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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/22454?offset=40</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40964/panev-an-r-package-for-a-pathway-based-network-visualization</guid>
	<pubDate>Sun, 09 Feb 2020 12:41:52 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40964/panev-an-r-package-for-a-pathway-based-network-visualization</link>
	<title><![CDATA[PANEV: an R package for a pathway-based network visualization]]></title>
	<description><![CDATA[<p><span>PANEV (PAthway NEtwork Visualizer) is an R package set for gene/pathway-based network visualization. Based on information available on KEGG, it visualizes genes within a network of multiple levels (from 1 to&nbsp;</span><em>n</em><span>) of interconnected upstream and downstream pathways. The network graph visualization helps to interpret functional profiles of a cluster of genes.</span></p>
<p><span><a href="https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-020-3371-7">https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-020-3371-7</a></span></p><p>Address of the bookmark: <a href="https://github.com/vpalombo/PANEV" rel="nofollow">https://github.com/vpalombo/PANEV</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41272/rainbowr-reliable-association-inference-by-optimizing-weights-with-r-r-package-for-snp-set-gwas-and-multi-kernel-mixed-model</guid>
	<pubDate>Fri, 28 Feb 2020 23:27:37 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41272/rainbowr-reliable-association-inference-by-optimizing-weights-with-r-r-package-for-snp-set-gwas-and-multi-kernel-mixed-model</link>
	<title><![CDATA[RAINBOWR: Reliable Association INference By Optimizing Weights with R (R package for SNP-set GWAS and multi-kernel mixed model)]]></title>
	<description><![CDATA[<p><code>RAINBOWR</code>(Reliable Association INference By Optimizing Weights with R) is a package to perform several types of <code>GWAS</code> as follows.</p>
<ul>
<li>Single-SNP GWAS with <code>RGWAS.normal</code> function</li>
<li>SNP-set (or gene set) GWAS with <code>RGWAS.multisnp</code> function (which tests multiple SNPs at the same time)</li>
<li>Check epistatic (SNP-set x SNP-set interaction) effects with <code>RGWAS.epistasis</code> (very slow and less reliable)</li>
</ul>
<p>https://github.com/KosukeHamazaki/RAINBOWR</p>
<p>https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1007663</p>
<p>https://cran.r-project.org/web/packages/RAINBOWR/index.html</p><p>Address of the bookmark: <a href="https://github.com/KosukeHamazaki/RAINBOWR" rel="nofollow">https://github.com/KosukeHamazaki/RAINBOWR</a></p>]]></description>
	<dc:creator>Surabhi Chaudhary</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42299/platypus-%E2%80%93-r-package-for-object-detection-and-image-segmentation</guid>
	<pubDate>Mon, 09 Nov 2020 02:56:25 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42299/platypus-%E2%80%93-r-package-for-object-detection-and-image-segmentation</link>
	<title><![CDATA[Platypus – R package for object detection and image segmentation.]]></title>
	<description><![CDATA[<p><a href="https://github.com/maju116/platypus" target="_blank">platypus</a>&nbsp;is an R package for object detection and semantic segmentation. Currently using&nbsp;</p>
<div>platypus&nbsp;you can perform:</div>
<ul>
<li>multi-class semantic segmentation using&nbsp;U-Net&nbsp;architecture</li>
<li>multi-class object detection using&nbsp;YOLOv3&nbsp;architecture</li>
</ul>
<p>You can install the latest version of&nbsp;platypus&nbsp;with&nbsp;remotes&nbsp;package:</p>
<div>
<div>
<div>
<div>remotes::install_github("maju116/platypus")</div>
</div>
</div>
</div>
<p>Note that in order to install&nbsp;platypus&nbsp;you need to install&nbsp;keras&nbsp;and&nbsp;tensorflow&nbsp;packages and&nbsp;Tensorflow&nbsp;version&nbsp;&gt;= 2.0.0&nbsp;(&nbsp;Tensorflow 1.x&nbsp;will not be supported!)</p><p>Address of the bookmark: <a href="https://github.com/maju116/platypus" rel="nofollow">https://github.com/maju116/platypus</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43848/r-shiny-in-life-sciences-%E2%80%93-top-7-dashboard-examples</guid>
	<pubDate>Fri, 01 Apr 2022 19:05:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43848/r-shiny-in-life-sciences-%E2%80%93-top-7-dashboard-examples</link>
	<title><![CDATA[R Shiny in Life Sciences – Top 7 Dashboard Examples]]></title>
	<description><![CDATA[<p><span>&nbsp;R Shiny is one of the easiest ways for developers to make production-ready dashboards when speed and functionality are crucial. Shiny is approachable with a lot of documentation available, and because of this, a lot of developers/researchers with non-coding backgrounds are able to produce some impressive results. The whole ecosystem is easy to get your head around and pretty much limitless with regard to what you can do.</span></p><p>Address of the bookmark: <a href="https://www.r-bloggers.com/2022/03/r-shiny-in-life-sciences-top-7-dashboard-examples/" rel="nofollow">https://www.r-bloggers.com/2022/03/r-shiny-in-life-sciences-top-7-dashboard-examples/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44487/r-package-for-pca-analysis</guid>
	<pubDate>Sun, 24 Mar 2024 20:06:24 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44487/r-package-for-pca-analysis</link>
	<title><![CDATA[R Package for PCA Analysis]]></title>
	<description><![CDATA[<p><span>An R package for performing principal component analysis (PCA) of genomics data. The package performs PCA, generates the publication-ready plots, and identifies population-specific outlier individuals. The package can be accessed on GitHub:&nbsp;https://github.com/Devashish13/PopulationStructure</span></p><p>Address of the bookmark: <a href="https://rpubs.com/Devashish13/PCAGenomics" rel="nofollow">https://rpubs.com/Devashish13/PCAGenomics</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/1215/livestock-functional-genomics-summer-school-lfg-2013</guid>
  <pubDate>Fri, 02 Aug 2013 09:57:37 -0500</pubDate>
  <link></link>
  <title><![CDATA[Livestock Functional Genomics Summer School (LFG 2013)]]></title>
  <description><![CDATA[
<p>*Livestock Functional Genomics Summer School - Call for applications*</p>

