<?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/38579?offset=50</link>
	<atom:link href="https://bioinformaticsonline.com/related/38579?offset=50" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39250/darwin-wga-a-co-processor-provides-increased-sensitivity-in-whole-genome-alignments-with-high-speedup</guid>
	<pubDate>Sat, 13 Apr 2019 08:55:31 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39250/darwin-wga-a-co-processor-provides-increased-sensitivity-in-whole-genome-alignments-with-high-speedup</link>
	<title><![CDATA[Darwin-WGA: A Co-processor Provides Increased Sensitivity in Whole Genome Alignments with High Speedup]]></title>
	<description><![CDATA[<p>Darwin-WGA, is the first hardware accelerator for whole genome alignment and accelerates the gapped filtering stage. Darwin-WGA also employs GACT-X, a novel algorithm used in the extension stage to align arbitrarily long genome sequences using a small on-chip memory, that provides better quality alignments at 2&times; improvement in memory and speed over the previously published GACT algorithm. Implemented on an FPGA, Darwin-WGA provides up to 24&times; improvement (performance/$) in WGA over iso-sensitive software.</p>
<p><a href="https://stanford.edu/~yatisht/pubs/darwin-wga.pdf">https://stanford.edu/~yatisht/pubs/darwin-wga.pdf</a></p><p>Address of the bookmark: <a href="https://github.com/gsneha26/Darwin-WGA" rel="nofollow">https://github.com/gsneha26/Darwin-WGA</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40549/mgse-mapping-based-genome-size-estimation</guid>
	<pubDate>Fri, 17 Jan 2020 02:11:43 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40549/mgse-mapping-based-genome-size-estimation</link>
	<title><![CDATA[MGSE: Mapping-based Genome Size Estimation]]></title>
	<description><![CDATA[<p>MGSE can harness the power of files generated in genome sequencing projects to predict the genome size. Required are the FASTA file containing a high continuity assembly and a BAM file with all available reads mapped to this assembly. The script construct_cov_file.py (https://doi.org/10.1186/s12864-018-5360-z) allows the generation of a COV file based on the (sorted) BAM file (also possible via MGSE directly). Next, this COV file can be used by MGSE to calculate the coverage in provided reference regions and to calculate the total number of mapped bases. Both values are subjected to the genome size estimation. Providing accurate reference regions is crucial for this genome size estimation.</p><p>Address of the bookmark: <a href="https://github.com/bpucker/MGSE" rel="nofollow">https://github.com/bpucker/MGSE</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41330/u-plot-genome-u-plot-sample-implementation</guid>
	<pubDate>Tue, 03 Mar 2020 01:39:12 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41330/u-plot-genome-u-plot-sample-implementation</link>
	<title><![CDATA[U-Plot: Genome U-Plot sample implementation]]></title>
	<description><![CDATA[<p>The Genome U-Plot is a JavaScript tool to visualize Chromosomal abnormalities in the Human Genome using a U-shape layout.</p>
<p><img src="https://raw.githubusercontent.com/gaitat/GenomeUPlot/master/public/data/LNCAP.png" alt="image" style="border: 0px;"></p><p>Address of the bookmark: <a href="https://github.com/gaitat/GenomeUPlot" rel="nofollow">https://github.com/gaitat/GenomeUPlot</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42415/sneakysnake-a-fast-and-accurate-universal-genome-pre-alignment-filter-for-cpus-gpus-and-fpgas</guid>
	<pubDate>Sun, 20 Dec 2020 01:39:54 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42415/sneakysnake-a-fast-and-accurate-universal-genome-pre-alignment-filter-for-cpus-gpus-and-fpgas</link>
	<title><![CDATA[SneakySnake: A Fast and Accurate Universal Genome Pre-Alignment Filter for CPUs, GPUs, and FPGAs]]></title>
