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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/44904?offset=170</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/44370/ncbiblast-2141-now-available</guid>
	<pubDate>Wed, 30 Aug 2023 02:36:13 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/44370/ncbiblast-2141-now-available</link>
	<title><![CDATA[NCBIBLAST+ 2.14.1 now available]]></title>
	<description><![CDATA[<p><a href="https://www.linkedin.com/feed/hashtag/?keywords=ncbiblast&amp;highlightedUpdateUrns=urn%3Ali%3Aactivity%3A7101231946264924160">#NCBIBLAST</a><span>+ 2.14.1 now available with improved documentation, faster and more reliable database downloads, and some bug fixes.&nbsp;</span></p><p>Check out the changes they made.</p><p>They added the&nbsp;<code><span>cleanup-blastdb-volumes.py</span></code>&nbsp;script to remove unused BLAST database volumes. Read the documentation&nbsp;<a href="https://www.ncbi.nlm.nih.gov/books/NBK592857/">here</a>.</p><p>They also switched the protocol from&nbsp;<code><span>ftp</span></code>&nbsp;to&nbsp;<code><span>https</span></code>&nbsp;to access BLAST databases for increased performance and reliability when downloading data from the NCBI with the&nbsp;<code><span>update_blastdb.pl</span></code>&nbsp;script.</p><p>And fixed a few bugs related to downloading data from the NCBI, and&nbsp;<code><span>mt_mode</span></code>&nbsp;crashing&nbsp;<code><span>blastn</span></code>&nbsp;and&nbsp;<code><span>blastx</span></code>.</p><p>Check out the&nbsp;<a href="https://www.ncbi.nlm.nih.gov/books/NBK131777/">release notes</a>.</p><p>Download&nbsp;<a href="https://ftp.ncbi.nlm.nih.gov/blast/executables/blast+/2.14.1/">BLAST+ 2.14.1</a></p><p>Questions or comments? Please write the&nbsp;<a href="https://support.nlm.nih.gov/support/create-case/">BLAST help desk</a>.</p><p><span><span>More info and download:</span>&nbsp;https://blast.ncbi.nlm.nih.gov/doc/blast-news/2023-BLAST-News.html</span></p>]]></description>
	<dc:creator>Neel</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33223/tbl2asn-a-command-line-program-that-automates-the-creation-of-sequence-records-for-submission-to-genbank</guid>
	<pubDate>Mon, 29 May 2017 07:37:08 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33223/tbl2asn-a-command-line-program-that-automates-the-creation-of-sequence-records-for-submission-to-genbank</link>
	<title><![CDATA[Tbl2asn: a command-line program that automates the creation of sequence records for submission to GenBank]]></title>
	<description><![CDATA[<p>Tbl2asn is a command-line program that automates the creation of sequence records for submission to GenBank. It uses many of the same functions as Sequin but is driven generally by data files. Tbl2asn generates .sqn files for submission to GenBank. Additional manual editing is not required before submission.</p>
<p>Tbl2asn is available by anonymous&nbsp;<a href="ftp://ftp.ncbi.nih.gov/toolbox/ncbi_tools/converters/by_program/tbl2asn/">FTP</a>. Copy the right version for your platform, then uncompress the file, rename it to "tbl2asn", and set the permissions, as necessary for the platform.</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/genbank/tbl2asn2/" rel="nofollow">https://www.ncbi.nlm.nih.gov/genbank/tbl2asn2/</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34391/taxoblast-taxoblast-is-a-pipeline-to-identify-contamination-in-genomic-sequence</guid>
	<pubDate>Thu, 23 Nov 2017 08:37:15 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34391/taxoblast-taxoblast-is-a-pipeline-to-identify-contamination-in-genomic-sequence</link>
	<title><![CDATA[Taxoblast : Taxoblast is a pipeline to identify contamination in genomic sequence]]></title>
