<?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/34562?offset=80</link>
	<atom:link href="https://bioinformaticsonline.com/related/34562?offset=80" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31012/genomecomp</guid>
	<pubDate>Fri, 17 Feb 2017 08:38:32 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31012/genomecomp</link>
	<title><![CDATA[GenomeComp]]></title>
	<description><![CDATA[<p>GenomeComp is a tool for summarizing, parsing and visualizing the genome wide sequence comparison results derived from voluminous BLAST textual output, so as to locate the rearrangements, insertions or deletions of genome segments between species or strains.<br><br>It can be easily used to compare, parsing and visualize large genomic sequences, especially closely related genomes such as inter-species or inter-strains. In addition, it can also show other sequence features like repeat sequence distributions in one whole-genome DNA sequence by comparing the genome to itself.<br><br>It is a stand-alone graphical user interface (GUI) program which runs on Linux, Unix, Mac OS X (tested on version 10.2.4 only) and Microsoft Windows platforms and is written in Perl/Tk.</p><p>Address of the bookmark: <a href="http://www.mgc.ac.cn/GenomeComp/" rel="nofollow">http://www.mgc.ac.cn/GenomeComp/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31064/cgaln</guid>
	<pubDate>Wed, 22 Feb 2017 05:14:15 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31064/cgaln</link>
	<title><![CDATA[Cgaln]]></title>
	<description><![CDATA[<p>Cgaln (Coarse grained alignment) is a program designed to align a pair of whole genomic sequences of not only bacteria but also entire chromosomes of vertebrates on a nominal desktop computer. Cgaln performs an alignment job in two steps, at the block level and then at the nucleotide level. The former "coarse-grained" alignment can explore genomic rearrangements and reduce the regions to be analyzed in the next step. The latter is devoted to detailed alignment within the limited regions found in the first stage. The output of Cgaln is 'glocal' in the sense that rearrangements are taken into consideration while each alignable region is extended as long as possible. Thus, Cgaln is not only fast and memory-efficient, but also can filter noisy outputs without missing the most important homologous segment pairs.</p>
<p>http://www.iam.u-tokyo.ac.jp/chromosomeinformatics/rnakato/cgaln/</p><p>Address of the bookmark: <a href="http://www.iam.u-tokyo.ac.jp/chromosomeinformatics/rnakato/cgaln/" rel="nofollow">http://www.iam.u-tokyo.ac.jp/chromosomeinformatics/rnakato/cgaln/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32633/a-post-assembly-genome-improvement-toolkit-pagit-to-obtain-annotated-genomes-from-contigs</guid>
	<pubDate>Fri, 12 May 2017 10:50:29 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32633/a-post-assembly-genome-improvement-toolkit-pagit-to-obtain-annotated-genomes-from-contigs</link>
	<title><![CDATA[A Post-assembly genome-improvement toolkit (PAGIT) to obtain annotated genomes from contigs]]></title>
	<description><![CDATA[<p>PAGIT addresses the need for software to generate high quality draft genomes. It is based on a series of programs that we developed:</p>
<p><a href="https://sourceforge.net/projects/abacas/files/">ABACAS</a>, that is able to contiguate contigs from a de novo assembly against a closely related reference.</p>
<p><a href="https://sourceforge.net/projects/image2/files/">IMAGE</a>, an iterative approach for closing gaps in assembled genomes using mate pair information. It is able to close gaps left open by the assembler in a draft genome, even when using the same data sets as used by the original assembler.</p>
<p><a href="http://icorn.sourceforge.net/">iCORN</a>, that enables errors in the consensus sequence to be corrected by iteratively mapping reads to the current assembly. An improved version, especially correction Pacfic Bioscience assemblies (PacBio) can be found&nbsp;<a href="ftp://ftp.sanger.ac.uk/pub4/resources/software/pagit/ICORN2/icorn2.V0.95.tgz">here</a>.</p>
<p><a href="https://ratt.svn.sourceforge.net/svnroot/ratt">RATT</a>, a tool to transfer the annotation from a reference genome, or an earlier assembly, onto the latest assembly.</p>
<p>PAGIT bundles these software and makes them more accessible for users.</p><p>Address of the bookmark: <a href="http://www.sanger.ac.uk/science/tools/pagit" rel="nofollow">http://www.sanger.ac.uk/science/tools/pagit</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33006/avid-a-global-alignment-program</guid>
	<pubDate>Wed, 24 May 2017 05:19:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33006/avid-a-global-alignment-program</link>
	<title><![CDATA[AVID: A Global Alignment Program]]></title>