	<description><![CDATA[<p><span>The first and the only pre-alignment filtering algorithm that works efficiently and fast on modern CPU, FPGA, and GPU architectures. SneakySnake greatly (by more than two orders of magnitude) expedites sequence alignment calculation for both short (Illumina) and long (ONT and PacBio) reads. Described by Alser et al. (preliminary version at&nbsp;</span><a href="https://arxiv.org/abs/1910.09020">https://arxiv.org/abs/1910.09020</a><span>).</span></p><p>Address of the bookmark: <a href="https://github.com/CMU-SAFARI/SneakySnake" rel="nofollow">https://github.com/CMU-SAFARI/SneakySnake</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43060/simons-genome-diversity-project</guid>
	<pubDate>Sat, 08 May 2021 21:55:25 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43060/simons-genome-diversity-project</link>
	<title><![CDATA[Simons Genome Diversity Project]]></title>
	<description><![CDATA[<p><em>Complete genome sequences from more than one hundred diverse human populations</em></p>
<p>All genomes in the dataset were sequenced to at least 30x coverage using Illumina technology. The sequencing reads were mapped and genotyped using a customized procedure that was optimized for population genetic analysis. The researchers eliminated bias of alleles toward matching the human genome reference sequence, and determined genotypes on a single-sample basis to avoid preferential calling of genotypes from populations that had more individuals represented.</p><p>Address of the bookmark: <a href="https://www.simonsfoundation.org/simons-genome-diversity-project/" rel="nofollow">https://www.simonsfoundation.org/simons-genome-diversity-project/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43376/hisat2-index-files-download</guid>
	<pubDate>Wed, 15 Sep 2021 22:17:49 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43376/hisat2-index-files-download</link>
	<title><![CDATA[HISAT2 Index Files Download !]]></title>
	<description><![CDATA[<p>Resource for downloading all the HISAT2 related files&nbsp;</p>
<p>Please cite:</p>
<blockquote>
<p>Kim, D., Paggi, J.M., Park, C.&nbsp;<em>et al.</em>&nbsp;Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype.&nbsp;<em>Nat Biotechnol</em>&nbsp;<strong>37</strong>, 907&ndash;915 (2019).&nbsp;<a href="https://doi.org/10.1038/s41587-019-0201-4" target="_blank">https://doi.org/10.1038/s41587-019-0201-4</a></p>
</blockquote><p>Address of the bookmark: <a href="http://daehwankimlab.github.io/hisat2/download/#h-sapiens" rel="nofollow">http://daehwankimlab.github.io/hisat2/download/#h-sapiens</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43652/peregrine-shimmer-genome-assembly-toolkit</guid>
	<pubDate>Thu, 16 Dec 2021 02:50:19 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43652/peregrine-shimmer-genome-assembly-toolkit</link>
	<title><![CDATA[Peregrine &amp; SHIMMER Genome Assembly Toolkit]]></title>
	<description><![CDATA[<p><span>Peregrine is a fast genome assembler for accurate long reads (length &gt; 10kb, accuracy &gt; 99%). It can assemble a human genome from 30x reads within 20 cpu hours from reads to polished consensus. It uses Sparse HIereachical MimiMizER (SHIMMER) for fast read-to-read overlaping without quadratic comparisions used in other OLC assemblers.</span></p><p>Address of the bookmark: <a href="https://github.com/cschin/Peregrine" rel="nofollow">https://github.com/cschin/Peregrine</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43725/comparative-genomics-workshops</guid>
	<pubDate>Tue, 25 Jan 2022 20:39:58 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43725/comparative-genomics-workshops</link>
	<title><![CDATA[Comparative Genomics Workshops !]]></title>
	<description><![CDATA[<p><span>This meeting's objective was to obtain a big picture look at the current state of the field of comparative&nbsp;genomics with a focus on commonalities across genomic investigations into humans, model organisms&nbsp;(both traditional and non-traditional), agricultural species, wildlife species and microbes.</span></p>