	<description><![CDATA[<p><span>Modern genome sequencing strategies are highly sensitive to contamination making the detection of foreign DNA sequences an important part of analysis pipelines. Here we use Taxoblast, a simple pipeline with a graphical user interface, for the post-assembly detection of contaminating sequences in the published genome of the kelp&nbsp;</span><em>Saccharina japonica</em><span>. Analyses were based on multiple blastn searches with short sequence fragments. They revealed a number of probable bacterial contaminations as well as hybrid scaffolds that contain both bacterial and algal sequences. This or similar types of analysis, in combination with manual curation, may thus constitute a useful complement to standard bioinformatics analyses prior to submission of genomic data to public repositories. Our analysis pipeline is open-source and freely available at&nbsp;</span><a href="http://sdittami.altervista.org/taxoblast" title="">http://sdittami.altervista.org/taxoblast</a><span>&nbsp;and via SourceForge (</span><a href="https://sourceforge.net/projects/taxoblast" title="">https://sourceforge.net/projects/taxoblast</a><span>).</span></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/taxoblast/files/" rel="nofollow">https://sourceforge.net/projects/taxoblast/files/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/36711/ancestral-sequence-reconstruction-steps</guid>
	<pubDate>Fri, 18 May 2018 08:28:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/36711/ancestral-sequence-reconstruction-steps</link>
	<title><![CDATA[Ancestral sequence reconstruction steps !]]></title>
	<description><![CDATA[<div><strong>Ancestral sequence reconstruction</strong>&nbsp;(<strong>ASR</strong>) &ndash; also known as&nbsp;<strong>ancestral gene</strong>/<strong>sequence reconstruction</strong>/<strong>resurrection</strong>&nbsp;&ndash; is a technique used in the study of&nbsp;molecular evolution. The method consists of the synthesis of an ancestral&nbsp;gene&nbsp;and expression of the corresponding ancestral&nbsp;protein.&nbsp;<a href="https://en.wikipedia.org/wiki/Ancestral_sequence_reconstruction#cite_note-thornton-1"></a>The idea of protein 'resurrection' was suggested in 1963 by Pauling and Zuckerkandl.<a href="https://en.wikipedia.org/wiki/Ancestral_sequence_reconstruction#cite_note-2"></a>&nbsp;Some early efforts were made in the eighties-nineties, led by the laboratory of&nbsp;Steven A. Benner, showing the potential of this technique &ndash; one that only started to be fulfilled in the post-genomic era.<a href="https://en.wikipedia.org/wiki/Ancestral_sequence_reconstruction#cite_note-3"></a>&nbsp;Thanks to the improvement of algorithms and of better sequencing and synthesis techniques, the method was developed further in the early 2000s to allow the resurrection of a greater variety of and much more ancient genes.<a href="https://en.wikipedia.org/wiki/Ancestral_sequence_reconstruction#cite_note-4"></a>&nbsp;Over the last decade, ancestral protein resurrection has developed as a strategy to reveal the mechanisms and dynamics of protein evolution.&nbsp;</div><div>&nbsp;</div><div>BEAST is the best way to predict the ancestral structure. but, I suggest following steps?</div><div>&nbsp;</div><div>1- Alignments "Mafft -&nbsp;<a href="https://www.researchgate.net/deref/http%3A%2F%2Fmafft.cbrc.jp%2Falignment%2Fsoftware%2Fsource.html" target="_blank">http://mafft.cbrc.jp/alignment/software/source.html</a>"</div><div>mafft --maxiterate 1000 --reorder --thread 24 --genafpair Dataset.fasta &gt; Dataset_Alig.fasta</div><div>&nbsp;</div><div>2- Your dataset has a good phylogenetic signal, is possible to perform with Tree-Puzzle "<a href="https://www.researchgate.net/deref/http%3A%2F%2Fwww.tree-puzzle.de" target="_blank">http://www.tree-puzzle.de</a>";</div><div>&nbsp;</div><div id="yui_3_14_1_1_1526649596608_1443">3 - This dataset which the saturation index, I perform with "<a href="https://www.researchgate.net/deref/http%3A%2F%2Fdambe.bio.uottawa.ca%2Fdambe.asp" target="_blank">http://dambe.bio.uottawa.ca/dambe.asp</a>";</div><div>&nbsp;</div><div>4- Has evidence of possible recombination in your dataset, the evaluate if this presence or absence, because this may to influence the grouping of clades, I perform with</div><div>---recombination</div><div>&nbsp;</div><div>4.1- Phi-test, implemented in SplitTree4"<a href="https://www.researchgate.net/deref/http%3A%2F%2Fwww.splitstree.org" target="_blank">http://www.splitstree.org</a>", (.nex file)</div><div>&nbsp;</div><div>4.2- GARD deployed in webserver in the DataMonkey "<a href="https://www.researchgate.net/deref/http%3A%2F%2Fwww.datamonkey.org%2F" target="_blank">http://www.datamonkey.org/</a>" - turning to the amino acid seaview -&gt; view proteins -&gt; save as ...) Ideally do a tree-based groups.