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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/43090?offset=270</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42038/pyparanoid-a-pipeline-for-rapid-identification-of-homologous-gene-families-in-a-set-of-genomes</guid>
	<pubDate>Thu, 13 Aug 2020 10:06:19 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42038/pyparanoid-a-pipeline-for-rapid-identification-of-homologous-gene-families-in-a-set-of-genomes</link>
	<title><![CDATA[PyParanoid: a pipeline for rapid identification of homologous gene families in a set of genomes]]></title>
	<description><![CDATA[<p>PyParanoid is a pipeline for rapid identification of homologous gene families in a set of genomes - a central task of any comparative genomics analysis. The "gold standard" for identifying homologs is to use reciprocal best hits (RBHs) which depends on performing a all-vs-all sequence comparison, usually using BLAST, to determine homology. However, these methods are computationally expensive, requiring&nbsp;O(n2)&nbsp;resources to identify RBHs. This is problematic, as the modern deluge of sequencing data means that comparative genomics analyses could be performed on datasets of thousands of strains.</p><p>Address of the bookmark: <a href="https://github.com/ryanmelnyk/PyParanoid" rel="nofollow">https://github.com/ryanmelnyk/PyParanoid</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44318/proksee-in-depth-characterization-and-visualization-of-bacterial-genomes</guid>
	<pubDate>Tue, 09 May 2023 19:38:52 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44318/proksee-in-depth-characterization-and-visualization-of-bacterial-genomes</link>
	<title><![CDATA[Proksee: in-depth characterization and visualization of bacterial genomes]]></title>
	<description><![CDATA[<p><span>Proksee is an expert system for genome assembly, annotation and visualization. To begin using Proksee, provide a complete genome sequence, sequencing reads or a CGView/Proksee map JSON file.</span></p><p>Address of the bookmark: <a href="https://proksee.ca/" rel="nofollow">https://proksee.ca/</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32129/lordec-a-hybrid-error-correction-program-for-long-pacbio-reads</guid>
	<pubDate>Mon, 10 Apr 2017 04:16:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32129/lordec-a-hybrid-error-correction-program-for-long-pacbio-reads</link>
	<title><![CDATA[LoRDEC: a hybrid error correction program for long, PacBio reads]]></title>
	<description><![CDATA[<p>LoRDEC is a program to correct sequencing errors in long reads from 3rd generation sequencing with high error rate, and is especially intended for PacBio reads. It uses a hybrid strategy, meaning that it uses two sets of reads: the reference read set, whose error rate is assumed to be small, and the PacBio read set, which is then corrected using the reference set. Typically, the reference set contains Illumina reads.</p>
<p><br> Usually, errors in PacBio reads include many insertions and deletions, and comparatively less substitutions. LoRDEC can correct errors of all these types.<br> After correction, a larger portion of the sequence of PacBio reads is usable for detection of region of similarity with other sequences, for aligning them to the contigs of an assembly, etc.</p>
<p>Why is LoRDEC different?</p>
<ul>
<li>It is efficient and can process large read data sets, included from eukaryotic or vertebrate species, on a usual computing server, and even works on desktop/laptop computers.</li>
<li>It adopts a novel graph based approach: it builds a succinct De Bruijn Graph (DBG) representing the short reads, and seeks a corrective sequence for each erroneous region of a long read by traversing chosen paths in the graph.</li>
</ul><p>Address of the bookmark: <a href="http://www.atgc-montpellier.fr/lordec/" rel="nofollow">http://www.atgc-montpellier.fr/lordec/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39640/flas-fast-and-high-throughput-algorithm-for-pacbio-long-read-self-correction</guid>
	<pubDate>Sat, 22 Jun 2019 12:16:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39640/flas-fast-and-high-throughput-algorithm-for-pacbio-long-read-self-correction</link>
	<title><![CDATA[FLAS: fast and high throughput algorithm for PacBio long read self-correction.]]></title>
	<description><![CDATA[<p><span>FLAS, a wrapper algorithm of MECAT, to achieve high throughput long read self-correction while keeping MECAT's fast speed. FLAS finds additional alignments from MECAT prealigned long reads to improve the correction throughput, and removes misalignments for accuracy.</span></p><p>Address of the bookmark: <a href="https://github.com/baoe/flas" rel="nofollow">https://github.com/baoe/flas</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37737/rebaler-program-for-conducting-reference-based-assemblies-using-long-reads</guid>
	<pubDate>Tue, 18 Sep 2018 07:52:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37737/rebaler-program-for-conducting-reference-based-assemblies-using-long-reads</link>
	<title><![CDATA[Rebaler: program for conducting reference-based assemblies using long reads.]]></title>
	<description><![CDATA[<p>Rebaler is a program for conducting reference-based assemblies using long reads. It relies mainly on&nbsp;<a href="https://github.com/lh3/minimap2">minimap2</a>&nbsp;for alignment and&nbsp;<a href="https://github.com/isovic/racon">Racon</a>&nbsp;for making consensus sequences.</p>
<p>I made Rebaler for bacterial genomes (specifically for the task of&nbsp;<a href="https://github.com/rrwick/Basecalling-comparison">testing basecallers</a>). It should in principle work for non-bacterial genomes as well, but I haven't tested it.</p><p>Address of the bookmark: <a href="https://github.com/rrwick/Rebaler" rel="nofollow">https://github.com/rrwick/Rebaler</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/16686/sequence-viewer-download-transcripts-exons-and-proteins</guid>
	<pubDate>Mon, 15 Sep 2014 17:30:36 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/16686/sequence-viewer-download-transcripts-exons-and-proteins</link>
	<title><![CDATA[Sequence Viewer: Download Transcripts, Exons and Proteins]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/ZWnLyYKozaI" frameborder="0" allowfullscreen></iframe>How to download FASTA sequence for certain gene features while in the NCBI's Sequence Viewer.

