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<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/8504?offset=1550</link>
	<atom:link href="https://bioinformaticsonline.com/related/8504?offset=1550" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/40953/explore-taxdump-files</guid>
	<pubDate>Sat, 08 Feb 2020 04:44:55 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/40953/explore-taxdump-files</link>
	<title><![CDATA[Explore taxdump files !]]></title>
	<description><![CDATA[<pre>This is an extract of taxdump-readme.txt to be found at 
ftp://ftp.ncbi.nih.gov/pub/taxonomy/

The content of the archive
--------------------------

It may look like this:

delnodes.dmp
division.dmp
gencode.dmp
merged.dmp
names.dmp
nodes.dmp
readme.txt

The readme.txt file gives a brief description of *.dmp files. These files
contain taxonomic information and are briefly described below. Each of the
files store one record in the single line that are delimited by "\t|\n"
(tab, vertical bar, and newline) characters. Each record consists of one 
or more fields delimited by "\t|\t" (tab, vertical bar, and tab) characters.
The brief description of field position and meaning for each file follows.

nodes.dmp
---------

This file represents taxonomy nodes. The description for each node includes 
the following fields:

	tax_id					-- node id in GenBank taxonomy database
 	parent tax_id				-- parent node id in GenBank taxonomy database
 	rank					-- rank of this node (superkingdom, kingdom, ...) 
 	embl code				-- locus-name prefix; not unique
 	division id				-- see division.dmp file
 	inherited div flag  (1 or 0)		-- 1 if node inherits division from parent
 	genetic code id				-- see gencode.dmp file
 	inherited GC  flag  (1 or 0)		-- 1 if node inherits genetic code from parent
 	mitochondrial genetic code id		-- see gencode.dmp file
 	inherited MGC flag  (1 or 0)		-- 1 if node inherits mitochondrial gencode from parent
 	GenBank hidden flag (1 or 0)            -- 1 if name is suppressed in GenBank entry lineage
 	hidden subtree root flag (1 or 0)       -- 1 if this subtree has no sequence data yet
 	comments				-- free-text comments and citations

names.dmp
---------
Taxonomy names file has these fields:

	tax_id					-- the id of node associated with this name
	name_txt				-- name itself
	unique name				-- the unique variant of this name if name not unique
	name class				-- (synonym, common name, ...)

division.dmp
------------
Divisions file has these fields:
	division id				-- taxonomy database division id
	division cde				-- GenBank division code (three characters)
	division name				-- e.g. BCT, PLN, VRT, MAM, PRI...
	comments

gencode.dmp
-----------
Genetic codes file:

	genetic code id				-- GenBank genetic code id
	abbreviation				-- genetic code name abbreviation
	name					-- genetic code name
	cde					-- translation table for this genetic code
	starts					-- start codons for this genetic code

delnodes.dmp
------------
Deleted nodes (nodes that existed but were deleted) file field:

	tax_id					-- deleted node id

merged.dmp
----------
Merged nodes file fields:

	old_tax_id                              -- id of nodes which has been merged
	new_tax_id                              -- id of nodes which is result of merging

</pre>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/11195/ncbi-gene-screencast</guid>
	<pubDate>Fri, 30 May 2014 06:21:18 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/11195/ncbi-gene-screencast</link>
	<title><![CDATA[NCBI Gene Screencast]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/WyFIf7YdM8A" frameborder="0" allowfullscreen></iframe>A short walkthrough of the NCBI Gene page]]></description>
	