</div><div>&nbsp;</div><div>4.3- RDP4 for download and installation on Windows in "<a href="https://www.researchgate.net/deref/http%3A%2F%2Fweb.cbio.uct.ac.za%2F~darren%2Frdp.html" target="_blank">http://web.cbio.uct.ac.za/~darren/rdp.html</a>"</div><div>&nbsp;</div><div>4.4- Hyphy (Mac, Windows, Linux) in "<a href="https://www.researchgate.net/deref/http%3A%2F%2Fhyphy.org%2Fw%2Findex.php%2FDownload" target="_blank">http://hyphy.org/w/index.php/Download</a>"</div><div>&nbsp;</div><div>4.5- Path-o-Gen (temporal structure of a tree input file -&gt; arquivo.tre)</div><div>These steps above, I call of pre-processing to inferences phylogenetic...</div><div>&nbsp;</div><div>5- Perform phylogenetic tree, used Bayesian Inference with Molecular Clock, but is necessary Clock Testing:</div><div>&nbsp;</div><div>- This step is performed with program Beast (Beauti, Beast and TreeAnnotator), and Tracer_v1.5 more FigTree to inspection.</div><div>&nbsp;</div><div>- Tutorials:&nbsp;<a href="https://www.researchgate.net/deref/http%3A%2F%2Fbeast.bio.ed.ac.uk%2Ftutorials" target="_blank">http://beast.bio.ed.ac.uk/tutorials</a></div><div>- Downloads:&nbsp;<a href="https://www.researchgate.net/deref/http%3A%2F%2Fbeast.bio.ed.ac.uk%2Fdownloads" target="_blank">http://beast.bio.ed.ac.uk/downloads</a></div>]]></description>
	<dc:creator>Surabhi Chaudhary</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37962/wtdbg2-a-de-novo-sequence-assembler-for-long-noisy-reads-produced-by-pacbio-or-oxford-nanopore</guid>
	<pubDate>Fri, 19 Oct 2018 08:48:43 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37962/wtdbg2-a-de-novo-sequence-assembler-for-long-noisy-reads-produced-by-pacbio-or-oxford-nanopore</link>
	<title><![CDATA[Wtdbg2: a de novo sequence assembler for long noisy reads produced by PacBio or Oxford Nanopore]]></title>
	<description><![CDATA[<p><span>Wtdbg2 is a&nbsp;</span><em>de novo</em><span>&nbsp;sequence assembler for long noisy reads produced by PacBio or Oxford Nanopore Technologies (ONT). It assembles raw reads without error correction and then builds the consensus from intermediate assembly output. Wtdbg2 is able to assemble the human and even the 32Gb&nbsp;</span><a href="https://www.nature.com/articles/nature25458">Axolotl</a><span>&nbsp;genome at a speed tens of times faster than&nbsp;</span><a href="https://github.com/marbl/canu">CANU</a><span>&nbsp;and&nbsp;</span><a href="https://github.com/PacificBiosciences/FALCON">FALCON</a><span>while producing contigs of comparable base accuracy.</span></p><p>Address of the bookmark: <a href="https://github.com/ruanjue/wtdbg2" rel="nofollow">https://github.com/ruanjue/wtdbg2</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39372/irnad-a-computational-tool-for-identifying-d-modification-sites-in-rna-sequence</guid>
	<pubDate>Thu, 16 May 2019 00:20:07 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39372/irnad-a-computational-tool-for-identifying-d-modification-sites-in-rna-sequence</link>
	<title><![CDATA[iRNAD: a computational tool for identifying D modification sites in RNA sequence]]></title>
	<description><![CDATA[<p><span>iRNAD, for identifying D modification sites in RNA sequence. In this predictor, the RNA samples derived from five species were encoded by nucleotide chemical property and nucleotide density. Support vector machine was utilized to perform the classification.&nbsp;</span></p>
<p><span><a href="http://lin-group.cn/server/iRNAD/">http://lin-group.cn/server/iRNAD/</a></span></p><p>Address of the bookmark: <a href="http://lin-group.cn/server/iRNAD/" rel="nofollow">http://lin-group.cn/server/iRNAD/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40510/reps-repeat-masked-phrap-with-scaffolding-a-wgs-sequence-assembler</guid>
	<pubDate>Sat, 04 Jan 2020 01:08:09 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40510/reps-repeat-masked-phrap-with-scaffolding-a-wgs-sequence-assembler</link>
	<title><![CDATA[RePS: Repeat-masked Phrap with scaffolding, a WGS sequence assembler]]></title>
