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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/38172?offset=40</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36857/%E2%80%9Cone-code-to-find-them-all%E2%80%9D-a-perl-tool-to-conveniently-parse-repeatmasker-output-files</guid>
	<pubDate>Mon, 04 Jun 2018 03:45:15 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36857/%E2%80%9Cone-code-to-find-them-all%E2%80%9D-a-perl-tool-to-conveniently-parse-repeatmasker-output-files</link>
	<title><![CDATA[“One code to find them all”: a perl tool to conveniently parse RepeatMasker output files]]></title>
	<description><![CDATA[One code to find them all is a set of perl scripts to extract useful information from RepeatMasker about transposable elements, retrieve their sequences and get some quantitative information.

Assemble RepeatMasker hits into complete TE copies, including LTR-retrotransposon
Retrieve corresponding TE sequences, and flanking sequences, from the local fasta files
Compute summary statistics for each TE family (number of TE copies, genome coverage...)
Ambiguous cases such as nested TE can be assembled into copies automatically or manually
Allow for working with a TE user-defined library
Allow for working with only a user-chosen set of TE families


http://doua.prabi.fr/software/one-code-to-find-them-all<p>Address of the bookmark: <a href="http://doua.prabi.fr/software/one-code-to-find-them-all" rel="nofollow">http://doua.prabi.fr/software/one-code-to-find-them-all</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27094/smash-an-alignment-free-method-to-find-and-visualise-rearrangements-between-pairs-of-dna-sequences</guid>
	<pubDate>Tue, 26 Apr 2016 12:18:49 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27094/smash-an-alignment-free-method-to-find-and-visualise-rearrangements-between-pairs-of-dna-sequences</link>
	<title><![CDATA[Smash: An alignment-free method to find and visualise rearrangements between pairs of DNA sequences]]></title>
	<description><![CDATA[<p><strong>Smash is a completely alignment-free method/tool to find and visualise genomic rearrangements</strong><span>. The detection is based on&nbsp;</span><strong>conditional exclusive compression</strong><span>, namely using a FCM (Markov model), of high context order (typically 20). For visualisation, Smash outputs a&nbsp;</span><strong>SVG image</strong><span>, with an&nbsp;</span><strong>ideogram</strong><span>output architecture, where the patterns are represented with several&nbsp;</span><strong>HSV values</strong><span>&nbsp;(only value varies). The method can perform both in small- and large-scale. Nevertheless is more directed to large-scale since that the main aim of the research is to&nbsp;</span><strong>know where the large-scale [chromosomal by chromosome] of several primates was equal/different, having at a glance a map of the entire genomes</strong><span>.</span></p><p>Address of the bookmark: <a href="http://bioinformatics.ua.pt/software/smash/" rel="nofollow">http://bioinformatics.ua.pt/software/smash/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44279/bioinformatics-training-material</guid>
	<pubDate>Sat, 18 Mar 2023 11:26:18 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44279/bioinformatics-training-material</link>
	<title><![CDATA[Bioinformatics Training Material !]]></title>
	<description><![CDATA[<p><span>Glittr</span>&nbsp;is a curated list of bioinformatics training material.<br>All material is:</p>
<ul>
<li>In a GitHub or GitLab repository</li>
<li>Free to use</li>
<li>Written in markdown or similar</li>
</ul>
<p><span>NOTE:</span>&nbsp;This list of courses is selected only based on the above criteria.<br>There are no checks on quality.</p>
<p>https://glittr.org/?per_page=25&amp;sort_by=stargazers&amp;sort_direction=desc</p><p>Address of the bookmark: <a href="https://glittr.org/?per_page=25&amp;sort_by=stargazers&amp;sort_direction=desc" rel="nofollow">https://glittr.org/?per_page=25&amp;sort_by=stargazers&amp;sort_direction=desc</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33789/i-pv-interactive-protein-sequence-visualization</guid>
	<pubDate>Mon, 03 Jul 2017 07:52:51 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33789/i-pv-interactive-protein-sequence-visualization</link>
	<title><![CDATA[I-PV: Interactive Protein Sequence Visualization]]></title>
	<description><![CDATA[<p><span>I-PV is a interactive data visualization software designed for inspection of protein sequences and mutation information. It is mainly used for Genetics and Bioinformatics. So what exactly makes it standout?</span></p>
<p><span>http://i-pv.org/ipv_rec</span></p><p>Address of the bookmark: <a href="http://i-pv.org/" rel="nofollow">http://i-pv.org/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/37049/chromomap-an-r-package-for-interactive-visualization-and-mapping-of-human-chromosomes</guid>
	<pubDate>Mon, 25 Jun 2018 17:22:24 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/37049/chromomap-an-r-package-for-interactive-visualization-and-mapping-of-human-chromosomes</link>
	<title><![CDATA[chromoMap-An R package for Interactive visualization and mapping of human chromosomes]]></title>
	<description><![CDATA[
<p>chromoMap is an R package that provides interactive, configurable and elegant graphics visualization of the human chromosomes allowing users to map chromosome elements (like genes, SNPs etc.) on the chromosome plot. It introduces a special plot viz. the "chromosome heatmap" that, in addition to mapping elements, can visualize the data associated with chromosome elements (like gene expression) in the form of heat colors which can be highly advantageous in the scientific interpretations and research work. Because of the enormous size of the chromosomes, it is impractical to visualize each element on the same plot. But chromoMap plots provide a magnified view for each of chromosome location to render additional information and visualization specific for that location. You can map thousands of genes and can view all mappings easily. Users can investigate the detailed information about the mappings (like gene names or total genes mapped on a location) or can view the magnified single or double stranded view of the chromosome at a location showing each mapped element in sequential order (You will see in the demos below). Not ony that, the plots can be saved as HTML documents that can be customized and shared easily. In addition, you can include them in R Markdown or in R Shiny applications.</p>

