<?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/14801?offset=20</link>
	<atom:link href="https://bioinformaticsonline.com/related/14801?offset=20" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	
<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/38551/gupta-lab</guid>
  <pubDate>Sat, 29 Dec 2018 13:18:31 -0600</pubDate>
  <link></link>
  <title><![CDATA[Gupta Lab]]></title>
  <description><![CDATA[
<p>Work include (i) understanding the evolutionary relationships among different prokaryotic and eukaryotic organisms; (ii) Understanding the cellular functions of these lineage-specific signature proteins as well as lineage-specific conserved inserts and deletions in important housekeeping proteins by genetic and biochemical studies; (iii) Development of novel diagnostic methods (PCR based and immunological) for identification of different groups of organisms based upon these signature proteins and conserved indels; (iv) The use of these lineage-specific probes with predicitive ability to identify/explore the presence of different groups of organisms in metagenomic sequences from various environments.</p>

<p>https://fhs.mcmaster.ca/gupta-lab/index.html</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/19792/irishgrid-irish-grid-mapping-system</guid>
	<pubDate>Fri, 26 Dec 2014 07:53:24 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/19792/irishgrid-irish-grid-mapping-system</link>
	<title><![CDATA[irishgrid: Irish Grid Mapping System]]></title>
	<description><![CDATA[<p>Perl module for creating geographic 10km-square maps using either SVG or PNG (with GD library) output format.</p>
<p>Originally design to map the location of objects in a 10 km map IrishGrid includes:</p>
<ul>
<li>native support of the Irish Grid System (see <a href="http://www.osi.ie/">http://www.osi.ie/</a>)</li>
<li>optimize for speed (there's as less as possible data to conversion)</li>
<li>customized color functions</li>
</ul>
<p>https://code.google.com/p/irishgrid/downloads/detail?name=irishgrid.pl</p><p>Address of the bookmark: <a href="https://code.google.com/p/irishgrid/" rel="nofollow">https://code.google.com/p/irishgrid/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29487/shinyheatmap</guid>
	<pubDate>Fri, 21 Oct 2016 05:12:11 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29487/shinyheatmap</link>
	<title><![CDATA[Shinyheatmap]]></title>
	<description><![CDATA[<p><span>Background: Transcriptomics, metabolomics, metagenomics, and other various next-generation sequencing (-omics) fields are known for their production of large datasets. Visualizing such big data has posed technical challenges in biology, both in terms of available computational resources as well as programming acumen. Since heatmaps are used to depict high-dimensional numerical data as a colored grid of cells, efficiency and speed have often proven to be critical considerations in the process of successfully converting data into graphics. For example, rendering interactive heatmaps from large input datasets (e.g., 100k+ rows) has been computationally infeasible on both desktop computers and web browsers. In addition to memory requirements, programming skills and knowledge have frequently been barriers-to-entry for creating highly customizable heatmaps. Results: We propose shinyheatmap: an advanced user-friendly heatmap software suite capable of efficiently creating highly customizable static and interactive biological heatmaps in a web browser. shinyheatmap is a low memory footprint program, making it particularly well-suited for the interactive visualization of extremely large datasets that cannot typically be computed in-memory due to size restrictions. Conclusions: shinyheatmap is hosted online as a freely available web server with an intuitive graphical user interface: http://shinyheatmap.com. The methods are implemented in R, and are available as part of the shinyheatmap project at: https://github.com/Bohdan-Khomtchouk/shinyheatmap.</span></p>
