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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/42963?offset=90</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43952/elastic-blast</guid>
	<pubDate>Tue, 06 Sep 2022 18:14:57 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43952/elastic-blast</link>
	<title><![CDATA[Elastic BLAST !]]></title>
	<description><![CDATA[<p><a href="https://blast.ncbi.nlm.nih.gov/doc/elastic-blast/elasticblast.html?utm_source=ncbi_insights&amp;utm_medium=referral&amp;utm_campaign=elasticblast-top3-20220823">ElasticBLAST</a>&nbsp;is a new way to&nbsp;<a href="https://blast.ncbi.nlm.nih.gov/?utm_source=ncbi_insights&amp;utm_medium=referral&amp;utm_campaign=elasticblast-top3-20220823">BLAST</a>&nbsp;large numbers of queries, faster and on the cloud. Here are the top three reasons you should use ElasticBLAST:</p>
<h6><strong><img src="https://i0.wp.com/ncbiinsights.ncbi.nlm.nih.gov/wp-content/uploads/2022/08/ElasticBLAST_Larger-e1659978198941.png?resize=150%2C120&amp;ssl=1" alt="" width="150" height="120" style="border: 0px;">1. ElasticBLAST can handle much LARGER queries!&nbsp;</strong></h6>
<p>ElasticBLAST can search query sets that have&nbsp;<em>hundreds to millions of sequences</em>&nbsp;and against BLAST databases of all sizes.</p>
<h6><span><img src="https://i0.wp.com/ncbiinsights.ncbi.nlm.nih.gov/wp-content/uploads/2022/08/ElasticBLAST_Faster.png?resize=150%2C120&amp;ssl=1" alt="" width="150" height="120" style="border: 0px;">2. ElasticBLAST is FASTER</span></h6>
<p>ElasticBLAST distributes your searches across multiple cloud instances to process them simultaneously. The ability to scale resources in this way allows you to process large numbers of queries in a shorter time than you could with BLAST+.</p>
<h6><img src="https://i0.wp.com/ncbiinsights.ncbi.nlm.nih.gov/wp-content/uploads/2022/08/ElasticBLAST_Easy.png?resize=150%2C120&amp;ssl=1" alt="" width="150" height="120" style="border: 0px;">3. ElasticBLAST is EASY to run on the cloud<strong><br></strong></h6>
<p>ElasticBLAST is easy to set up using our step-by-step instructions&nbsp;<span>(</span><a href="https://blast.ncbi.nlm.nih.gov/doc/elastic-blast/quickstart-aws.html?utm_source=ncbi_insights&amp;utm_medium=referral&amp;utm_campaign=elasticblast-top3-20220823" target="_blank"><span><span>Amazon Web&nbsp;</span><span>Services (AWS)</span></span></a><span>,&nbsp;</span><a href="https://blast.ncbi.nlm.nih.gov/doc/elastic-blast/quickstart-gcp.html?utm_source=ncbi_insights&amp;utm_medium=referral&amp;utm_campaign=elasticblast-top3-20220823" target="_blank"><span>Google Cloud Platform (GCP)</span></a><span><span>)</span>&nbsp;<span>and</span>&nbsp;<span>allows&nbsp;</span><span>you&nbsp;</span><span>to leverage the power of</span><span>&nbsp;the&nbsp;</span><span>cloud. Once configured, i</span><span>t</span>&nbsp;<span>manages the software and database installation, handles partitioning of the BLAST workload among the various instances, and deallocates cloud resources when the searches are done.</span></span></p>
<p><span><span>ElasticBLAST</span>&nbsp;<span>also&nbsp;</span><span>selects the instance (</span><span>i.e.,</span><span>&nbsp;machine) type for you based on database size. Of course, you can also choose the instance type manually if you prefer</span><span>.&nbsp;</span></span></p><p>Address of the bookmark: <a href="https://blast.ncbi.nlm.nih.gov/doc/elastic-blast/" rel="nofollow">https://blast.ncbi.nlm.nih.gov/doc/elastic-blast/</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33955/crocoblast-optimized-parallel-implementation-of-local-sequence-alignment-algorithms</guid>
	<pubDate>Tue, 25 Jul 2017 05:03:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33955/crocoblast-optimized-parallel-implementation-of-local-sequence-alignment-algorithms</link>
	<title><![CDATA[CrocoBLAST: Optimized parallel implementation of local sequence alignment algorithms]]></title>