<p>https://cran.r-project.org/web/packages/chromoMap/index.html</p>
]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43243/interactive-bioinformatics-resources</guid>
	<pubDate>Thu, 12 Aug 2021 00:09:00 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43243/interactive-bioinformatics-resources</link>
	<title><![CDATA[Interactive Bioinformatics Resources !]]></title>
	<description><![CDATA[<p>Learn how to use bioinformatics tools right from your browser.<br>Everything runs in a sandbox, so you can experiment all you want.</p>
<p>More at sandbox.bio</p><p>Address of the bookmark: <a href="http://sandbox.bio" rel="nofollow">http://sandbox.bio</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35764/generate-interactive-codon-usage-plots</guid>
	<pubDate>Wed, 28 Feb 2018 03:47:40 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35764/generate-interactive-codon-usage-plots</link>
	<title><![CDATA[Generate interactive codon usage plots]]></title>
	<description><![CDATA[<p>Generate interactive codon usage plots as used at&nbsp;<a href="http://ensembl.lepbase.org/">ensembl.lepbase.org</a>. The input file format can be generated from an&nbsp;<a href="http://ensembl.org/">Ensembl</a>&nbsp;database using the&nbsp;<code>export_json.pl</code>&nbsp;script from the&nbsp;<a href="http://easy-import.readme.io/">easy-import</a>&nbsp;pipeline.</p>
<p><a href="http://content.lepbase.org/pages/annotations/codon-usage.html?assembly=Heliconius_melpomene_Hmel2">live demo</a></p><p>Address of the bookmark: <a href="https://github.com/rjchallis/codon-usage" rel="nofollow">https://github.com/rjchallis/codon-usage</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40594/gfaviz-flexible-and-interactive-visualization-of-gfa-sequence-graphs</guid>
	<pubDate>Thu, 23 Jan 2020 07:33:46 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40594/gfaviz-flexible-and-interactive-visualization-of-gfa-sequence-graphs</link>
	<title><![CDATA[GfaViz: flexible and interactive visualization of GFA sequence graphs]]></title>
	<description><![CDATA[<p><span>GFA (Graphical Fragment Assembly) is an emerging standard format for representing sequence graphs. Although it was originally conceived as a format for sequence assembly (hence the name), and this remains its core application, it is more general, and able to represent many different types of sequence graphs, including scaffolding graphs, alignment graphs, variant graphs and splicing graphs.</span></p><p>Address of the bookmark: <a href="https://github.com/ggonnella/gfaviz" rel="nofollow">https://github.com/ggonnella/gfaviz</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42155/clustergrammer-is-a-web-based-tool-for-visualizing-high-dimensional-data-as-an-interactive-and-shareable-hierarchically-clustered-heatmap</guid>
	<pubDate>Sun, 23 Aug 2020 19:30:17 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42155/clustergrammer-is-a-web-based-tool-for-visualizing-high-dimensional-data-as-an-interactive-and-shareable-hierarchically-clustered-heatmap</link>
	<title><![CDATA[Clustergrammer is a web-based tool for visualizing high-dimensional data as an interactive and shareable hierarchically clustered heatmap]]></title>
	<description><![CDATA[<p><span>Clustergrammer is a web-based tool for visualizing high-dimensional data (e.g. a matrix) as an interactive and shareable hierarchically clustered heatmap. Clustergrammer's front end (</span><a href="http://clustergrammer.readthedocs.io/clustergrammer_js.html#clustergrammer-js">Clustergrammer-JS</a><span>) is built using&nbsp;</span><a href="https://d3js.org/">D3.js</a><span>&nbsp;and its back-end (</span><a href="http://clustergrammer.readthedocs.io/clustergrammer_py.html#clustergrammer-py">Clustergrammer-PY</a><span>) is built using Python. Clustergrammer produces highly interactive visualizations that enable intuitive exploration of high-dimensional data and has several biology-specific features (e.g. enrichment analysis, see&nbsp;</span><a href="http://clustergrammer.readthedocs.io/biology_specific_features.html#biology-specific-features">Biology-Specific Features</a><span>) to facilitate the exploration of gene-level biological data.&nbsp;</span></p><p>Address of the bookmark: <a href="https://github.com/MaayanLab/clustergrammer" rel="nofollow">https://github.com/MaayanLab/clustergrammer</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33011/grinder-biogrinder-a-versatile-omics-shotgun-and-amplicon-sequencing-read-simulator</guid>
	<pubDate>Wed, 24 May 2017 08:41:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33011/grinder-biogrinder-a-versatile-omics-shotgun-and-amplicon-sequencing-read-simulator</link>
	<title><![CDATA[Grinder / Biogrinder - A versatile omics shotgun and amplicon sequencing read simulator]]></title>
	<description><![CDATA[<p><span>Grinder is a versatile program to create random shotgun and amplicon sequence libraries based on DNA, RNA or proteic reference sequences provided in a FASTA file. </span></p>
<p><span>Grinder can produce genomic, metagenomic, transcriptomic, metatranscriptomic, proteomic, metaproteomic shotgun and amplicon datasets from current sequencing technologies such as Sanger, 454, Illumina. These simulated datasets can be used to test the accuracy of bioinformatic tools under specific hypothesis, e.g. with or without sequencing errors, or with low or high community diversity. Grinder may also be used to help decide between alternative sequencing methods for a sequence-based project, e.g. should the library be paired-end or not, how many reads should be sequenced.</span></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/biogrinder/files/biogrinder/" rel="nofollow">https://sourceforge.net/projects/biogrinder/files/biogrinder/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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