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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/40598?offset=380</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42271/mcclintock-meta-pipeline-to-identify-transposable-element-insertions-using-next-generation-sequencing-data</guid>
	<pubDate>Tue, 27 Oct 2020 00:21:18 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42271/mcclintock-meta-pipeline-to-identify-transposable-element-insertions-using-next-generation-sequencing-data</link>
	<title><![CDATA[McClintock: Meta-pipeline to identify transposable element insertions using next generation sequencing data]]></title>
	<description><![CDATA[<p><span>an integrated bioinformatics pipeline for the detection of TE insertions in whole-genome shotgun data, called McClintock (</span><a href="https://github.com/bergmanlab/mcclintock">https://github.com/bergmanlab/mcclintock</a><span>), which automatically runs and standardizes output for multiple TE detection methods. We demonstrate the utility of McClintock by evaluating six TE detection methods using simulated and real genome data from the model microbial eukaryote,&nbsp;</span><em>Saccharomyces cerevisiae</em><span>.&nbsp;</span></p><p>Address of the bookmark: <a href="https://github.com/bergmanlab/mcclintock" rel="nofollow">https://github.com/bergmanlab/mcclintock</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26852/awesome-bioinformatics-pipelines</guid>
	<pubDate>Wed, 30 Mar 2016 21:50:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26852/awesome-bioinformatics-pipelines</link>
	<title><![CDATA[Awesome bioinformatics pipelines !]]></title>
	<description><![CDATA[<p><span>A curated list of awesome pipeline toolkits ...</span></p>
<p><span>https://github.com/pditommaso/awesome-pipeline</span></p><p>Address of the bookmark: <a href="https://github.com/pditommaso/awesome-pipeline" rel="nofollow">https://github.com/pditommaso/awesome-pipeline</a></p>]]></description>
	<dc:creator>Jitendra Prajapati</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38747/seqkit-a-cross-platform-and-ultrafast-toolkit-for-fastaq-file-manipulation</guid>
	<pubDate>Sun, 20 Jan 2019 06:18:32 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38747/seqkit-a-cross-platform-and-ultrafast-toolkit-for-fastaq-file-manipulation</link>
	<title><![CDATA[SeqKit - a cross-platform and ultrafast toolkit for FASTA/Q file manipulation]]></title>
	<description><![CDATA[<p><span>FASTA and FASTQ are basic and ubiquitous formats for storing nucleotide and protein sequences. Common manipulations of FASTA/Q file include converting, searching, filtering, deduplication, splitting, shuffling, and sampling. Existing tools only implement some of these manipulations, and not particularly efficiently, and some are only available for certain operating systems. Furthermore, the complicated installation process of required packages and running environments can render these programs less user friendly.</span></p><p>Address of the bookmark: <a href="https://bioinf.shenwei.me/seqkit/usage/" rel="nofollow">https://bioinf.shenwei.me/seqkit/usage/</a></p>]]></description>
	<dc:creator>BioJoker</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43445/parebrick-parallel-rearrangements-and-breaks-identification-toolkit</guid>
	<pubDate>Fri, 08 Oct 2021 10:20:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43445/parebrick-parallel-rearrangements-and-breaks-identification-toolkit</link>
	<title><![CDATA[PaReBrick: PArallel REarrangements and BReaks identification toolkit]]></title>
	<description><![CDATA[<p><span>PaReBrick. The tool takes a collection of strains represented as a sequence of oriented synteny blocks and a phylogenetic tree as input data. It identifies rearrangements, tests them for consistency with a tree, and sorts the events by their parallelism score. The tool provides diagrams of the neighbors for each block of interest, allowing the detection of horizontally transferred blocks or their extra copies and the inversions in which copied blocks are involved.We demonstrated PaReBrick&rsquo;s efficiency and accuracy and showed its potential to detect genome rearrangements responsible for pathogenicity and adaptation in bacterial genomes</span></p>
<p>More at&nbsp;https://academic.oup.com/bioinformatics/advance-article/doi/10.1093/bioinformatics/btab691/6380551</p>
<p><img src="https://github.com/ctlab/parallel-rearrangements/raw/master/figs/pipeline.svg" alt="image" style="border: 0px;"></p><p>Address of the bookmark: <a href="https://github.com/ctlab/parallel-rearrangements" rel="nofollow">https://github.com/ctlab/parallel-rearrangements</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27821/blobsplorer</guid>
	<pubDate>Tue, 14 Jun 2016 10:28:58 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27821/blobsplorer</link>
	<title><![CDATA[Blobsplorer]]></title>
	<description><![CDATA[<p>Blobsplorer is a tool for interactive visualization of assembled DNA sequence data ("contigs") derived from (often unintentionally) mixed-species pools. It allows the simultaneous display of GC content, coverage, and taxonomic annotation for collections of contigs with a view to separating out those belonging to different taxa.</p>