<p><span>More at&nbsp;http://biorxiv.org/content/early/2016/09/21/076463&nbsp;</span></p><p>Address of the bookmark: <a href="http://shinyheatmap.com/" rel="nofollow">http://shinyheatmap.com/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41694/mercator-multiple-whole-genome-orthology-map-construction</guid>
	<pubDate>Tue, 19 May 2020 16:46:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41694/mercator-multiple-whole-genome-orthology-map-construction</link>
	<title><![CDATA[Mercator: Multiple Whole-Genome Orthology Map Construction]]></title>
	<description><![CDATA[<p><span>Whole-genome homology maps attempt to identify the evolutionary relationships between and within multiple genomes. The term "syntenic" is often used to describe regions of multiple genomes that are believed to have evolved from the same region in an ancestral genome. However, it has been pointed out that this use of the term is incorrect (</span><a href="https://www.biostat.wisc.edu/~cdewey/mercator/#refSynteny">Passarge et al. 1999</a><span>) and thus we will use the terms "homologous", "orthologous", and "paralogous" instead. Ideally, given K genomes, we would like to identify all orthologous genomic regions as well as paralogous regions within each genome and hypothetical ancestral genome. Maps listing these relationships are extremely valuable to researchers performing comparative analyses of genomic sequence. Here we present our initial work in the form a program called&nbsp;</span><em>Mercator</em><span>&nbsp;that constructs orthology maps between multiple whole genomes.</span></p><p>Address of the bookmark: <a href="https://www.biostat.wisc.edu/~cdewey/mercator/" rel="nofollow">https://www.biostat.wisc.edu/~cdewey/mercator/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44182/collection-of-graph-visualization-tools</guid>
	<pubDate>Wed, 25 Jan 2023 02:57:42 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44182/collection-of-graph-visualization-tools</link>
	<title><![CDATA[Collection of Graph Visualization tools !]]></title>
	<description><![CDATA[<p>Standard approaches to genome inference and analysis relate sequences to a single linear reference genome. This is efficient but has a fundamental problem: Differences from this reference are hard to observe and describe in a coherent way. Variation and sequence are separated.</p>
<p><a href="https://pangenome.github.io/images/genomic-vs-pangenomic-analysis.png"><img src="https://pangenome.github.io/images/genomic-vs-pangenomic-analysis.png" alt="image" width="45%" style="border: 0px; border: 0px;"></a><span>&nbsp;</span><a href="https://pangenome.github.io/images/genomic-vs-pangenomic-models.png"><img src="https://pangenome.github.io/images/genomic-vs-pangenomic-models.png" alt="image" width="54%" style="border: 0px; border: 0px;"></a></p>
<p><a href="https://fungidb.org/fungidb/app/downloads/Current_Release/GultimumBR650/" target="_blank">https://fungidb.org/fungidb/app/downloads/Current_Release/GultimumBR650/</a></p><p>Address of the bookmark: <a href="https://pangenome.github.io/" rel="nofollow">https://pangenome.github.io/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/10659/gps-dna-tracking-university-of-sheffield</guid>
	<pubDate>Sat, 10 May 2014 04:33:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/10659/gps-dna-tracking-university-of-sheffield</link>
	<title><![CDATA[GPS DNA tracking - University of Sheffield]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/Aap-s1kle4Q" frameborder="0" allowfullscreen></iframe>University of Sheffield geneticist and bioinformatics expert Dr Eran Elhaik demonstrates the power of his new DNA research, which allows people to discover their genetic homeland from 1000 years ago. Find out more about our biological research here http://www.sheffield.ac.uk/aps]]></description>
	
