<?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/36360?</link>
	<atom:link href="https://bioinformaticsonline.com/related/36360?" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40298/environment-for-tree-exploration-ete-is-a-python-programming-toolkit-that-assists-in-the-recontruction-manipulation-analysis-and-visualization-of-phylogenetic-trees</guid>
	<pubDate>Wed, 27 Nov 2019 05:32:33 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40298/environment-for-tree-exploration-ete-is-a-python-programming-toolkit-that-assists-in-the-recontruction-manipulation-analysis-and-visualization-of-phylogenetic-trees</link>
	<title><![CDATA[Environment for Tree Exploration (ETE) is a Python programming toolkit that assists in the recontruction, manipulation, analysis and visualization of phylogenetic trees]]></title>
	<description><![CDATA[<p><span>The Environment for Tree Exploration (ETE) is a Python programming toolkit that assists in the recontruction, manipulation, analysis and visualization of phylogenetic trees (although clustering trees or any other tree-like data structure are also supported).</span></p>
<p><span>Other tools</span></p>
<p><span><a href="https://github.com/shenwei356/taxonkit">https://github.com/shenwei356/taxonkit</a></span></p>
<p>&nbsp;</p>
<ul>
<li>ETE, version:&nbsp;<a href="https://pypi.org/project/ete3/3.1.1/">3.1.1</a></li>
<li>BioPython, version:&nbsp;<a href="https://pypi.org/project/biopython/1.73/">1.73</a></li>
<li>taxadb, version:&nbsp;<a href="https://pypi.org/project/taxadb/0.9.0">0.10.1</a></li>
<li>TaxonKit, version:&nbsp;<a href="https://github.com/shenwei356/taxonkit/releases/tag/0.10.1">0.5.0</a></li>
</ul><p>Address of the bookmark: <a href="https://pypi.org/project/ete3/3.1.1/" rel="nofollow">https://pypi.org/project/ete3/3.1.1/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/36605/hello-python-world</guid>
	<pubDate>Mon, 14 May 2018 16:41:01 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/36605/hello-python-world</link>
	<title><![CDATA[Hello Python World !]]></title>
	<description><![CDATA[<p>As I mentioned earlier, I will keep on posting one Python script per day to introduce you to Python programming. Whether you are an experienced programmer or not, this tutorial is intended for everyone who wishes to learn the Python programming language.</p><p>Python is a very simple language, and has a very straightforward syntax. The simplest directive in Python is the "print" directive - it simply prints out a line (and also includes a newline).</p><p>Create a file Hello.py</p><blockquote><p>print("Hello, Python World !.")</p></blockquote><p>Run</p><p>python3 Hello.py</p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/23160/opencpu</guid>
	<pubDate>Sun, 05 Jul 2015 18:34:46 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/23160/opencpu</link>
	<title><![CDATA[OpenCPU]]></title>
	<description><![CDATA[<p>OpenCPU is a system for embedded scientific computing and reproducible research. The OpenCPU server provides a reliable and interoperable <a href="https://www.opencpu.org/api.html">HTTP API</a> for data analysis based on R.</p><p>The OpenCPU <a href="https://www.opencpu.org/jslib.html">JavaScript client library</a> provides the most seamless integration of R and JavaScript available today.</p><p>OpenCPU uses standard R packaging to develop, ship and deploy web applications. Several open source <a href="https://www.opencpu.org/apps.html">example apps</a> are available from Github.</p><p>Installing your own OpenCPU server is <a href="https://www.opencpu.org/download.html">super easy</a> and only takes a few minutes.</p><p>More at https://www.opencpu.org/</p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35565/circosjs-d3-library-to-build-circular-graphs</guid>
	<pubDate>Tue, 13 Feb 2018 06:57:32 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35565/circosjs-d3-library-to-build-circular-graphs</link>
	<title><![CDATA[circosJS: d3 library to build circular graphs]]></title>