<p>1st Livestock Functional Genomics Summer School (LFG 2013).</p>

<p>This School was designed for graduate students and early-stage researchers with interest in livestock genomics, who are engaged in projects that require knowledge in the field of computational biology.</p>

<p>Sixty selected participants will spend 13 days receiving theoretical and practical training in genomic data handling from internationally renowned experts.</p>

<p>After the course, the participant should understand the basis and the context of livestock big molecular data, and be able to manipulate high density genotypes, whole genome sequences and transcriptome data.</p>

<p>The Summer School will be held in Araçatuba-SP Brazil, from the 13th to the 21st of September 2013.</p>

<p>All accepted participants will have *expenses fully covered (air ticket, hotel and meals)*, including a free pass to the 5th International Symposium on Animal Functional Genomics http://www.isafg2013.org.br </p>

<p>Applicants will be selected based on their résumés. Application date is due by August 10th.  Results will be announced in August 12th.  </p>

<p>Please consult website: http://www.sciencesatellite.org.br/sschool</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/21685/uiar-short-term-trainingfinal-year-dissertation-project-in-life-sciencesbioinformaticsbiotech</guid>
  <pubDate>Mon, 16 Mar 2015 23:56:25 -0500</pubDate>
  <link></link>
  <title><![CDATA[UIAR Short-Term Training/Final Year Dissertation Project in Life Sciences/Bioinformatics/Biotech]]></title>
  <description><![CDATA[
<p>Short-term training/Final year dissertation project</p>

<p>Candidates desirous of doing a short-term training / final year dissertation project for MSc (Life Sciences/Bioinformatics/Biotechnology or any science discipline) at UIAR Biophysics and Bioinformatics department may please drop an email atanju@iiar.res.in along with their resume.</p>

<p>Selected candidates will be further intimated. There will be a fees charged for doing the project at UIAR. The projects will be experimental or computational or involve both.</p>

<p>The training scope will be in the following areas but not limited to:</p>

<p>Bioinformatics analysis, Docking and Virtual screening, Molecular Dynamics simulation, Cloning, expression and purification of proteins, Biophysical and Biochemical characterisation of proteins, Crystallization and Structural Studies.</p>