	<description><![CDATA[<p>A new global alignment method called AVID. The method is designed to be fast, memory efficient, and practical for sequence alignments of large genomic regions up to megabases long. We present numerous applications of the method, ranging from the comparison of assemblies to alignment of large syntenic genomic regions and whole genome human/mouse alignments. We have also performed a quantitative comparison of AVID with other popular alignment tools. To this end, we have established a format for the representation of alignments and methods for their comparison. These formats and methods should be useful for future studies. The tools we have developed for the alignment comparisons, as well as the AVID program, are publicly available. See Web Site References section for AVID Web address and Web addresses for other programs discussed in this paper.</p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC430967/" rel="nofollow">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC430967/</a></p>]]></description>
	<dc:creator>Archana Malhotra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39017/macse-multiple-alignment-of-coding-sequences-accounting-for-frameshifts-and-stop-codons</guid>
	<pubDate>Mon, 18 Feb 2019 04:21:50 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39017/macse-multiple-alignment-of-coding-sequences-accounting-for-frameshifts-and-stop-codons</link>
	<title><![CDATA[MACSE: Multiple Alignment of Coding SEquences Accounting for Frameshifts and Stop Codons]]></title>
	<description><![CDATA[<p>MACSE aligns coding NT sequences with respect to their AA translation while allowing NT sequences to contain multiple frameshifts and/or stop codons. MACSE is hence the first automatic solution to align protein-coding gene datasets containing non-functional sequences (pseudogenes) without disrupting the underlying codon structure. It has also proved useful in detecting undocumented frameshifts in public database sequences and in aligning next-generation sequencing reads/contigs against a reference coding sequence.</p>
<p>For further details about the underlying algorithm see the original publication:<br><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0022594" target="_new">MACSE: Multiple Alignment of Coding SEquences accounting for frameshifts and stop codons.<br>Vincent Ranwez, S&eacute;bastien Harispe, Fr&eacute;d&eacute;ric Delsuc, Emmanuel JP Douzery<br>PLoS One 2011, 6(9): e22594</a>.</p><p>Address of the bookmark: <a href="https://bioweb.supagro.inra.fr/macse/index.php?menu=releases" rel="nofollow">https://bioweb.supagro.inra.fr/macse/index.php?menu=releases</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<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/42965/nucl2vec-local-alignment-of-dna-sequences-using-distributed-vector-representation</guid>
	<pubDate>Tue, 16 Mar 2021 05:45:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42965/nucl2vec-local-alignment-of-dna-sequences-using-distributed-vector-representation</link>
	<title><![CDATA[Nucl2Vec: Local alignment of DNA sequences using Distributed Vector Representation]]></title>
	<description><![CDATA[<p><span>We demonstrate a novel approach for</span><span>local alignment of DNA reads with respect to reference genome.</span><span>For this process we have used Skip-gram model for creating</span><span>encoding(Nucl2Vec) and k-nearest neighbor for the alignment.</span><span>With our new approach we have reduced computation cost for</span><span>local alignment , while achieving accuracy comparable to existing</span><span>defacto standard BWA-MEM tool.</span> </p>
<p><em>https://prakharg24.github.io/papers/401851.full.pdf</em></p><p>Address of the bookmark: <a href="https://prakharg24.github.io/papers/401851.full.pdf" rel="nofollow">https://prakharg24.github.io/papers/401851.full.pdf</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/37502/alignqc-a-tool-for-assessing-an-alignment-and-generating-reports-that-are-easy-to-share</guid>
	<pubDate>Tue, 07 Aug 2018 04:41:07 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37502/alignqc-a-tool-for-assessing-an-alignment-and-generating-reports-that-are-easy-to-share</link>
	<title><![CDATA[AlignQC: A tool for assessing an alignment, and generating reports that are easy to share]]></title>
	<description><![CDATA[<p><span>Long read alignment analysis. Generate a reports on sequence alignments for mappability vs read sizes, error patterns, annotations and rarefraction curve analysis. The most basic analysis only requires a BAM file, and outputs a web browser compatible xhtml to visualize/share/store/extract analysis results.</span></p>
<p>https://f1000research.com/articles/6-100/</p>
<p>https://github.com/jason-weirather/AlignQC</p><p>Address of the bookmark: <a href="https://www.healthcare.uiowa.edu/labs/au/AlignQC/" rel="nofollow">https://www.healthcare.uiowa.edu/labs/au/AlignQC/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37776/rhat-a-seed-and-extension-based-noisy-long-read-alignment-tool</guid>
	<pubDate>Sun, 23 Sep 2018 05:12:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37776/rhat-a-seed-and-extension-based-noisy-long-read-alignment-tool</link>
	<title><![CDATA[rHAT: a seed-and-extension-based noisy long read alignment tool]]></title>
	<description><![CDATA[<p><span>rHAT is a seed-and-extension-based noisy long read alignment tool. It is suitable for aligning 3rd generation sequencing reads which are in large read length with relatively high error rate, especially Pacbio's Single Molecule Read-time (SMRT) sequencing reads.</span></p><p>Address of the bookmark: <a href="https://github.com/dfguan/rHAT" rel="nofollow">https://github.com/dfguan/rHAT</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>

</channel>
</rss>