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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/38004?offset=90</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38743/molinspiration-broad-range-of-cheminformatics-software-tools-supporting-molecule-manipulation</guid>
	<pubDate>Sun, 20 Jan 2019 05:32:40 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38743/molinspiration-broad-range-of-cheminformatics-software-tools-supporting-molecule-manipulation</link>
	<title><![CDATA[molinspiration: broad range of cheminformatics software tools supporting molecule manipulation]]></title>
	<description><![CDATA[<p><span>Molinspiration offers&nbsp;</span><a href="https://www.molinspiration.com/products.html">broad range of cheminformatics software tools</a><span>&nbsp;supporting molecule manipulation and processing, including SMILES and SDfile conversion, normalization of molecules, generation of tautomers, molecule fragmentation, calculation of various molecular properties needed in QSAR, molecular modelling and drug design, high quality molecule depiction, molecular database tools supporting substructure and similarity searches. Our products support also fragment-based virtual screening, bioactivity prediction and data visualization. Molinspiration tools are written in Java, therefore can be used practically on any computer platform.</span></p><p>Address of the bookmark: <a href="https://www.molinspiration.com/" rel="nofollow">https://www.molinspiration.com/</a></p>]]></description>
	<dc:creator>BioJoker</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/40882/troyanskaya-lab</guid>
  <pubDate>Tue, 04 Feb 2020 06:40:36 -0600</pubDate>
  <link></link>
  <title><![CDATA[Troyanskaya Lab]]></title>
  <description><![CDATA[
<p>The goal of our research is to interpret and distill this complexity through accurate analysis and modeling of molecular pathways, particularly those in which malfunctions lead to the manifestation of disease. We are inventing integrative methods for systems-level pathway modeling through integrative analysis of genome-scale datasets. We apply these approaches in studying challenging biological problems, such as how pathways function in diverse cell types and how they change dynamically.</p>

<p>https://function.princeton.edu/</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/42166/software-for-genome-assembly</guid>
	<pubDate>Sun, 30 Aug 2020 09:51:38 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/42166/software-for-genome-assembly</link>
	<title><![CDATA[Software for genome assembly !]]></title>
	<description><![CDATA[<p>List of bioinformatics tools/Software Website References for genome assembly:</p><p>1 Falcon&nbsp;https://github.com/PacificBiosciences/pb-assembly</p><p>2 Canu assembler http://canu.readthedocs.io/en/latest/index.html</p><p>3 Miniasm assembler https://github.com/lh3/miniasm</p><p>4 PBJelly scaffolding tool https://sourceforge.net/projects/pb-jelly/</p><p>5 ARCS scaffolding tool https://github.com/bcgsc/arcs</p><p>6 Redundans reduction and scaffolding tool https://github.com/Gabaldonlab/redundans</p><p>7 Arrow error correction https://github.com/PacificBiosciences/ GenomicConsensus</p><p>8 PILON error correction https://github.com/broadinstitute/pilon/wiki</p><p>9 BUSCO single copy gene markers http://busco.ezlab.org/</p><p>10 Bandage graph assembly viewer https://rrwick.github.io/Bandage/</p><p>11 Gepard dotter http://cube.univie.ac.at/gepard</p><p>12 MUMmer aligner and plotter http://mummer.sourceforge.net/</p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/43084/frequently-used-bioinformatics-tools-for-viral-genome-analysis</guid>
	<pubDate>Wed, 23 Jun 2021 07:40:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/43084/frequently-used-bioinformatics-tools-for-viral-genome-analysis</link>
	<title><![CDATA[Frequently used bioinformatics tools for viral genome analysis !]]></title>