<p>Advertisement: www.iiar.res.in/?q=node/450</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42499/galaxy-training-resources</guid>
	<pubDate>Sun, 27 Dec 2020 05:28:07 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42499/galaxy-training-resources</link>
	<title><![CDATA[Galaxy Training Resources !]]></title>
	<description><![CDATA[<p>Welcome to Galaxy Training!</p>
<p>Collection of tutorials developed and maintained by the worldwide Galaxy community</p>
<table>
<thead>
<tr><th>Topic</th><th>Tutorials</th></tr>
</thead>
<tbody>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/introduction/">Introduction to Galaxy Analyses</a></td>
<td>10</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/assembly/">Assembly</a></td>
<td>6</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/climate/">Climate</a></td>
<td>3</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/computational-chemistry/">Computational chemistry</a></td>
<td>6</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/ecology/">Ecology</a></td>
<td>6</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/epigenetics/">Epigenetics</a></td>
<td>6</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/genome-annotation/">Genome Annotation</a></td>
<td>3</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/imaging/">Imaging</a></td>
<td>3</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/metabolomics/">Metabolomics</a></td>
<td>4</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/metagenomics/">Metagenomics</a></td>
<td>7</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/proteomics/">Proteomics</a></td>
<td>18</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/sequence-analysis/">Sequence analysis</a></td>
<td>2</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/statistics/">Statistics and machine learning</a></td>
<td>8</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/transcriptomics/">Transcriptomics</a></td>
<td>23</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/variant-analysis/">Variant Analysis</a></td>
<td>8</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/visualisation/">Visualisation</a></td>
<td>2</td>
</tr>
</tbody>
</table>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://training.galaxyproject.org/training-material/" rel="nofollow">https://training.galaxyproject.org/training-material/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/42814/bioinformatics-in-africa-part6-sudan</guid>
	<pubDate>Sat, 06 Feb 2021 21:20:59 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/42814/bioinformatics-in-africa-part6-sudan</link>
	<title><![CDATA[Bioinformatics in Africa: Part6 - Sudan]]></title>
	<description><![CDATA[<p>Commission&nbsp;for&nbsp;Biotechnology&nbsp;&amp;&nbsp;Genetic&nbsp;Engineering&nbsp;&shy;&nbsp;Khartoum: The&nbsp;Commission&nbsp;for&nbsp;Biotechnology&nbsp;and&nbsp;Genetic&nbsp;Engineering&nbsp;was&nbsp;established&nbsp;in&nbsp;9/2/1993&nbsp;as&nbsp; research&nbsp;unit.&nbsp;In&nbsp;addition&nbsp;to&nbsp;research&nbsp;activities&nbsp;it&nbsp;acts&nbsp;as&nbsp;focal&nbsp;point&nbsp;for&nbsp;the&nbsp;International&nbsp;Center&nbsp;for&nbsp; Biotechnology&nbsp;and&nbsp;Genetic&nbsp;Engineering. The&nbsp;commission&nbsp;conducts&nbsp;researches&nbsp;in&nbsp;order&nbsp;to&nbsp;play&nbsp;a&nbsp;part&nbsp;in&nbsp;solving&nbsp;economical,&nbsp;environmental,&nbsp; health&nbsp;and&nbsp;nutritional&nbsp;problems&nbsp;using&nbsp;modern&nbsp;research&nbsp;techniques&nbsp;with&nbsp;an&nbsp;emphasis&nbsp;on&nbsp;the&nbsp;applied&nbsp; researches&nbsp;in&nbsp;these&nbsp;areas. The&nbsp;laboratories&nbsp;were&nbsp;well&nbsp;furnished&nbsp;with&nbsp;the&nbsp;essential&nbsp;equipments&nbsp;and&nbsp;the&nbsp;catalyst&nbsp;infrastructure&nbsp;to&nbsp; facilitate&nbsp;emergence&nbsp;of&nbsp;a&nbsp;successful&nbsp;for&nbsp;research.&nbsp;The&nbsp;Commission&nbsp;equipped&nbsp;with&nbsp;a&nbsp;computer&nbsp;center&nbsp; and&nbsp;information&nbsp;to&nbsp;serve&nbsp;as&nbsp;informatics&nbsp;and&nbsp;Digital&nbsp;library.</p><p>Research&nbsp;Interest&nbsp;and&nbsp;Activities: 1. Plant&nbsp;Genetic&nbsp;Transformations<br />2. Molecular&nbsp;Population&nbsp;Genetics 3. Detection&nbsp;of&nbsp;human&nbsp;and&nbsp;Animals&nbsp;diseases 4. Breast&nbsp;Cancer&shy;specific&nbsp;protein&nbsp;marker 5. Phytochemical 6. Genomic&nbsp;map 7. Bioremediation 8. Tissue&nbsp;Culture.</p><p>Web&nbsp;site&nbsp;and&nbsp;links: www.geocity.cbge.com</p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44624/bioinformatics-workshops</guid>
	<pubDate>Wed, 31 Jul 2024 02:16:53 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44624/bioinformatics-workshops</link>
	<title><![CDATA[Bioinformatics Workshops !]]></title>
	<description><![CDATA[<p>When delving into bioinformatics, having access to reliable resources is crucial for effective research and analysis. Key online resources include the National Center for Biotechnology Information (NCBI), which offers tools like BLAST for sequence alignment and comprehensive gene databases. For presentations and educational materials, exploring SlideShare for introductory and advanced bioinformatics topics can provide valuable insights and learning aids.</p>
<p>https://evomics.org/2024-workshop-on-genomics/</p><p>Address of the bookmark: <a href="https://evomics.org/2024-workshop-on-genomics/" rel="nofollow">https://evomics.org/2024-workshop-on-genomics/</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>

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