><![CDATA[<p>GWASpro supports building complex design matrices, by which complex experimental designs that may include replications, treatments, locations and times, can be accounted for in the linear mixed model (LMM). GWASpro is optimized to handle GWAS data that may consist of up to 10 million markers and 10,000 samples from replicable lines or hybrids. GWASpro provides an interface that significantly reduces the learning curve for new GWAS investigators.</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://bioinfo.noble.org/GWASPRO/" rel="nofollow">https://bioinfo.noble.org/GWASPRO/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27461/maftools</guid>
	<pubDate>Sat, 21 May 2016 22:40:21 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27461/maftools</link>
	<title><![CDATA[mafTools]]></title>
	<description><![CDATA[<p><span>Bioinformatics tools for dealing with Multiple Alignment Format (MAF) files.</span></p><p>Address of the bookmark: <a href="https://github.com/dentearl/mafTools" rel="nofollow">https://github.com/dentearl/mafTools</a></p>]]></description>
	<dc:creator>Radha Agarkar</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/27473/project-assistantjunior-research-fellow-position-at-centre-of-biomedical-research-sanjay-gandhi-postgraduate-institute-of-medical-sciences-campus-lucknow</guid>
  <pubDate>Mon, 23 May 2016 01:31:29 -0500</pubDate>
  <link></link>
  <title><![CDATA[Project Assistant/Junior Research Fellow Position at  Centre of Biomedical Research, Sanjay Gandhi Postgraduate Institute of Medical Sciences Campus, Lucknow.]]></title>
  <description><![CDATA[
<p>Applications are invited from eligible candidates willing to join in a Department of Science and Technology (DST) project entitled “"Mapping neural regions involved in reading process in skilled adult Deaf reader: From neuroimaging perspective (functional Magnetic Resonance Imaging (fMRI) and Diffuse Tensor Imaging (DTI.)" as a Project Assistant/Junior Research Fellow (JRF) at Centre of Biomedical Research, Sanjay Gandhi Postgraduate Institute of Medical Sciences Campus, Lucknow.</p>

<p>Essential Qualification:</p>

<p>1. Master's degree in Bioinformatics / Computer Applications / Cognitive Science /Neuroscience/ Neuropsychology or equivalent. (Advantage will be given to NET JRF qualified candidate) Additional</p>

<p>Desirable Skills:</p>

<p>1) Programming skills (e.g., C++, Matlab, Python) 2) Experience/competent in working Window and Linux based programme.</p>

<p>Please mail your CV and covering letter to dr.uttam.kumar@gmail.com.</p>

<p>To know more about lab works please visit http://uttambrainlab.co.in/lab/.</p>

<p>Last date: 15/06/16</p>

<p>Advertisement: http://cbmr.res.in/wp-content/uploads/2016/05/Advertisement-19-5-2016.pdf</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44539/bactopia-a-flexible-pipeline-for-complete-analysis-of-bacterial-genomes</guid>
	<pubDate>Wed, 15 May 2024 14:36:12 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44539/bactopia-a-flexible-pipeline-for-complete-analysis-of-bacterial-genomes</link>
	<title><![CDATA[Bactopia: a Flexible Pipeline for Complete Analysis of Bacterial Genomes]]></title>
	<description><![CDATA[<p dir="auto">Bactopia is a flexible pipeline for complete analysis of bacterial genomes. The goal of Bactopia is to process your data with a broad set of tools, so that you can get to the fun part of analyses quicker!</p>
<p dir="auto">Bactopia can be split into two main parts:&nbsp;<a href="https://bactopia.github.io/latest/beginners-guide/">Bactopia Analysis Pipeline</a>, and&nbsp;<a href="https://bactopia.github.io/latest/bactopia-tools/">Bactopia Tools</a>.</p>
<p dir="auto">Bactopia Analysis Pipeline is the main&nbsp;<em>per-isolate</em>&nbsp;workflow in Bactopia. Built with&nbsp;<a href="https://www.nextflow.io/">Nextflow</a>, input FASTQs (local or available from SRA/ENA) are put through numerous analyses including: quality control, assembly, annotation, minmer sketch queries, sequence typing, and more.</p>
<p dir="auto"><a href="https://github.com/bactopia/bactopia/blob/master/data/bactopia-workflow.png" target="_blank"><img src="https://github.com/bactopia/bactopia/raw/master/data/bactopia-workflow.png" alt="Bactopia Overview" style="border: 0px;"></a></p>
<p dir="auto">Bactopia Tools are a set a independent workflows fo</p><p>Address of the bookmark: <a href="https://github.com/bactopia/bactopia" rel="nofollow">https://github.com/bactopia/bactopia</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/27554/jrf-bioinformatics-at-actrec-navi-mumbai</guid>
  <pubDate>Mon, 30 May 2016 03:24:22 -0500</pubDate>
  <link></link>
  <title><![CDATA[JRF Bioinformatics at ACTREC, Navi Mumbai]]></title>
  <description><![CDATA[
<p>No. ACTREC/Advt./23/2016<br />JRF Bioinformatics recruitment in ACTREC (On contract Basis- Primeone Workforce Pvt. Ltd.)<br />Title : “Investigating the molecular basis of CaM/c-FLIP interaction to design specific c-FLIP inhibitor for modulating its anti-apoptotic function”.<br />Qualification : Master’s degree in bioinformatics, biochemistry, biotechnology and biological sciences from a recognized university with not less than 55% aggregate marks. Experience: Prior experience in modelling, protein-protein/ligand docking, Molecular dynamics simulation required. Knowledge in database development will be preferred.   </p>