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/38226/ncbi-to-assist-in-virus-hunting-data-science-hackathon</guid>
	<pubDate>Thu, 15 Nov 2018 12:55:01 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/38226/ncbi-to-assist-in-virus-hunting-data-science-hackathon</link>
	<title><![CDATA[NCBI to assist in Virus Hunting Data Science Hackathon]]></title>
	<description><![CDATA[<p>NCBI Hackathon are pleased to announce the second installment of the&nbsp;<a href="https://ncbiinsights.ncbi.nlm.nih.gov/2017/11/30/ncbi-southern-california-genomics-hackathon-january/" target="_blank">SoCal Bioinformatics Hackathon</a>. From January 9-11, 2019, the&nbsp;<a href="https://www.ncbi.nlm.nih.gov/" target="_blank">NCBI</a>&nbsp;will help run a bioinformatics hackathon in Southern California hosted by the&nbsp;<a href="http://www.csrc.sdsu.edu/" target="_blank">Computational Sciences Research Center</a>&nbsp;at&nbsp;<a href="http://www.sdsu.edu/" target="_blank">San Diego State University</a>!</p><p><span>NCBI Hackathon</span>&nbsp;specifically looking for folks who have experience in computational virus hunting or adjacent fields to identify known, taxonomically-definable and novel viruses from a few hundred thousand metagenomic datasets that we&rsquo;ll put on cloud infrastructure. This event is for researchers, including students and postdocs, who are already engaged in the use of bioinformatics data or in the development of pipelines for virological analyses from high-throughput experiments. If this describes you, please&nbsp;<a href="https://goo.gl/forms/kDnSG0IAZD62XQRe2" target="_blank">apply</a>! The event is open to anyone selected for the hackathon and willing to travel to SDSU (see below).</p><p>https://ncbiinsights.ncbi.nlm.nih.gov/2018/11/09/ncbi-sdsu-virus-hunting-data-science-hackathon-january-2019/</p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/41956/blast-on-docker-google-cloud-amazon-cloud</guid>
	<pubDate>Thu, 09 Jul 2020 02:57:11 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/41956/blast-on-docker-google-cloud-amazon-cloud</link>
	<title><![CDATA[Blast on Docker, Google Cloud, Amazon Cloud]]></title>
	<description><![CDATA[<p>As announced in a&nbsp;<a href="https://ncbiinsights.ncbi.nlm.nih.gov/2019/07/16/the-blast-programs-and-databases-are-available-in-docker-and-cloud-ready/" target="_blank">previous post</a>, we offer a&nbsp;<a href="https://www.docker.com/" target="_blank">Docker</a>&nbsp;version of NCBI BLAST+ that you can use locally or on the&nbsp;<a href="https://cloud.google.com/" target="_blank">Google Cloud</a>&nbsp;where we have pre-loaded BLAST databases.&nbsp; We are happy to announce that the same functionality is now available on the&nbsp;<a href="https://aws.amazon.com/" target="_blank">Amazon Cloud</a>.&nbsp; In addition, we now offer 23 different BLAST databases on each cloud platform.<span style="text-decoration: underline;"></span><span style="text-decoration: underline;"></span></p><p>As mentioned before, working with BLAST+ in Docker and the cloud has several advantages:<span style="text-decoration: underline;"></span><span style="text-decoration: underline;"></span></p><ul>
<li>Docker manages installation and maintenance of the BLAST programs and databases.<span style="text-decoration: underline;"></span><span style="text-decoration: underline;"></span></li>
<li>Docker makes it is easier to integrate BLAST with other tools in your pipelines.<span style="text-decoration: underline;"></span><span style="text-decoration: underline;"></span></li>
<li>NCBI BLAST databases are pre-loaded now on the both the&nbsp;<a href="https://cloud.google.com/" target="_blank" title="Follow link">Google Cloud</a>&nbsp;and&nbsp;<a href="https://aws.amazon.com/" target="_blank" title="Follow link">Amazon Cloud</a>, providing fast access.<span style="text-decoration: underline;"></span><span style="text-decoration: underline;"></span></li>
</ul><p>You can also use the BLAST+ Docker image on any Docker-enabled platform, such as another cloud platform or on your local computer.<span style="text-decoration: underline;"></span><span style="text-decoration: underline;"></span></p><p>See the&nbsp;&nbsp;<a href="https://github.com/ncbi/blast_plus_docs" target="_blank" title="Follow link">BLAST+ in the Cloud</a>&nbsp;and&nbsp;&nbsp;<a href="https://github.com/ncbi/docker/wiki/Getting-BLAST-databases" target="_blank" title="Follow link">database information</a>&nbsp;documentation to get started.<span style="text-decoration: underline;"></span><span style="text-decoration: underline;"></span></p><p>If you have any questions, please email us at&nbsp;blast-help@ncbi.nlm.nih.gov</p><p>Source:<span>Dave Arndt</span></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/8481/des-higgins-visualizing-multiple-sequence-alignments</guid>
	<pubDate>Wed, 26 Feb 2014 00:50:08 -0600</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/8481/des-higgins-visualizing-multiple-sequence-alignments</link>
	<title><![CDATA[Des Higgins: Visualizing Multiple Sequence Alignments]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/IQkOK3dsWs4" frameborder="0" allowfullscreen></iframe>Copyright Broad Institute, 2013. All rights reserved.
Des Higgins (http://www.bioinf.ucd.ie) gives a very entertaining introduction to the visualization of multiple sequence alignment, and to his widely-used Clustal tool. He highlights the emerging challenge of managing alignments with a very large number of sequences, and presents several approaches to this challenge, including faster algorithms and abstract views of clusters of alignments. This talk was presented at VIZBI 2011, an international conference series on visualizing biological data (http://www.vizbi.org) funded by NIH & EMBO.