<p>https://www.genome.gov/event-calendar/perspectives-in-comparative-genomics-and-evolution</p><p>Address of the bookmark: <a href="https://www.genome.gov/event-calendar/perspectives-in-comparative-genomics-and-evolution" rel="nofollow">https://www.genome.gov/event-calendar/perspectives-in-comparative-genomics-and-evolution</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44168/environmental-genomics-group-scilifelabkth-stockholm</guid>
	<pubDate>Thu, 01 Dec 2022 01:12:43 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44168/environmental-genomics-group-scilifelabkth-stockholm</link>
	<title><![CDATA[Environmental Genomics Group SciLifeLab/KTH Stockholm]]></title>
	<description><![CDATA[<p>Useful Metagenomics resources</p><p>Address of the bookmark: <a href="https://github.com/envgen" rel="nofollow">https://github.com/envgen</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/44342/ncbi-datasets%E2%80%AFpages</guid>
	<pubDate>Wed, 12 Jul 2023 06:29:31 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/44342/ncbi-datasets%E2%80%AFpages</link>
	<title><![CDATA[NCBI Datasets pages]]></title>
	<description><![CDATA[<p>Update! Assembly and Genome record pages now redirect to new NCBI Datasets pages. NCBI Datasets is a new resource that makes it easier to find and download genome data. Learn more: https://ncbiinsights.ncbi.nlm.nih.gov/2023/07/11/ncbi-datasets-genome-assembly-pages/&nbsp;<a href="https://ow.ly/GU3o50P8QH4"></a><a href="https://www.linkedin.com/feed/hashtag/?keywords=ncbicgr&amp;highlightedUpdateUrns=urn%3Ali%3Aactivity%3A7084592728260386816">#NCBICGR</a></p><p><span>Effective July 10, 2023, NCBI&rsquo;s Assembly and Genome record pages now redirect to&nbsp;</span>new<a href="https://www.ncbi.nlm.nih.gov/datasets/?utm_source=ncbi_insights&amp;utm_medium=referral&amp;utm_campaign=datasets-genome-assembly-redirect-20230711"> NCBI Datasets </a><span>pages. As&nbsp;</span><a href="https://ncbiinsights.ncbi.nlm.nih.gov/2023/03/07/ncbi-datasets-genome-taxonomy-pages/?utm_source=ncbi_insights&amp;utm_medium=referral&amp;utm_campaign=datasets-genome-assembly-redirect-20230711">previously announced</a><span>, these updates are part of our ongoing effort to modernize and improve your user experience. NCBI Datasets is a new resource that makes it easier to find and download genome data.  </span><span>&nbsp;</span></p><h5>The following pages have been updated:</h5><ul>
<li><span>The NCBI Assembly record pages now redirect to the new </span><a href="https://www.ncbi.nlm.nih.gov/datasets/genome/GCF_023065955.2/?utm_source=ncbi_insights&amp;utm_medium=referral&amp;utm_campaign=datasets-genome-assembly-redirect-20230711"><span>NCBI Datasets</span><strong><span> </span></strong><span>Genome</span></a><span> </span><span>record pages that describe assembled genomes and provide links to related NCBI tools such as Genome Data Viewer and BLAST. </span><span>&nbsp;</span></li>
<li><span>The NCBI</span><strong> </strong><span>Genome record pages now redirect to the </span><a href="https://www.ncbi.nlm.nih.gov/datasets/taxonomy/9644/?utm_source=ncbi_insights&amp;utm_medium=referral&amp;utm_campaign=datasets-genome-assembly-redirect-20230711"><span>NCBI Datasets</span><strong><span> </span></strong><span>Taxonomy</span></a><span> </span><span>record pages that provide a taxonomy-focused portal to genes, genomes, and additional NCBI resources.  </span><span>&nbsp;</span></li>
</ul><p><span>During this transition, you will have the option to return to the legacy Genome and Assembly record pages. We will remove the legacy pages in early 2024. </span><span>&nbsp;</span></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>

</channel>
</rss>