<p>Pay Scale : Rs. 32,500/- <br />How to apply<br />Candidates fulfilling these requirements should pre-register by sending their application in the prescribed format with recent CV and contact details of 2 referees by e-mail to  ‘program.office@actrec.gov.in’ latest by  17.00 hrs on 23-06-2016. The interviews would be held on 27-06-2016 and only pre-registered candidates will be eligible to appear for interview. Candidates should report between 09.30 to 10.00 a.m. in Steno Pool,  3rd floor, Khanolkar Shodhika, ACTREC, Kharghar, Navi Mumbai.</p>

<p>More at http://www.actrec.gov.in/</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/27695/the-kingsley-lab</guid>
  <pubDate>Fri, 03 Jun 2016 09:55:10 -0500</pubDate>
  <link></link>
  <title><![CDATA[The Kingsley Lab]]></title>
  <description><![CDATA[
<p>The Molecular Basis of Vertebrate Evolution. Naturally occurring species show spectacular differences in morphology, physiology, behavior, disease susceptibility, and life span. Although the genomes of many organisms have now been completely sequenced, Kingsley lab still know relatively little about the specific DNA sequence changes that underlie interesting species-specific traits. Kingsley lab laboratory is using a combination of genetic and genomic approaches to identify the detailed molecular mechanisms that control evolutionary change in vertebrates.</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33912/mesquite-a-modular-system-for-evolutionary-analysis</guid>
	<pubDate>Tue, 18 Jul 2017 07:42:46 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33912/mesquite-a-modular-system-for-evolutionary-analysis</link>
	<title><![CDATA[Mesquite: A modular system for evolutionary analysis]]></title>
	<description><![CDATA[<p><span>Mesquite is modular, extendible software for evolutionary biology, designed to help biologists organize and analyze comparative data about organisms. Its emphasis is on phylogenetic analysis, but some of its modules concern population genetics, while others do non-phylogenetic multivariate analysis. Because it is modular, the analyses available depend on the modules installed.</span></p>
<p><span>http://mesquiteproject.wikispaces.com/</span></p><p>Address of the bookmark: <a href="https://github.com/MesquiteProject/MesquiteCore/releases" rel="nofollow">https://github.com/MesquiteProject/MesquiteCore/releases</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/34465/rnaseq-data-analysis-links</guid>
	<pubDate>Mon, 27 Nov 2017 16:28:11 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/34465/rnaseq-data-analysis-links</link>
	<title><![CDATA[RNAseq data analysis links !]]></title>
	<description><![CDATA[<p>RNA-sequencing (RNA-seq) has a wide variety of applications, but no single analysis pipeline can be used in all cases. We review all of the major steps in RNA-seq data analysis, including experimental design, quality control, read alignment, quantification of gene and transcript levels, visualization, differential gene expression, alternative splicing, functional analysis, gene fusion detection and eQTL mapping.</p><p><a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4728800/" target="_blank">A survey of best practices for RNA-seq data analysis</a></p><p><a href="http://www.bioconductor.org/help/workflows/rnaseqGene/" target="_blank">RNA-seq workflow: gene-level exploratory analysis and DE</a></p><p><a href="https://github.com/crazyhottommy/RNA-seq-analysis" target="_blank">RNAseq analysis notes from Tommy Tang</a></p><p><a href="http://web.stanford.edu/group/wonglab/doc/RNA-seq-talk-JSM2010.pdf" target="_blank">Analysis of RNA ‐ Seq Data</a></p><p><a href="https://f1000research.com/articles/5-1408/v2" target="_blank">RNA-seq analysis is easy as 1-2-3 with limma, Glimma and edgeR</a></p><p><a href="http://www.nature.com/nprot/journal/v7/n3/full/nprot.2012.016.html" target="_blank">Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks.</a></p><p><a href="https://www.ebi.ac.uk/training/online/course/ebi-next-generation-sequencing-practical-course/rna-sequencing/rna-seq-analysis-transcriptome" target="_blank">EBI RNA-Seq exercise</a></p><p><a href="https://f1000research.com/articles/5-1574/v1" target="_blank">An open RNA-Seq data analysis pipeline tutorial with an example</a></p><p><a href="https://ycl6.gitbooks.io/rna-seq-data-analysis/rna-seq_analysis_workflow.html" target="_blank">RNA-Seq Analysis Workflow</a></p><p><a href="http://www.nature.com/nprot/journal/v11/n9/full/nprot.2016.095.html" target="_blank">Transcript-level expression analysis of RNA-seq experiments</a></p>]]></description>