	<description><![CDATA[<p><span>Local sequence alignment is a cornerstone of bioinformatics, allowing to compare the amino-acid sequences of different proteins, or the nucleotide sequences of different pieces of DNA. The Basic Local Alignment Search Tool (BLAST) has revolutionized the field of bioinformatics, and is currently implemented in all free and commercial bioinformatics packages. However, with the advent of Next Generation Sequencing (NGS) and the development of new sequencing techniques, the utility of traditional BLAST implementations is limited. CrocoBLAST combines the accuracy and general applicability of BLAST with computational efficiency, accessibility, and user experience, so that NGS data can be analyzed efficiently even when only modest computational resources are available.</span></p>
<p>https://webchem.ncbr.muni.cz/Platform/App/CrocoBLAST</p><p>Address of the bookmark: <a href="https://webchem.ncbr.muni.cz/Platform/App/CrocoBLAST" rel="nofollow">https://webchem.ncbr.muni.cz/Platform/App/CrocoBLAST</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35432/mummer4-a-fast-and-versatile-genome-alignment-system</guid>
	<pubDate>Sat, 03 Feb 2018 04:59:17 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35432/mummer4-a-fast-and-versatile-genome-alignment-system</link>
	<title><![CDATA[MUMmer4: A fast and versatile genome alignment system]]></title>
	<description><![CDATA[<p><span>MUMmer4, a substantially improved version of MUMmer that addresses genome size constraints by changing the 32-bit suffix tree data structure at the core of MUMmer to a 48-bit suffix array, and that offers improved speed through parallel processing of input query sequences. With a theoretical limit on the input size of 141Tbp, MUMmer4 can now work with input sequences of any biologically realistic length. We show that as a result of these enhancements, the&nbsp;</span><span>nucmer</span><span>&nbsp;program in MUMmer4 is easily able to handle alignments of large genomes;&nbsp;</span></p><p>Address of the bookmark: <a href="https://mummer4.github.io/" rel="nofollow">https://mummer4.github.io/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36800/genomemapper-simultaneous-alignment-of-short-reads-against-multiple-genomes</guid>
	<pubDate>Fri, 25 May 2018 09:29:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36800/genomemapper-simultaneous-alignment-of-short-reads-against-multiple-genomes</link>
	<title><![CDATA[GenomeMapper: Simultaneous alignment of short reads against multiple genomes]]></title>
	<description><![CDATA[GenomeMapper is a short read mapping tool designed for accurate read alignments. It quickly aligns millions of reads either with ungapped or gapped alignments. It can be used to align against multiple genomes simulanteously or against a single reference. If you are unsure which one is the appropriate GenomeMapper, you might want to use the latter

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2768987/<p>Address of the bookmark: <a href="http://1001genomes.org/software/genomemapper.html" rel="nofollow">http://1001genomes.org/software/genomemapper.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40217/shouji-a-fast-and-efficient-pre-alignment-filter-for-sequence-alignment</guid>
	<pubDate>Mon, 04 Nov 2019 07:09:45 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40217/shouji-a-fast-and-efficient-pre-alignment-filter-for-sequence-alignment</link>
	<title><![CDATA[Shouji: a fast and efficient pre-alignment filter for sequence alignment]]></title>
	<description><![CDATA[<p>The ability to generate massive amounts of sequencing data continues to overwhelm the processing capacity of existing algorithms and compute infrastructures. In this work, we explore the use of hardware/software co-design and hardware acceleration to significantly reduce the execution time of short sequence alignment, a crucial step in analyzing sequenced genomes.</p>
<p>&nbsp;<img src="https://github.com/BilkentCompGen/Shoji/raw/master/Figure1-GitHub.png" alt="image" style="border: 0px;"></p>
