<?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: All site bookmarks]]></title>
	<link>https://bioinformaticsonline.com/bookmarks/all?offset=250</link>
	<atom:link href="https://bioinformaticsonline.com/bookmarks/all?offset=250" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42566/genomic-open-source-breeding-informatics-initiative</guid>
	<pubDate>Wed, 06 Jan 2021 19:42:21 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42566/genomic-open-source-breeding-informatics-initiative</link>
	<title><![CDATA[Genomic Open-source Breeding informatics initiative]]></title>
	<description><![CDATA[<p><span>To build open-source genomic data management and analysis tools to enable breeders to implement genomic and marker-assisted selection as part of their routine breeding programs.</span></p>
<p><span><span>To transform breeding by connecting diverse data with precision breeding tools to advance yields and adaptation to local growing conditions, bringing global communities closer to a sustainable, reliable food supply.</span></span></p><p>Address of the bookmark: <a href="http://cbsugobii05.biohpc.cornell.edu/wordpress/" rel="nofollow">http://cbsugobii05.biohpc.cornell.edu/wordpress/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42552/bioinformatics-workbook</guid>
	<pubDate>Tue, 05 Jan 2021 22:42:32 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42552/bioinformatics-workbook</link>
	<title><![CDATA[bioinformatics workbook]]></title>
	<description><![CDATA[<p><span>This books assumes that the reader has some knowledge of biology and basic understanding of the Unix command line. However, for the beginner, the appendix contains introductory material and tips/tricks for common bioinformatic problems, that is referred to for more information throughout the book.</span></p>
<p>https://bioinformaticsworkbook.org/</p><p>Address of the bookmark: <a href="https://bioinformaticsworkbook.org/" rel="nofollow">https://bioinformaticsworkbook.org/</a></p>]]></description>
	<dc:creator>biogeek</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42530/shovill-assemble-bacterial-isolate-genomes-from-illumina-paired-end-reads</guid>
	<pubDate>Sat, 02 Jan 2021 07:05:36 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42530/shovill-assemble-bacterial-isolate-genomes-from-illumina-paired-end-reads</link>
	<title><![CDATA[shovill: Assemble bacterial isolate genomes from Illumina paired-end reads]]></title>
	<description><![CDATA[<p><span>Shovill is a pipeline which uses SPAdes at its core, but alters the steps before and after the primary assembly step to get similar results in less time. Shovill also supports other assemblers like SKESA, Velvet and Megahit, so you can take advantage of the pre- and post-processing the Shovill provides with those too.</span></p><p>Address of the bookmark: <a href="https://github.com/tseemann/shovill" rel="nofollow">https://github.com/tseemann/shovill</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</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/bookmarks/view/42497/genome-assembly-training-tutorial-at-galaxy</guid>
	<pubDate>Sun, 27 Dec 2020 05:25:45 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42497/genome-assembly-training-tutorial-at-galaxy</link>
	<title><![CDATA[Genome assembly training tutorial at Galaxy !]]></title>
	<description><![CDATA[<p>In this tutorial we assemble and annotate the genome of <em>E. coli</em> strain <a href="http://cgsc2.biology.yale.edu/Strain.php?ID=8232">C-1</a>. This strain is routinely used in experimental evolution studies involving bacteriophages. For instance, now classic works by Holly Wichman and Jim Bull (<a href="https://training.galaxyproject.org/training-material/topics/assembly/tutorials/unicycler-assembly/tutorial.html#Bull1997">Bull 1997</a>, <a href="https://training.galaxyproject.org/training-material/topics/assembly/tutorials/unicycler-assembly/tutorial.html#Bull1998">Bull 1998</a>, <a href="https://training.galaxyproject.org/training-material/topics/assembly/tutorials/unicycler-assembly/tutorial.html#Wichman1999">Wichman 1999</a>) have been performed using this strain and bacteriophage phiX174.</p><p>Address of the bookmark: <a href="https://training.galaxyproject.org/training-material/topics/assembly/tutorials/unicycler-assembly/tutorial.html" rel="nofollow">https://training.galaxyproject.org/training-material/topics/assembly/tutorials/unicycler-assembly/tutorial.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42491/eukulele-taxonomic-annotation-of-the-unsung-eukaryotic-microbes</guid>
	<pubDate>Sat, 26 Dec 2020 12:10:17 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42491/eukulele-taxonomic-annotation-of-the-unsung-eukaryotic-microbes</link>
	<title><![CDATA[EUKulele: Taxonomic annotation of the unsung eukaryotic microbes]]></title>