	<description><![CDATA[<p>Circos is a javascript library to easily build interactive graphs in a circular layout. It's based on&nbsp;<a href="https://d3js.org/">d3.js</a>. It aims to be a javascript version of the&nbsp;<a href="http://circos.ca/">Circos</a>&nbsp;software.</p>
<p>You should consider using Circos to show:</p>
<ul>
<li>relationships between entities</li>
<li>periodical data</li>
</ul><p>Address of the bookmark: <a href="https://github.com/nicgirault/circosJS" rel="nofollow">https://github.com/nicgirault/circosJS</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38646/visnetwork-an-r-package-for-network-visualization-using-visjs-javascript-library</guid>
	<pubDate>Wed, 09 Jan 2019 11:00:32 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38646/visnetwork-an-r-package-for-network-visualization-using-visjs-javascript-library</link>
	<title><![CDATA[visNetwork: an R package for network visualization, using vis.js javascript library]]></title>
	<description><![CDATA[<div id="introduction">
<p><strong>visNetwork</strong>&nbsp;is an R package for network visualization, using&nbsp;<strong>vis.js</strong>&nbsp;javascript library (<a href="http://visjs.org/">http://visjs.org/</a>). All remarks and bugs are welcome on github :&nbsp;<a href="https://github.com/datastorm-open/visNetwork">https://github.com/datastorm-open/visNetwork</a>.</p>
</div>
<div id="features">
<h2>Features</h2>
<p>Based on&nbsp;<a href="http://www.htmlwidgets.org/">htmlwidgets</a>, so :</p>
<ul>
<li>compatible with&nbsp;<a href="http://shiny.rstudio.com/">shiny</a>, R Markdown documents, and RStudio viewer</li>
</ul>
<p>The package proposes all the features available in&nbsp;<strong>vis.js</strong>&nbsp;API, and even more with special features for R :</p>
<ul>
<li>easy to use</li>
<li>custom shapes, styles, colors, sizes, &hellip;</li>
<li>works smooth on any modern browser for up to a few thousand nodes and edges</li>
<li>interactivity controls (highlight, collapsed nodes, selection, zoom, physics, movement of nodes, tooltip, events, &hellip;)</li>
<li>visualize&nbsp;<code>rpart</code>&nbsp;tree</li>
<li></li>
</ul>
</div><p>Address of the bookmark: <a href="https://datastorm-open.github.io/visNetwork/" rel="nofollow">https://datastorm-open.github.io/visNetwork/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43698/mimilook-a-phylogenetic-workflow-for-detection-of-gene-acquisition-in-major-orthologous-groups-of-megavirales</guid>
	<pubDate>Mon, 10 Jan 2022 06:32:22 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43698/mimilook-a-phylogenetic-workflow-for-detection-of-gene-acquisition-in-major-orthologous-groups-of-megavirales</link>
	<title><![CDATA[MimiLook: A Phylogenetic Workflow for Detection of Gene Acquisition in Major Orthologous Groups of Megavirales]]></title>
	<description><![CDATA[<p><span>This tool detects statistically validated events of gene acquisitions with the help of the T-REX algorithm by comparing individual gene tree with NCBI species tree. In between the steps, the workflow decides about handling paralogs, filtering outputs, identifying Megavirale specific OGs, detection of HGTs, along with retrieval of information about those OGs that are monophyletic with organisms from cellular domains of life.&nbsp;</span></p>
<p>https://www.readcube.com/articles/10.3390%2Fv9040072</p><p>Address of the bookmark: <a href="https://pubmed.ncbi.nlm.nih.gov/28387730/" rel="nofollow">https://pubmed.ncbi.nlm.nih.gov/28387730/</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34569/ksnp30-snp-detection-and-phylogenetic-analysis-of-genomes-without-genome-alignment-or-reference-genome</guid>
	<pubDate>Fri, 08 Dec 2017 16:48:40 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34569/ksnp30-snp-detection-and-phylogenetic-analysis-of-genomes-without-genome-alignment-or-reference-genome</link>
	<title><![CDATA[kSNP3.0: SNP detection and phylogenetic analysis of genomes without genome alignment or reference genome]]></title>