<p>We introduce Shouji, a highly parallel and accurate pre-alignment filter that remarkably reduces the need for computationally-costly dynamic programming algorithms. The first key idea of our proposed pre-alignment filter is to provide high filtering accuracy by correctly detecting all common subsequences shared between two given sequences. The second key idea is to design a hardware accelerator design that adopts modern FPGA (field-programmable gate array) architectures to further boost the performance of our algorithm.</p>
<p>More at <a href="https://github.com/CMU-SAFARI/Shouji">https://github.com/CMU-SAFARI/Shouji</a></p><p>Address of the bookmark: <a href="https://github.com/CMU-SAFARI/Shouji" rel="nofollow">https://github.com/CMU-SAFARI/Shouji</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42405/caretta-%E2%80%93-a-multiple-protein-structure-alignment-and-feature-extraction-suite</guid>
	<pubDate>Fri, 18 Dec 2020 02:09:44 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42405/caretta-%E2%80%93-a-multiple-protein-structure-alignment-and-feature-extraction-suite</link>
	<title><![CDATA[Caretta – A multiple protein structure alignment and feature extraction suite]]></title>
	<description><![CDATA[<h3>Caretta &ndash;&nbsp;a multiple protein structure alignment and feature extraction suite</h3>
<p><span>Caretta, a multiple structure alignment suite meant for homologous but sequentially divergent protein families which consistently returns accurate alignments with a higher coverage than current state-of-the-art tools. Caretta is available as a GUI and command-line application and additionally outputs an aligned structure feature matrix for a given set of input structures, which can readily be used in downstream steps for supervised or unsupervised machine learning.&nbsp;</span></p><p>Address of the bookmark: <a href="http://www.bioinformatics.nl/caretta/" rel="nofollow">http://www.bioinformatics.nl/caretta/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40611/deepvariant-an-analysis-pipeline-that-uses-a-deep-neural-network-to-call-genetic-variants-from-next-generation-dna-sequencing-data</guid>
	<pubDate>Sat, 25 Jan 2020 13:28:09 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40611/deepvariant-an-analysis-pipeline-that-uses-a-deep-neural-network-to-call-genetic-variants-from-next-generation-dna-sequencing-data</link>
	<title><![CDATA[DeepVariant : an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.]]></title>
	<description><![CDATA[<p><span>DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.</span></p>
<p><span><span>DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data. DeepVariant relies on&nbsp;</span><a href="https://github.com/google/nucleus">Nucleus</a><span>, a library of Python and C++ code for reading and writing data in common genomics file formats (like SAM and VCF) designed for painless integration with the&nbsp;</span><a href="https://www.tensorflow.org/">TensorFlow</a><span>&nbsp;machine learning framework.</span></span></p>
<p><span><a href="https://ai.googleblog.com/2017/12/deepvariant-highly-accurate-genomes.html">https://ai.googleblog.com/2017/12/deepvariant-highly-accurate-genomes.html</a></span></p>
<p><span><a href="https://www.biorxiv.org/content/10.1101/092890v6">https://www.biorxiv.org/content/10.1101/092890v6</a></span></p>
<p><span><img src="https://4.bp.blogspot.com/-2KlXZO60sWE/WiGc8qlZfxI/AAAAAAAACOs/s1pNiKI8jsAvJLr1E_po5udDO8eObm_awCLcBGAs/s640/image3.png" width="640" height="427" alt="image" style="border: 0px;"></span></p><p>Address of the bookmark: <a href="https://github.com/google/deepvariant" rel="nofollow">https://github.com/google/deepvariant</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34420/rita-rapid-identification-of-high-confidence-taxonomic-assignments-for-metagenomic-data</guid>
	<pubDate>Mon, 27 Nov 2017 08:25:33 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34420/rita-rapid-identification-of-high-confidence-taxonomic-assignments-for-metagenomic-data</link>
	<title><![CDATA[RITA: Rapid identification of high-confidence taxonomic assignments for metagenomic data]]></title>