	<description><![CDATA[<p>RePS (Repeat-masked Phrap with scaffolding), a WGS sequence assembler, that explicitly identifies exact kmer repeats from the shotgun data and removes them prior to the assembly. The established software Phrap is used to compute meaningful error probabilities for each base. Clone-end-pairing information is used to construct scaffolds that order and orient the contigs. The updated version of RePS incorporates some of the ideas introduced by Phusion on clustering</p>
<p><img src="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC186573/bin/45793-17f1_F4TT.jpg" alt="image" style="border: 0px;"></p>
<p>More at</p>
<p><a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC186573/">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC186573/</a></p><p>Address of the bookmark: <a href="ftp://ftp.genomics.org.cn/pub/ricedb/Tools/RePS/RePS-IBM-AIX.tar.gz" rel="nofollow">ftp://ftp.genomics.org.cn/pub/ricedb/Tools/RePS/RePS-IBM-AIX.tar.gz</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/41300/china%E2%80%99s-bgi-says-it-can-sequence-a-genome-for-just-100</guid>
	<pubDate>Sat, 29 Feb 2020 04:49:43 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/41300/china%E2%80%99s-bgi-says-it-can-sequence-a-genome-for-just-100</link>
	<title><![CDATA[China’s BGI says it can sequence a genome for just $100]]></title>
	<description><![CDATA[<p>Using technology originally acquired in the US, the Chinese gene giant BGI Group says it will make genome sequencing cheaper than ever, breaking the $100 barrier for the first time.</p><p>The Shenzhen company says the low cost will be possible with an &ldquo;extreme&rdquo; DNA sequencing system it plans to offer that is capable of decoding the genomes of 100,000 people a year.</p><p>Ref:&nbsp;<a href="https://www.technologyreview.com/s/615289/china-bgi-100-dollar-genome/">https://www.technologyreview.com/s/615289/china-bgi-100-dollar-genome/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43090/loretta-a-user-friendly-tool-for-assembling-viral-genomes-from-pacbio-sequence-data</guid>
	<pubDate>Wed, 23 Jun 2021 07:54:53 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43090/loretta-a-user-friendly-tool-for-assembling-viral-genomes-from-pacbio-sequence-data</link>
	<title><![CDATA[LoReTTA, a user-friendly tool for assembling viral genomes from PacBio sequence data]]></title>
	<description><![CDATA[<p>LoReTTA (Long Read Template-Targeted Assembler), a tool designed for performing <em>de novo</em> assembly of long reads generated from viral genomes on the PacBio platform. LoReTTA exploits a reference genome to guide the assembly process, an approach that has been successful with short reads.</p>
<p>https://academic.oup.com/ve/article/7/1/veab042/6248116</p><p>Address of the bookmark: <a href="https://academic.oup.com/ve/article/7/1/veab042/6248116" rel="nofollow">https://academic.oup.com/ve/article/7/1/veab042/6248116</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44508/a-web-based-tool-for-sequence-alignment-statistics-and-innovative-visualization</guid>
	<pubDate>Thu, 04 Apr 2024 01:44:50 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44508/a-web-based-tool-for-sequence-alignment-statistics-and-innovative-visualization</link>
	<title><![CDATA[A web-based tool for sequence alignment statistics and innovative visualization]]></title>
	<description><![CDATA[<p>AlignStatPlot, a new R package and online tool that is well-documented and easy-to usefor MSA and post-MSA analysis. This tool performs both traditional and cutting-edge analy-ses on sequencing data and generates new visualisation methods for MSA results. Whencompared to currently available tools, AlignStatPlot provides a robust ability to handle andvisualise diversity data, while the online version will save time and encourage researchersto focus on explaining their findings. It is a simple tool that can be used in conjunction withpopulation genetics software (PDF) AlignStatPlot: An R package and online tool for robust sequence alignment statistics and innovative visualization of big data.</p><p>Address of the bookmark: <a href="https://bioinformatics.um6p.ma/AlignStatPlot/" rel="nofollow">https://bioinformatics.um6p.ma/AlignStatPlot/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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