	<dc:creator>Robert M Willioms</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27841/covcal-coverage-read-count-calculator</guid>
	<pubDate>Wed, 15 Jun 2016 18:08:13 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27841/covcal-coverage-read-count-calculator</link>
	<title><![CDATA[CovCal: Coverage / Read Count Calculator]]></title>
	<description><![CDATA[<h2>Coverage / Read Count Calculator</h2>
<h4>Calculate how much sequencing you need to hit a target depth of coverage (or vice versa).</h4>
<p><span>Instructions:</span> set the read length/configuration and genome size, then select what you want to calculate.</p>
<p>Written by <a href="http://stephenturner.us/" target="blank">Stephen Turner</a>, based on the <a href="http://www.ncbi.nlm.nih.gov/pubmed/3294162" target="_blank">Lander-Waterman formula</a>, inspired by <a href="http://core-genomics.blogspot.com/2016/05/how-many-reads-to-sequence-genome.html" target="_blank">a similar calculator</a> written by James Hadfield. Coverage is calculated as <em>C=LN/G</em> and reads as <em>N=CG/L</em> where <em>C</em> = Coverage (X),<em>L</em> = Read length (bp), <em>G</em> = Haploid genome size (bp), and <em>N</em> = Number of reads. Source code <a href="https://github.com/stephenturner/covcalc" target="_blank">on GitHub</a>.</p><p>Address of the bookmark: <a href="http://apps.bioconnector.virginia.edu/covcalc/" rel="nofollow">http://apps.bioconnector.virginia.edu/covcalc/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27959/darkhorse</guid>
	<pubDate>Wed, 22 Jun 2016 05:37:38 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27959/darkhorse</link>
	<title><![CDATA[DarkHorse]]></title>
	<description><![CDATA[<p><em>DarkHorse</em>&nbsp;is a bioinformatic method for rapid, automated identification and ranking of phylogenetically atypical proteins on a genome-wide basis. It works by selecting potential ortholog matches from a reference database of amino acid sequences, then using these matches to calculate a lineage probability index (LPI) score for each genome protein.</p>
<p>LPI scores are inversely proportional to the phylogenetic distance between database match sequences and the query genome. These scores are useful not only for large-scale<em>de novo</em>&nbsp;predictions of horizontally transferred proteins, but can also serve as an independent quality control test for potential horizontal transfer candidates identified by alternative methods, especially those based on nucleic acid signatures. Candidates having high LPI scores are unlikely to have been horizontally transferred, since they are highly conserved among closely related organisms.</p>
<p>One unique and powerful feature of the DarkHorse HGT Candidate database is the opportunity to explore the phylogenetic background of potential HGT donors as well as recipients. The breadth of the database allows not only query sequences, but also their database match partners to be evaluated for sequence similarity or novelty compared to taxonomically related organisms.</p>
<p><em>DarkHorse</em>&nbsp;is configurable for varying degrees of phylogenetic granularity and protein sequence conservation. Users should consult the&nbsp;<a href="http://darkhorse.ucsd.edu/#references">references</a>&nbsp;cited below for a complete explanation of parameter selection and result interpretation. A brief&nbsp;<a href="http://darkhorse.ucsd.edu/tutorial.html">tutorial</a>&nbsp;page is also available on-line.</p><p>Address of the bookmark: <a href="http://darkhorse.ucsd.edu/download.html" rel="nofollow">http://darkhorse.ucsd.edu/download.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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