	<description><![CDATA[<p><span><span>&nbsp;</span>EUKulele, an open-source software tool designed to assign taxonomy to microeukaryotes detected in meta-omic samples, and complement analysis approaches in other domains by accommodating assembly output and providing concrete metrics reporting the taxonomic completeness of each sample.</span></p><p>Address of the bookmark: <a href="https://github.com/AlexanderLabWHOI/EUKulele" rel="nofollow">https://github.com/AlexanderLabWHOI/EUKulele</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42485/fastprongs-fast-preprocessing-of-next-generation-sequencing-reads</guid>
	<pubDate>Sat, 26 Dec 2020 08:35:21 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42485/fastprongs-fast-preprocessing-of-next-generation-sequencing-reads</link>
	<title><![CDATA[FastProNGS: fast preprocessing of next-generation sequencing reads]]></title>
	<description><![CDATA[<p><span>FastProNGS to integrate the quality control process with automatic adapter removal. Parallel processing was implemented to speed up the process by allocating multiple threads. Compared with similar up-to-date preprocessing tools, FastProNGS is by far the fastest.&nbsp;</span></p><p>Address of the bookmark: <a href="https://github.com/Megagenomics/FastProNGS" rel="nofollow">https://github.com/Megagenomics/FastProNGS</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42477/hifiasm-a-haplotype-resolved-assembler-for-accurate-hifi-reads</guid>
	<pubDate>Thu, 24 Dec 2020 10:03:36 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42477/hifiasm-a-haplotype-resolved-assembler-for-accurate-hifi-reads</link>
	<title><![CDATA[Hifiasm: a haplotype-resolved assembler for accurate Hifi reads]]></title>
	<description><![CDATA[<p><span>Hifiasm is a fast haplotype-resolved de novo assembler for PacBio Hifi reads. It can assemble a human genome in several hours and works with the California redwood genome, one of the most complex genomes sequenced so far. Hifiasm can produce primary/alternate assemblies of quality competitive with the best assemblers. It also introduces a new graph binning algorithm and achieves the best haplotype-resolved assembly given trio data.</span></p><p>Address of the bookmark: <a href="https://github.com/chhylp123/hifiasm" rel="nofollow">https://github.com/chhylp123/hifiasm</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42472/maftools-summarize-analyze-and-visualize-maf-files</guid>
	<pubDate>Wed, 23 Dec 2020 05:29:33 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42472/maftools-summarize-analyze-and-visualize-maf-files</link>
	<title><![CDATA[maftools : Summarize, Analyze and Visualize MAF Files]]></title>
	<description><![CDATA[<p><span>With advances in Cancer Genomics,&nbsp;</span><a href="https://docs.gdc.cancer.gov/Data/File_Formats/MAF_Format/">Mutation Annotation Format</a><span>&nbsp;(MAF) is being widely accepted and used to store somatic variants detected.&nbsp;</span><a href="http://cancergenome.nih.gov/">The Cancer Genome Atlas</a><span>&nbsp;Project has sequenced over 30 different cancers with sample size of each cancer type being over 200.&nbsp;</span><a href="https://wiki.nci.nih.gov/display/TCGA/TCGA+MAF+Files">Resulting data</a><span>&nbsp;consisting of somatic variants are stored in the form of&nbsp;</span><a href="https://docs.gdc.cancer.gov/Data/File_Formats/MAF_Format/">Mutation Annotation Format</a><span>. This package attempts to summarize, analyze, annotate and visualize MAF files in an efficient manner from either TCGA sources or any in-house studies as long as the data is in MAF format.</span></p><p>Address of the bookmark: <a href="https://www.bioconductor.org/packages/release/bioc/vignettes/maftools/inst/doc/maftools.html" rel="nofollow">https://www.bioconductor.org/packages/release/bioc/vignettes/maftools/inst/doc/maftools.html</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42468/applied-computational-genomics-course-at-uu-spring-2020</guid>
	<pubDate>Wed, 23 Dec 2020 03:30:44 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42468/applied-computational-genomics-course-at-uu-spring-2020</link>
	<title><![CDATA[Applied Computational Genomics Course at UU: Spring 2020]]></title>
	<description><![CDATA[<p><span>This course will provide a comprehensive introduction to fundamental concepts and experimental approaches in the analysis and interpretation of experimental genomics data. It will be structured as a series of lectures covering key concepts and analytical strategies. A diverse range of biological questions enabled by modern DNA sequencing technologies will be explored including sequence alignment, the identification of genetic variation, structural variation, and ChIP-seq and RNA-seq analysis. Students will learn and apply the fundamental data formats and analysis strategies that underlie computational genomics research.<span>&nbsp;</span></span><strong>The primary goal of the course is for students to be grounded in theory and leave the course empowered to conduct independent genomic analyses.</strong></p><p>Address of the bookmark: <a href="https://github.com/quinlan-lab/applied-computational-genomics" rel="nofollow">https://github.com/quinlan-lab/applied-computational-genomics</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>

</channel>
</rss>