<p>Blobsplorer is unlikely to be of use on its own as it requires contig data to be supplied in a format that involves considerable preprocessing (see below for a description). The easiest way to use Blobsplorer is as part of a workflow using scripts from <a href="https://github.com/blaxterlab/blobology">here</a>.</p><p>Address of the bookmark: <a href="http://nematodes.org/martin/blobsplorer/blobsplorer.html" rel="nofollow">http://nematodes.org/martin/blobsplorer/blobsplorer.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33820/circular-visualization-in-r</guid>
	<pubDate>Wed, 05 Jul 2017 04:11:30 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33820/circular-visualization-in-r</link>
	<title><![CDATA[Circular Visualization in R]]></title>
	<description><![CDATA[<p>This is the documentation of the&nbsp;<a href="https://cran.r-project.org/package=circlize"><span>circlize</span></a>&nbsp;package. Examples in the book are generated under version 0.4.1.</p>
<p>If you use&nbsp;<span>circlize</span>&nbsp;in your publications, I would be appreciated if you can cite:</p>
<p>Gu, Z. (2014) circlize implements and enhances circular visualization in R. Bioinformatics. DOI:&nbsp;<a href="https://doi.org/10.1093/bioinformatics/btu393">10.1093/bioinformatics/btu393</a></p><p>Address of the bookmark: <a href="http://zuguang.de/circlize_book/book/" rel="nofollow">http://zuguang.de/circlize_book/book/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36216/crusview</guid>
	<pubDate>Thu, 12 Apr 2018 09:22:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36216/crusview</link>
	<title><![CDATA[CrusView]]></title>
	<description><![CDATA[<p><span>CrusView&nbsp;is a java based tool for karyotype/genome visualization and comparison of crucifer&nbsp;Species. It also integrates an binary version of KGBassembler and a&nbsp;post-modification step for its assembling result.</span></p><p>Address of the bookmark: <a href="http://www.cmbb.arizona.edu/?page_id=250" rel="nofollow">http://www.cmbb.arizona.edu/?page_id=250</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37230/navigator-network-analysis-visualization-and-graphing-toronto</guid>
	<pubDate>Tue, 03 Jul 2018 05:05:55 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37230/navigator-network-analysis-visualization-and-graphing-toronto</link>
	<title><![CDATA[NAViGaTOR: Network Analysis, Visualization and Graphing Toronto]]></title>
	<description><![CDATA[NAViGaTOR –  Network Analysis, Visualization, &amp; Graphing TORonto is a software system for scaleable visualizing and analyzing networks.

The current version, NAViGaTOR 3, increases modularity, improves scaleability, extends input/output options, brings new network views and analysis algorithms.

http://142.150.188.236/navigatorwp/<p>Address of the bookmark: <a href="http://142.150.188.236/navigatorwp/" rel="nofollow">http://142.150.188.236/navigatorwp/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38819/upsetr-an-r-package-for-the-visualization-of-intersecting-sets-and-their-properties</guid>
	<pubDate>Mon, 28 Jan 2019 18:38:44 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38819/upsetr-an-r-package-for-the-visualization-of-intersecting-sets-and-their-properties</link>
	<title><![CDATA[UpSetR: An R Package for the Visualization of Intersecting Sets and their Properties]]></title>
	<description><![CDATA[<p>UpSetR generates static&nbsp;<a href="http://vcg.github.io/upset/">UpSet</a>&nbsp;plots. The UpSet technique visualizes set intersections in a matrix layout and introduces aggregates based on groupings and queries. The matrix layout enables the effective representation of associated data, such as the number of elements in the aggregates and intersections, as well as additional summary statistics derived from subset or element attributes.</p>
<p>For further details about the original technique see the&nbsp;<a href="http://vcg.github.io/upset/about/">UpSet website</a>. You can also check out the&nbsp;<a href="https://gehlenborglab.shinyapps.io/upsetr/">UpSetR shiny app</a>.&nbsp;<a href="https://github.com/hms-dbmi/UpSetR-shiny">Here is the source code</a>&nbsp;for the shiny wrapper.</p>
<p>A&nbsp;<a href="https://github.com/ImSoErgodic/py-upset">Python package</a>&nbsp;called&nbsp;<a href="https://github.com/ImSoErgodic/py-upset">py-upset</a>&nbsp;to create UpSet plots has been created by GitHub user&nbsp;<a href="https://github.com/ImSoErgodic">ImSoErgodic</a>.</p><p>Address of the bookmark: <a href="https://github.com/hms-dbmi/UpSetR/" rel="nofollow">https://github.com/hms-dbmi/UpSetR/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/35395/comprehensive-list-of-visualization-tools-for-biological-pathways</guid>
	<pubDate>Tue, 30 Jan 2018 06:01:31 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/35395/comprehensive-list-of-visualization-tools-for-biological-pathways</link>