	<description><![CDATA[<p><span>Sept. 20, 2017 Version 3.1 released. Major upgrade. Version 3.1 fixes the problems with SNP annotation that arose when NCBI discontinued use of GI numbers. Please read carefully the Preface (page 3) and the File of annotated genomes section (pages 9-10) in the version 3.1 User Guide. Thanks to Tom Slezak for revsing the get_genbank_file3 script and to Tod Stuber (USDA) for testing version 3.1 even though he doesn't need the annotation feature. All users are encouraged to upgrade to version 3.1.&nbsp;<br></span></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/ksnp/files/" rel="nofollow">https://sourceforge.net/projects/ksnp/files/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44468/orthoflow-workflow-for-phylogenetic-inference-of-genome-scale-datasets-of-protein-coding-genes</guid>
	<pubDate>Wed, 21 Feb 2024 06:13:08 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44468/orthoflow-workflow-for-phylogenetic-inference-of-genome-scale-datasets-of-protein-coding-genes</link>
	<title><![CDATA[Orthoflow: workflow for phylogenetic inference of genome-scale datasets of protein-coding genes]]></title>
	<description><![CDATA[<p><span>Orthoflow is a workflow for phylogenetic inference of genome-scale datasets of protein-coding genes. Our goal was to make it straightforward to work from a combination of input sources including annotated contigs in Genbank format and FASTA files containing CDSs. It uses several state of the art inference methods for orthology inference, either based on HMM profiles or de novo inference of orthogroups. Through the use of OrthoSNAP, many additional ortholog alignments can be generated from multi-copy gene families. For phylogenetic inference, users can choose a supermatrix approach and/or gene tree inference followed by supertree reconstruction. Users can specify a range of alignment filtering settings to retain high-quality alignments for phylogenetic inference. The workflow produces a detailed report that, in addition to the phylogenetic results, includes a range of diagnostics to verify the quality of the results.</span></p><p>Address of the bookmark: <a href="https://github.com/rbturnbull/orthoflow" rel="nofollow">https://github.com/rbturnbull/orthoflow</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/1467/biopython-cookbook</guid>
	<pubDate>Thu, 08 Aug 2013 06:43:02 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/1467/biopython-cookbook</link>
	<title><![CDATA[BioPython Cookbook]]></title>
	<description><![CDATA[<p>If you are planning to start learning BioPython ( it does not bite but&nbsp;swallow :P just kidding) then this online cookbook will be really helpful for you.</p><p>http://biopython.org/DIST/docs/tutorial/Tutorial.html</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/17926/orange-bioinformatics-2534</guid>
	<pubDate>Mon, 06 Oct 2014 12:51:37 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/17926/orange-bioinformatics-2534</link>
	<title><![CDATA[Orange-Bioinformatics 2.5.34]]></title>
	<description><![CDATA[<p>Orange Bioinformatics extends <a href="http://orange.biolab.si/">Orange</a>, a data mining software package, with common functionality for bioinformatics. The provided functionality can be accessed as a Python library or through a visual programming interface (Orange Canvas). The latter is also suitable for non-programmers.</p>
<p>Orange Bioinformatics provides access to publicly available data, like GEO data sets, Biomart, GO, KEGG, Atlas, ArrayExpress, and PIPAx database. As for the analytics, there is gene selection, quality control, scoring distances between experiments with multiple factors. All features can be combined with powerful visualization, network exploration and data mining techniques from the Orange data mining framework.</p><p>Address of the bookmark: <a href="https://pypi.python.org/pypi/Orange-Bioinformatics/2.5.34" rel="nofollow">https://pypi.python.org/pypi/Orange-Bioinformatics/2.5.34</a></p>]]></description>
	<dc:creator>Robert M Willioms</dc:creator>
</item>

</channel>
</rss>