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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/41496?offset=90</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40463/%E2%80%98dockr%E2%80%99-the-r-container</guid>
	<pubDate>Mon, 23 Dec 2019 09:56:49 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40463/%E2%80%98dockr%E2%80%99-the-r-container</link>
	<title><![CDATA[‘dockr’: the R container]]></title>
	<description><![CDATA[<p><code>dockr</code> 0.8.6 is now available on CRAN. <code>dockr</code> is a minimal toolkit to build a lightweight Docker container image for your R package, in which the package itself is available. The Docker image seeks to mirror your R session as close as possible with respect to R specific dependencies. Both dependencies on CRAN R packages as well as local non-CRAN R packages will be included in the Docker container image.</p>
<p>If you want to know, how Docker works, and why you should consider using Docker, please take a look at the <a href="https://www.docker.com/why-docker" target="_blank">Docker website</a>.</p><p>Address of the bookmark: <a href="https://www.docker.com/why-docker" rel="nofollow">https://www.docker.com/why-docker</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<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/42313/crbhits-from-conditional-reciprocal-best-hits-to-codon-alignments-and-kaks-in-r</guid>
	<pubDate>Wed, 11 Nov 2020 23:06:03 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42313/crbhits-from-conditional-reciprocal-best-hits-to-codon-alignments-and-kaks-in-r</link>
	<title><![CDATA[CRBHits: From Conditional Reciprocal Best Hits to Codon Alignments and Ka/Ks in R]]></title>
	<description><![CDATA[<p>CRBHits is a coding sequence (CDS) analysis pipeline in R (R Core Team, 2019). It reimplements the Conditional Reciprocal Best Hit (CRBH) algorithm crb-blast and covers all necessary steps from sequence similarity searches, codon alignments to Ka/Ks calculations and synteny. The new R package targets ecology, population and evolutionary biologists working in the field of comparative genomics.</p><p>Address of the bookmark: <a href="https://gitlab.gwdg.de/mpievolbio-it/crbhits" rel="nofollow">https://gitlab.gwdg.de/mpievolbio-it/crbhits</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44362/biostats-book</guid>
	<pubDate>Mon, 14 Aug 2023 03:11:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44362/biostats-book</link>
	<title><![CDATA[Biostats book !]]></title>
	<description><![CDATA[<p>https://practical-stats-med-r.netlify.app/</p><p>Address of the bookmark: <a href="https://practical-stats-med-r.netlify.app/" rel="nofollow">https://practical-stats-med-r.netlify.app/</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44663/svbyeye-r-package-to-visualize-alignments-between-two-or-multiple-dna-sequences</guid>
	<pubDate>Tue, 17 Sep 2024 02:34:57 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44663/svbyeye-r-package-to-visualize-alignments-between-two-or-multiple-dna-sequences</link>
	<title><![CDATA[SVbyEye: R Package to visualize alignments between two or multiple DNA sequences]]></title>
	<description><![CDATA[<p dir="auto">R Package to visualize alignments between two or multiple DNA sequences including<br>a number of functionalities to facilitate processing of alignments in PAF format.</p>
<p dir="auto"><span>SVbyEye, an open-source R package to visualize and annotate sequence-to-sequence alignments along with various functionalities to process alignments in PAF format. The tool facilitates the characterization of complex SVs in the context of sequence homology helping resolve the mechanisms underlying their formation. Availability and implementation SVbyEye is available at https://github.com/daewoooo/SVbyEye.</span></p>
<p dir="auto">Author: David Porubsky</p><p>Address of the bookmark: <a href="https://github.com/daewoooo/SVbyEye" rel="nofollow">https://github.com/daewoooo/SVbyEye</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38563/hecil-a-hybrid-error-correction-algorithm-for-long-reads-with-iterative-learning</guid>
	<pubDate>Tue, 01 Jan 2019 12:01:00 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38563/hecil-a-hybrid-error-correction-algorithm-for-long-reads-with-iterative-learning</link>
	<title><![CDATA[HECIL: A Hybrid Error Correction Algorithm for Long Reads with Iterative Learning]]></title>
	<description><![CDATA[<p><span>HECIL&mdash;Hybrid Error Correction with Iterative Learning&mdash;a hybrid error correction framework that determines a correction policy for erroneous long reads, based on optimal combinations of decision weights obtained from short read alignments.&nbsp;</span></p>
<p><span><span>HECIL&rsquo;s core algorithm by introducing an iterative learning paradigm that enhances the correction policy at each iteration by incorporating knowledge gathered from previous iterations via data-driven confidence metrics assigned to prior corrections.</span></span></p><p>Address of the bookmark: <a href="https://github.com/NDBL/HECIL" rel="nofollow">https://github.com/NDBL/HECIL</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36849/glean-an-unsupervised-learning-system-to-integrate-disparate-sources-of-gene-structure-evidence</guid>
	<pubDate>Sat, 02 Jun 2018 07:38:33 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36849/glean-an-unsupervised-learning-system-to-integrate-disparate-sources-of-gene-structure-evidence</link>
	<title><![CDATA[GLEAN: an unsupervised learning system to integrate disparate sources of gene structure evidence]]></title>
	<description><![CDATA[<p><span>GLEAN is an unsupervised learning system to integrate disparate sources of gene structure evidence (gene model predictions, EST/protein genomic sequence alignments, SAGE/peptide tags, etc) to produce a consensus gene prediction, without prior training.</span></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/glean-gene/" rel="nofollow">https://sourceforge.net/projects/glean-gene/</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/44640/new-blast-core-nucleotide-database-core-nt</guid>
	<pubDate>Tue, 13 Aug 2024 07:12:53 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/44640/new-blast-core-nucleotide-database-core-nt</link>
	<title><![CDATA[New BLAST Core Nucleotide Database (core_nt)]]></title>
	<description><![CDATA[<p><span>The Core Nucleotide Database (core_nt) is now the default nucleotide BLAST database. Core_nt is also available on the command line. You get faster searches &amp; more focused results.</span></p><p><span><span>Core_nt contains the same eukaryotic transcript and gene-related sequences as nt. The core_nt database is nt without most eukaryotic chromosome sequences. Most nucleotide BLAST searches with core_nt will be similar to the nt database. However, core_nt is better than nt for accomplishing your most common BLAST search goals, such as identifying gene-related sequences like transcript sequences and complete bacterial chromosomes. This is because, in recent years, nt has acquired more low-relevance, non-annotated, and non-gene&nbsp;<span>content.&nbsp;</span></span></span></p><p><span> Learn more:&nbsp;https://ncbiinsights.ncbi.nlm.nih.gov/2024/07/18/new-blast-core-nucleotide-database/</span></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/120/user</guid>
	<pubDate>Wed, 10 Jul 2013 14:41:49 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/120/user</link>
	<title><![CDATA[useR!]]></title>
	<description><![CDATA[<p><span>The R project actively supports two conference series, organized regularly by members from the R community: useR! - providing a forum to the R user community - and DSC - a platform for developers of statistical software.</span></p><p><span>Recently useR! conference have been organized&nbsp;<span>University of Castilla-La Mancha, Albacete, Spain.</span></span></p><p><a href="http://www.edii.uclm.es/~useR-2013//">http://www.edii.uclm.es/~useR-2013//</a></p><p>&nbsp;</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>

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