	<title><![CDATA[Comprehensive list of visualization tools for biological pathways]]></title>
	<description><![CDATA[<p>The study of biological pathways is a key to understand the different processes inside a cell: proteins exert their function not in isolation but in a tightly controlled network of interactions and reactions. Activation of a pathway typically leads to a change of state in the cell. Pathways come in different flavors, depending on their functions in the cell &ndash; the three main types are metabolic pathways, gene regulatory pathways, and signaling pathways. These biological pathways and networks are not only an appropriate approach to visualize molecular reactions. They have also become one leading method in -omics data analysis and visualization.</p><p><img src="https://photos-1.dropbox.com/t/2/AABemz29qAuSTqSzr5mEsQE7JIMxZlU1CBy0E5n0yUVYbA/12/85115969/png/32x32/1/_/1/2/pathway.png/EOfXoUIYrJ8CIAcoBw/01qsT2eykyPvSH-rNpy3cqioDzZPc4i-xULG3BEZvCk?preserve_transparency=1&amp;size=1280x960&amp;size_mode=3" width="800" height="533" alt="image" style="border: 0px;"></p><p>Following are the comprehensive list of visualization tools for biological pathways:</p><p>BiNA</p><p>Drawings of metabolic networks supporting hiding of cofactors and drawing of chemical structures</p><p>http://bina.unipax.info/</p><p>BioTapestry</p><p>Interactive tool for building, visualizing and sharing gene regulatory network models over the web</p><p>http://www.biotapestry.org/</p><p>Caleydo</p><p>Visual analysis framework targeted at biomolecular data. Visualization of interdependencies between multiple datasets</p><p>http://www.caleydo.org/</p><p>CellDesigner</p><p>A modeling tool for biochemical networks</p><p>http://www.celldesigner.org/</p><p>Edinburgh Pathway Editor</p><p>Edit and draw pathway diagrams</p><p>http://epe.sourceforge.net/SourceForge/EPE.html</p><p>GenMAPP</p><p>Visualization of gene expression and other genomic data on maps representing biological pathways and groupings of genes</p><p>http://www.genmapp.org/</p><p>Ingenuity IPA</p><p>Data integration platform and manually annotated pathways</p><p>http://tinyurl.com/IngenuityPath</p><p>JDesigner</p><p>Graphical modeling environment for biochemical reaction networks</p><p>http://jdesigner.sourceforge.net/Site/JDesigner.html</p><p>KaPPA View</p><p>Plant pathways</p><p>http://kpv.kazusa.or.jp/</p><p>KEGG Atlas</p><p>Interactive Kyoto Encyclopedia of Genes and Genomes pathways</p><p>http://www.genome.jp/kegg/</p><p>Omix&nbsp;</p><p>Visualizing multi-omics data in metabolic networks</p><p>https://www.omix-visualization.com</p><p>PathVisio&nbsp;</p><p>Biological pathway analysis software that allows drawing, editing and analysis of biological pathways</p><p>http://www.pathvisio.org/</p><p>VitaPad&nbsp;</p><p>Application to visualize biological pathways and map experimental data to them</p><p>http://tinyurl.com/vitapad/</p><p>Web tools for pathways</p><p>ArrayXPath&nbsp;</p><p>Mapping and visualizing microarray gene-expression data and integrated biological pathway resources using SVG</p><p>http://tinyurl.com/ArrayXPath/</p><p>GEPAT&nbsp;</p><p>Integrated analysis of transcriptome data in genomic, proteomic and metabolic contexts</p><p>http://gepat.sourceforge.net/</p><p>iPath&nbsp;</p><p>Web-based tool for the visualization, analysis and customization of pathway maps</p><p>http://pathways.embl.de/</p><p>Kegg-Based Viewer&nbsp;</p><p>KEGG-based pathway visualization tool for complex high-throughput data</p><p>http://www.g-language.org/data/marray/</p><p>MapMan&nbsp;</p><p>User-driven tool that displays large datasets onto diagrams of metabolic pathways or other processes</p><p>http://mapman.gabipd.org/web/guest/mapman</p><p>MetPA&nbsp;</p><p>Analysis and visualization of metabolomic data within the biological context of metabolic pathways</p><p>http://metpa.metabolomics.ca</p><p>Omics Viewer&nbsp;</p><p>Data mapping on BioCyc pathways (collection of 5500 pathway/genome databases)</p><p>http://www.biocyc.org/</p><p>Pathway Explorer</p><p>Interactive Java drawing tool for the construction of biological pathway diagrams in a visual way and the annotation of the components and interactions between them</p><p>http://genome.tugraz.at/pathwayexplorer/pathwayexplorer_description.shtml</p><p>Pathway projector&nbsp;</p><p>Zoomable pathway browser using KEGG atlas and Google Maps API</p><p>http://www.g-language.org/PathwayProjector/</p><p>PATIKA&nbsp;</p><p>Integrated environment composed of a central database and a visual editor, built around an extensive ontology and an integration framework</p><p>http://www.cs.bilkent.edu.tr/~patikaweb/</p><p>Reactome SkyPainter&nbsp;</p><p>Visualization of over-represented pathways and reactions from gene lists</p><p>http://www.reactome.org/skypainter-2</p><p>WikiPathways</p><p>Wiki-based, open, public platform dedicated to the curation of biological pathways by and for the scientific community</p><p>http://www.wikipathways.org/</p>]]></description>
	<dc:creator>Neel</dc:creator>
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