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/26390/przeworski-lab</guid>
  <pubDate>Mon, 15 Feb 2016 05:41:54 -0600</pubDate>
  <link></link>
  <title><![CDATA[Przeworski lab]]></title>
  <description><![CDATA[
<p>Genetic differences among individuals reflect the combined effects of mutation, recombination, population history and natural selection. As a result, studies of natural variation can provide important insights into evolutionary and genetic mechanisms: as examples, DNA sequence conservation among distantly related species can help identify functional roles too subtle to be detected in lab settings, while analyses of population variation allow for inferences about events that are too infrequent to be measured directly. Our research employs this general approach to learn about the dynamics of adaptation and the determinants of recombination and mutation, in humans and in other species.</p>

<p>More at http://przeworski.c2b2.columbia.edu/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39187/distruct-a-program-for-the-graphical-display-of-population-structure</guid>
	<pubDate>Mon, 25 Mar 2019 03:33:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39187/distruct-a-program-for-the-graphical-display-of-population-structure</link>
	<title><![CDATA[DISTRUCT: a program for the graphical display of population structure]]></title>
	<description><![CDATA[<p><em>distruct</em><span>&nbsp;is a program that can be used to graphically display results produced by the genetic clustering program&nbsp;</span><em><a href="http://pritch.bsd.uchicago.edu/">structure</a></em><span>&nbsp;or by other similar programs. The figures produced by&nbsp;</span><em>distruct</em><span>display individual membership coefficients in the same form as used in&nbsp;</span><a href="https://rosenberglab.stanford.edu/papers/popstruct.pdf">"Genetic structure of human populations"&nbsp;<em>Science</em>&nbsp;298: 2381-2385 (2002)</a><span>. Various options enable the user to control left-to-right printing order of populations, bottom-to-top printing order of clusers, colors, and other graphical details. [</span><a href="https://rosenberglab.stanford.edu/distructExample.html">Example</a><span>]</span></p>
<p>[<a href="https://rosenberglab.stanford.edu/distructForms/distructRegistration.html">Download software package (includes the manual)</a>] (you will be directed first to a registration page and we would very much appreciate if you register)&nbsp;<br>[<a href="https://rosenberglab.stanford.edu/software/distructManual.pdf">Download manual</a>]&nbsp;<br>[<a href="https://rosenberglab.stanford.edu/papers/distructNote.pdf">Download software note from&nbsp;<em>Molecular Ecology Notes</em>&nbsp;4: 137-138 (2004)</a>]</p>
<p>To use the UNIX versions, unzip and untar the files in an appropriate directory using</p>
<pre>gunzip filename.tar.gz; tar xvf filename.tar</pre>
<p><span>where "filename.tar.gz" is the downloaded file. Winzip will unzip the Windows version. Run the program by typing</span></p>
<pre>./distruct</pre>
<p><span>in UNIX or</span></p>
<pre>distruct</pre>
<p><span>from a Dos prompt in Windows. It will produce a figure using the data that are represented in the Central/South Asia&nbsp;</span><em>K=5</em><span>&nbsp;plot in&nbsp;</span><em>Science</em><span>&nbsp;298: 2381-2385 (2002).</span></p>
<p>Please send comments or problems with&nbsp;<em>distruct</em>&nbsp;to Noah Rosenberg.</p>
<h4><em>October 15, 2014 &mdash; Users of Distruct may also find&nbsp;<a href="https://rosenberglab.stanford.edu/clumpp.html">CLUMPP</a>&nbsp;and&nbsp;<a href="http://clumpak.tau.ac.il/">CLUMPAK</a>&nbsp;of interest.</em></h4><p>Address of the bookmark: <a href="https://rosenberglab.stanford.edu/distruct.html" rel="nofollow">https://rosenberglab.stanford.edu/distruct.html</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/13999/tedxcopenhagen-morten-sommer-what-bacteria-means-for-the-good-life</guid>
	<pubDate>Wed, 13 Aug 2014 05:07:19 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/13999/tedxcopenhagen-morten-sommer-what-bacteria-means-for-the-good-life</link>
	<title><![CDATA[TEDxCopenhagen - Morten Sommer - What Bacteria Means for the Good Life]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/aji0_ycIU0E" frameborder="0" allowfullscreen></iframe><p>Scientist and entrepreneur Morten Sommer will talk about how bacteria and microbes form an integral part of the human body and play a significant role in controlling human health and well About TEDx, x = independently organized event: In the spirit of ideas worth spreading, TEDx is a program of local, self-organized events that bring people together to share a TED-like experience. At a TEDx event, TEDTalks video and live speakers combine to spark deep discussion and connection in a small group. These local, self-organized events are branded TEDx, where x = independently organized TED event. The TED Conference provides general guidance for the TEDx program, but individual TEDx events are self-organized.* (*Subject to certain rules and regulations)</p>]]></description>
	
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35823/regen-ancestral-genome-reconstruction-for-bacteria</guid>
	<pubDate>Tue, 06 Mar 2018 05:02:36 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35823/regen-ancestral-genome-reconstruction-for-bacteria</link>
	<title><![CDATA[REGEN: Ancestral Genome Reconstruction for Bacteria]]></title>
	<description><![CDATA[<p><span>REGEN infers evolutionary events, including gene creation and deletion and replicon fission and fusion. The reconstruction can be performed by either a maximum parsimony or a maximum likelihood method. Gene content reconstruction is based on the concept of neighboring gene pairs. REGEN was designed to be used with any set of genomes that are sufficiently related, which will usually be the case for bacteria within the same taxonomic order.&nbsp;</span></p><p>Address of the bookmark: <a href="http://www.mdpi.com/2073-4425/3/3/423" rel="nofollow">http://www.mdpi.com/2073-4425/3/3/423</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>

</channel>
</rss>