	<description><![CDATA[<p><strong>IVA: accurate de novo assembly of RNA virus genomes.</strong><br /> Hunt M, Gall A, Ong SH, Brener J, Ferns B, Goulder P, Nastouli E, Keane JA, Kellam P, Otto TD.<br /> Bioinformatics. 2015 Jul 15;31(14):2374-6. doi: <a href="http://bioinformatics.oxfordjournals.org/content/31/14/2374.long">10.1093/bioinformatics/btv120</a>. Epub 2015 Feb 28.</p><p><a href="http://www.nature.com/nmeth/journal/v9/n1/full/nmeth.1814.html"><strong>Adapter sequences</strong></a>:<br /> <strong>Optimal enzymes for amplifying sequencing libraries.</strong><br /> Quail, M. a et al. Nat. Methods 9, 10-1 (2012).</p><p><a href="http://genome.cshlp.org/content/early/2012/01/12/gr.131383.111"><strong>GAGE</strong></a>:<br /> <strong>GAGE: A critical evaluation of genome assemblies and assembly algorithms.</strong><br /> Salzberg, S. L. et al. Genome Res. 22, 557-67 (2012).</p><p><a href="http://www.biomedcentral.com/1471-2105/14/160"><strong>KMC</strong></a>:<br /> <strong>Disk-based k-mer counting on a PC.</strong><br /> Deorowicz, S., Debudaj-Grabysz, A. &amp; Grabowski, S. BMC Bioinformatics 14, 160 (2013).</p><p><a href="http://genomebiology.com/2014/15/3/R46"><strong>Kraken</strong></a>:<br /> <strong>Kraken: ultrafast metagenomic sequence classification using exact alignments.</strong><br /> Wood, D. E. &amp; Salzberg, S. L. Genome Biol. 15, R46 (2014).</p><p><a href="http://genomebiology.com/2004/5/2/r12"><strong>MUMmer</strong></a>:<br /> <strong>Versatile and open software for comparing large genomes.</strong><br /> Kurtz, S. et al. Genome Biol. 5, R12 (2004).</p><p><strong>R</strong>:<br /> <strong>R: A language and environment for statistical computing.</strong><br /> R Core Team (2013). R Foundation for Statistical Computing, Vienna, Austria. URL <a href="http://www.R-project.org/">http://www.R-project.org/</a>.</p><p><a href="http://nar.oxfordjournals.org/content/39/9/e57"><strong>RATT</strong></a>:<br /> <strong>RATT: Rapid Annotation Transfer Tool.</strong><br /> Otto, T. D., Dillon, G. P., Degrave, W. S. &amp; Berriman, M. Nucleic Acids Res. 39, e57 (2011).</p><p><a href="http://bioinformatics.oxfordjournals.org/content/25/16/2078.abstract"><strong>SAMtools</strong></a>:<br /> <strong>The Sequence Alignment/Map format and SAMtools.</strong><br /> Li, H. et al. Bioinformatics 25, 2078-9 (2009).</p><p><a href="http://bioinformatics.oxfordjournals.org/content/early/2014/04/12/bioinformatics.btu170"><strong>Trimmomatic</strong></a>:<br /> <strong>Trimmomatic: A flexible trimmer for Illumina Sequence Data.</strong><br /> Bolger, A. M., Lohse, M. &amp; Usadel, B. Bioinformatics 1-7 (2014).</p>]]></description>
	<dc:creator>Neel</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/43728/short-read-assembly-using-spades</guid>
	<pubDate>Mon, 31 Jan 2022 07:18:16 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/43728/short-read-assembly-using-spades</link>
	<title><![CDATA[Short-read assembly using Spades !]]></title>
	<description><![CDATA[<h2 id="short-read-assembly-a-comparison">If we only had Illumina reads, we could also assemble these using the tool Spades.</h2><p>You can try this here, or try it later on your own data.</p><h2 id="get-data">Get data</h2><p>We will use the same Illumina data as we used above:</p><ul>
<li>illumina_R1.fastq.gz: the Illumina forward reads</li>
<li>illumina_R2.fastq.gz: the Illumina reverse reads</li>
</ul><h2 id="assemble">Assemble</h2><p>Run Spades:</p><div><pre>spades.py -1 illumina_R1.fastq.gz -2 illumina_R2.fastq.gz --careful --cov-cutoff auto -o spades_assembly_all_illumina
</pre></div><ul>
<li><code>-1</code>&nbsp;is input file of forward reads</li>
<li><code>-2</code>&nbsp;is input file of reverse reads</li>
<li><code>--careful</code>&nbsp;minimizes mismatches and short indels</li>
<li><code>--cov-cutoff auto</code>&nbsp;computes the coverage threshold (rather than the default setting, &ldquo;off&rdquo;)</li>
<li><code>-o</code>&nbsp;is the output directory</li>
</ul><h2 id="results">Results</h2><p>Move into the output directory and look at the contigs:</p><div><pre>infoseq contigs.fasta</pre></div>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44551/bioinformatic-tools-for-pathogens-informatics-at-cvr</guid>
	<pubDate>Sat, 08 Jun 2024 15:59:46 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44551/bioinformatic-tools-for-pathogens-informatics-at-cvr</link>
	<title><![CDATA[Bioinformatic tools for pathogens informatics at CVR]]></title>