	<description><![CDATA[<p>RITA is a standalone software package and Web server for taxonomic assignment of metagenomic sequence reads. By combining homology predictions from BLAST or UBLAST with compositional classifications from a Naive Bayes classifier, RITA is able to achieve very high accuracy on short reads. Unlike other hybrid approaches which combine these predictions for all sequences to be classified, RITA uses a pipeline to first identify cases where both types of classifier are in agreement, which constitute the highest-confidence set. Sequences not classified in this manner are subjected to a series of downstream classification steps.</p>
<p>This work has been accepted for publication:</p>
<p>MacDonald NJ, Parks DH, and Beiko RG. Rapid identification of taxonomic assignments. Accepted to&nbsp;<em>Nucleic Acids Research</em>&nbsp;April 4, 2012.</p>
<p>If you have any questions or bug reports, please let us know at &lt;beiko@cs.dal.ca&gt;.</p><p>Address of the bookmark: <a href="http://kiwi.cs.dal.ca/Software/RITA" rel="nofollow">http://kiwi.cs.dal.ca/Software/RITA</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/42296/igblast-117-is-now-available-with-improved-identification-of-productive-v-gene-sequences</guid>
	<pubDate>Sun, 01 Nov 2020 16:52:58 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/42296/igblast-117-is-now-available-with-improved-identification-of-productive-v-gene-sequences</link>
	<title><![CDATA[IgBLAST 1.17 is now available with improved identification of productive V gene sequences]]></title>
	<description><![CDATA[<p>A new release of&nbsp;<a href="https://go.usa.gov/x7WMc" target="_blank">IgBLAST</a>&nbsp;(1.17), the popular package for classifying and analyzing immunoglobulin and T cell receptor sequences, is now available on the&nbsp;<a href="https://go.usa.gov/x7WMc" target="_blank">web</a>&nbsp;and from the&nbsp;<a href="https://ftp.ncbi.nih.gov/blast/executables/igblast/release/LATEST" target="_blank">FTP site</a>. The updated package is better at identifying productive V gene sequences. We added a new field , &ldquo;V frame shift&rdquo;, to the IgBLAST output to indicate whether the V gene translation frame contains a frame-shift. We have also updated the definition of a productive V(D)J sequence to now exclude those with internal frame shifts.</p><p>See the&nbsp;<a href="https://ncbi.github.io/igblast/" target="_blank">new IgBLAST manual</a>&nbsp;on the NCBI GitHub site for more information on setting up and running IgBLAST.</p><p>If you have any questions or concerns, please email us at&nbsp;<a href="mailto:blast-help@ncbi.nlm.nih.gov" target="_blank">blast-help@ncbi.nlm.nih.gov</a></p><p>&nbsp;</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44549/quartet-a-telomere-to-telomere-toolkit-for-gap-free-genome-assembly-and-centromeric-repeat-identification</guid>
	<pubDate>Sat, 08 Jun 2024 15:54:36 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44549/quartet-a-telomere-to-telomere-toolkit-for-gap-free-genome-assembly-and-centromeric-repeat-identification</link>
	<title><![CDATA[quarTeT: a telomere-to-telomere toolkit for gap-free genome assembly and centromeric repeat identification.]]></title>
	<description><![CDATA[<p><span>quarTeT is a collection of tools for T2T genome assembly and basic analysis in automatic workflow.</span><br><br><span>Task include:</span></p>
<ul>
<li><a href="http://www.atcgn.com:8080/quarTeT/docuWeb.html#AssemblyMapper">AssemblyMapper</a>&nbsp;: reference-guided genome assembly</li>
<li><a href="http://www.atcgn.com:8080/quarTeT/docuWeb.html#GapFiller">GapFiller</a>&nbsp;: long-reads based gap filling</li>
<li><a href="http://www.atcgn.com:8080/quarTeT/docuWeb.html#TeloExplorer">TeloExplorer</a>&nbsp;: telomere identification</li>
<li><a href="http://www.atcgn.com:8080/quarTeT/docuWeb.html#CentroMiner">CentroMiner</a>&nbsp;: centromere candidate prediction</li>
</ul>
<p>https://academic.oup.com/hr/article/10/8/uhad127/7197191?login=false&nbsp;</p><p>Address of the bookmark: <a href="http://www.atcgn.com:8080/quarTeT/home.html" rel="nofollow">http://www.atcgn.com:8080/quarTeT/home.html</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>

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