For information about data visualization efforts at the Broad Institute, please visit:
http://www.broadinstitute.org/node/1363/]]></description>
	
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35896/phylographer-graph-visualization-tool</guid>
	<pubDate>Wed, 07 Mar 2018 18:11:25 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35896/phylographer-graph-visualization-tool</link>
	<title><![CDATA[PhyloGrapher - Graph Visualization Tool]]></title>
	<description><![CDATA[<p><strong>PhyloGrapher</strong><span>&nbsp;is a program designed to visualize and study evolutionary relationships within families of homologous genes or proteins (elements).&nbsp;</span><strong>PhyloGrapher</strong><span>&nbsp;is a drawing tool that generates custom graphs for a given set of elements. In general, it is possible to use&nbsp;</span><strong>PhyloGrapher</strong><span>&nbsp;to visualize any type of relations between elements.&nbsp;</span></p>
<p><span>https://www.youtube.com/watch?v=WgufqYMHCvM</span></p><p>Address of the bookmark: <a href="http://www.atgc.org/PhyloGrapher/PhyloGrapher_Welcome.html" rel="nofollow">http://www.atgc.org/PhyloGrapher/PhyloGrapher_Welcome.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36905/d-genies-a-tool-for-dotplot-large-genomes-in-an-interactive-efficient-and-simple-way</guid>
	<pubDate>Mon, 11 Jun 2018 09:41:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36905/d-genies-a-tool-for-dotplot-large-genomes-in-an-interactive-efficient-and-simple-way</link>
	<title><![CDATA[D-GENIES: A tool for Dotplot large Genomes in an Interactive, Efficient and Simple way]]></title>
	<description><![CDATA[D-GENIES – for Dotplot large Genomes in an Interactive, Efficient and Simple way – is an online tool designed to compare two genomes. It supports large genome and you can interact with the dot plot to improve the visualisation.

We use minimap version 2 to align the two genomes. Then, the PAF file is parsed and plotted into an interactive plot written with d3.js library.

D-Genies also allows to display dot plots from other aligners by uploading their PAF or MAF alignment file.

http://dgenies.toulouse.inra.fr/<p>Address of the bookmark: <a href="http://dgenies.toulouse.inra.fr/" rel="nofollow">http://dgenies.toulouse.inra.fr/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38577/genoviz-visualization-software-for-genomics</guid>
	<pubDate>Wed, 02 Jan 2019 04:07:57 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38577/genoviz-visualization-software-for-genomics</link>
	<title><![CDATA[GenoViz: Visualization software for genomics]]></title>
	<description><![CDATA[<p><span>GenoViz provides software applications and re-usable components for data visualization and data sharing in genomics. Our flagship product is Integrated Genome Browser (IGB).</span><br><br><span>For more information about IGB, visit&nbsp;</span><a href="http://bioviz.org/" target="_blank">http://bioviz.org<span></span></a><span>.</span><br><br><span>Source code for the project was hosted here for many years. In 2014, we moved to a new git repository at&nbsp;</span><a href="http://www.bitbucket.org/lorainelab/integrated-genome-browser" target="_blank">http://www.bitbucket.org/lorainelab/integrated-genome-browser<span></span></a><span>. We are still using SourceForge to distribute new releases of IGB as compiled code (igb.zip) you can use to run IGB on your computer.&nbsp;</span><br><br><span>If you have questions, feel free to get in touch. Contact project head Ann Loraine (</span><a href="mailto:aloraine@uncc.edu" target="_blank">aloraine@uncc.edu<span></span></a><span>) or lead developer David Norris (</span><a href="mailto:dcnorris@uncc.edu" target="_blank">dcnorris@uncc.edu<span></span></a><span>&gt;).</span></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/genoviz/" rel="nofollow">https://sourceforge.net/projects/genoviz/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39917/chromomap-an-r-package-for-interactive-visualization-and-annotation-of-chromosomes</guid>
	<pubDate>Sat, 07 Sep 2019 10:45:31 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39917/chromomap-an-r-package-for-interactive-visualization-and-annotation-of-chromosomes</link>
	<title><![CDATA[chromoMap-An R package for Interactive Visualization and Annotation of Chromosomes]]></title>
	<description><![CDATA[<p><code>chromoMap</code>&nbsp;provides interactive, configurable and elegant graphics visualization of chromosomes or chromosomal regions allowing users to map chromosome elements (like genes,SNPs etc.) on the chromosome plot.Each chromosome is composed of loci(representing a specific range determined based on chromosome length) that, on hover, shows details about the annotations in that locus range. The plots can be saved as HTML documents that can be shared easily. In addition, you can include them in R Markdown or in R Shiny applications.</p>
<p>Some of the prominent features of the package are:</p>
<ul>
<li>visualizing polyploidy simultaneously on the same plot.</li>
<li>annotating groups of elements as distinct colors.</li>
<li>creating chromosome heatmaps.</li>
<li>adjusting chromosome range or visualizing chromosome regions such as genes</li>
<li>adding labels to the plot</li>
<li>adding hyperlinks to each element</li>
</ul><p>Address of the bookmark: <a href="https://cran.r-project.org/web/packages/chromoMap/vignettes/chromoMap.html" rel="nofollow">https://cran.r-project.org/web/packages/chromoMap/vignettes/chromoMap.html</a></p>]]></description>
	<dc:creator>Jit</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>
</item>

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