	<description><![CDATA[<div><div><div><div><div><p>Novel sequencing and analytical approaches focused on studying viruses and virus-host interactions. Below you will find summaries and links to a number of bioinformatic tools that have been developed @ CVR.</p></div><div><h3><a href="http://giffordlabcvr.github.io/DIGS-tool/" target="_blank" title="DIGS">DIGS</a></h3></div><div><p>The database-integrated genome-screening (DIGS) tool provides a framework for implementing automated in silico screening of sequence databases using BLAST in combination with a relational database (MySQL).</p></div><div><h3><a href="https://bioinformatics.cvr.ac.uk/software/discvr/" target="" title="DisCVR">DisCVR</a></h3></div><div><p>DisCVR is a Diagnostic tool for detecting known human viruses in clinical samples from Next-Generation Sequencing (NGS) data. The tool uses a simple and straightforward Graphical User Interface and is optimized on Windows OS without compromising speed and accuracy.</p></div><div><h3><a href="http://josephhughes.github.io/DiversiTools/" target="_blank" title="DiversiTools">DiversiTools</a></h3></div><div><p>DiversiTools is a computational tool that is specifically tailored towards viral HTS data sets and the analysis of the underlying viral populations that they represent. It was initially developed in collaboration with a number of virologists interested in characterising the intra-host diversity of viral populations and studying their evolution across transmission chains at the micro-evolutionary scale.</p></div><div><h3><a href="http://glue-tools.cvr.gla.ac.uk/" target="_blank" title="GLUE">GLUE</a></h3></div><div><p>GLUE is a flexible data-centric bioinformatics environment for virus sequence data, with a focus on virus evolution and genomic variation. GLUE has been applied to a range of viruses. A GLUE-based resource focused on Hepatitis C virus is HCV-GLUE.</p></div><div><h3><a href="https://bioinformatics.cvr.ac.uk/tanoti/" target="_blank" title="Tanoti">Tanoti</a></h3></div><div><p>Tanoti is a BLAST guided reference based short read aligner. It is developed for maximising alignment in highly variable next generation sequence data sets (Illumina).</p></div><div><h3><a href="https://bioinformatics.cvr.ac.uk/victree/" target="_blank" title="VicTREE">ViCTree</a></h3></div><div><p>ViCTree is a bioinformatic framework that automatically selects new candidate virus sequences from GenBank, generates multiple sequence alignments, calculates a maximum likelihood phylogeny and integrates the sequences into the existing phylogenetic trees.&nbsp;<span>For more information click&nbsp;</span><a href="https://bioinformatics.cvr.ac.uk/victree_web/" target="_blank">here</a>.</p></div></div></div></div></div><div><div><div><div><div><h3><a href="https://bioinformatics.cvr.ac.uk/software/viral-host-predictor/" target="" title="Viral Host Predictor">Viral Host Predictor</a></h3></div><div><p>Viral Host Predictor provides a fast and simple way to predict the hosts and vectors of RNA viruses from viral sequences.</p></div><div><h3><a href="https://github.com/salvocamiolo/GRACy/releases/tag/v0.4.4" target="_blank" title="GRACy">GRACy</a></h3></div><div><p>GRACy is a bioinformatic tool designed for the analysis of Illumina data originated from Human cytomegalovirus samples. GRACy can be used to perform read quality filtering, genotyping, de novo assembly, variant detection, annotation and data submission to public database.</p></div><div><h3><a href="https://github.com/salvocamiolo/LoReTTA/releases/tag/v0.1" target="_blank" title="LoReTTA">LoReTTA</a></h3></div><div><p>LoReTTA (Long Read Template Targeted Assembler) is a reference assisted de novo assembler specifically designed to deal with PacBio reads generated from viral genomes.&nbsp;</p></div><div><h3><a href="https://bioinformatics.cvr.ac.uk/software/bingleseq/" target="" title="BingleSeq">BingleSeq</a></h3></div><div><p>BingleSeq is a R-package enables the user-friendly analysis of count tables obtained by both Bulk RNA-Seq and single-cell RNA-Seq protocols. The development of BingleSeq focused on providing a flexible and intuitive user experience.</p></div></div></div></div></div>]]></description>
	<dc:creator>Abhi</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/13267/the-genome-10k-project</guid>
	<pubDate>Tue, 29 Jul 2014 09:11:04 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/13267/the-genome-10k-project</link>
	<title><![CDATA[The Genome 10K Project]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/B57xDIGtCT0" frameborder="0" allowfullscreen></iframe>https://genome10k.soe.ucsc.edu

The Genome 10K project aims to assemble a genomic zoo—a collection of DNA sequences representing the genomes of 10,000 vertebrate species, approximately one for every vertebrate genus. The trajectory of cost reduction in DNA sequencing suggests that this project will be feasible within a few years. Capturing the genetic diversity of vertebrate species would create an unprecedented resource for the life sciences and for worldwide conservation efforts.

The growing Genome 10K Community of Scientists (G10KCOS), made up of leading scientists representing major zoos, museums, research centers, and universities around the world, is dedicated to coordinating efforts in tissue specimen collection that will lay the groundwork for a large-scale sequencing and analysis project.]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43110/quasimodo-quasispecies-metric-determination-on-omics</guid>
	<pubDate>Sat, 26 Jun 2021 15:22:56 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43110/quasimodo-quasispecies-metric-determination-on-omics</link>
	<title><![CDATA[QuasiModo - Quasispecies Metric Determination on Omics]]></title>
	<description><![CDATA[<p><span>This repository contains the scripts and pipeline that reproduces the results of the HCMV benchmarking study. In this study we evaluated genome assemblers and variant callers on 10 in vitro generated, mixed strain HCMV sequence samples, each consisting of two lab strains in different abundance ratios. This tool can also be used to evaluate assemblies and variant calling results on other similar datasets.</span></p>
<p><span>https://academic.oup.com/bib/article/22/3/bbaa123/5868070</span></p><p>Address of the bookmark: <a href="https://github.com/hzi-bifo/Quasimodo" rel="nofollow">https://github.com/hzi-bifo/Quasimodo</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44628/uncovar-workflow-for-transparent-and-robust-virus-variant-calling-genome-reconstruction-and-lineage-assignment</guid>
	<pubDate>Mon, 05 Aug 2024 23:01:29 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44628/uncovar-workflow-for-transparent-and-robust-virus-variant-calling-genome-reconstruction-and-lineage-assignment</link>
	<title><![CDATA[UnCoVar: Workflow for Transparent and Robust Virus Variant Calling, Genome Reconstruction and Lineage Assignment]]></title>
	<description><![CDATA[<p>UnCoVar: Workflow for Transparent and Robust Virus Variant Calling, Genome Reconstruction and Lineage Assignment</p>
<ul>
<li>
<p>Using state of the art tools, easily extended for other viruses</p>
</li>
<li>
<p>Tool and database updates for critical components via Conda</p>
</li>
<li>
<p>Built using modern design patterns with Conda and Snakemake</p>
</li>
<li>
<p>Extensible and easy to customize</p>
</li>
<li>
<p>Submission Ready Genomes</p>
</li>
<li>
<p>Customizable reporting with comprehensive visualization</p>
</li>
</ul>
<p>https://ikim-essen.github.io/uncovar/</p>
<p>Github&nbsp;https://github.com/IKIM-Essen/uncovar</p>
<p>&nbsp;</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://ikim-essen.github.io/uncovar/" rel="nofollow">https://ikim-essen.github.io/uncovar/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39383/geck-trio-based-comparative-benchmarking-of-variant-calls</guid>
	<pubDate>Sun, 19 May 2019 20:54:12 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39383/geck-trio-based-comparative-benchmarking-of-variant-calls</link>
	<title><![CDATA[geck: trio-based comparative benchmarking of variant calls]]></title>
	<description><![CDATA[<p><span>Determine the accuracy of our model by comparing the precision and recall of GATK Unified Genotyper and Haplotype Caller on the high-confidence SNPs of the NIST Ashkenazim trio and the two independent Platinum Genome trios. We show that our method is able to estimate&nbsp;</span><em>differential</em><span>&nbsp;precision and recall between the two pipelines with&nbsp;</span><span>10<span>&minus;3</span></span><span>uncertainty.</span></p><p>Address of the bookmark: <a href="https://github.com/sbg/geck" rel="nofollow">https://github.com/sbg/geck</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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