Sequence Viewer homepage:
www.ncbi.nlm.nih.gov/projects/sviewer/

Sequence Viewer playlist:
https://www.youtube.com/playlist?list=PL76D7EE6A6A8AC1C3]]></description>
	
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27971/samtools-primer</guid>
	<pubDate>Thu, 23 Jun 2016 07:18:17 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27971/samtools-primer</link>
	<title><![CDATA[Samtools Primer !!]]></title>
	<description><![CDATA[<p>SAMtools: Primer / Tutorial by Ethan Cerami, Ph.D.<br><br>keywords: samtools, next-gen, next-generation, sequencing, bowtie, sam, bam, primer, tutorial, how-to, introduction<br>Revisions<br><br>&nbsp;&nbsp;&nbsp; 1.0: May 30, 2013: First public release on biobits.org.<br>&nbsp;&nbsp;&nbsp; 1.1: July 24, 2013: Updated with Disqus Comments / Feedback section.<br>&nbsp;&nbsp;&nbsp; 1.2: December 19, 2014: Multiple updates, including:<br>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Updated to use samtools 1.1 and bcftools 1.2.<br>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Updated usage for bcftools.<br><br>About<br><br>SAMtools is a popular open-source tool used in next-generation sequence analysis. This primer provides an introduction to SAMtools, and is geared towards those new to next-generation sequence analysis. The primer is also designed to be self-contained and hands-on, meaning that you only need to install SAMtools, and no other tools, and sample data sets are provided. Terms in bold are also explained in the glossary at the end of the document.</p><p>Address of the bookmark: <a href="http://biobits.org/samtools_primer.html" rel="nofollow">http://biobits.org/samtools_primer.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30831/fsa-fast-statistical-alignment</guid>
	<pubDate>Mon, 06 Feb 2017 04:26:01 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30831/fsa-fast-statistical-alignment</link>
	<title><![CDATA[FSA: Fast Statistical Alignment]]></title>
	<description><![CDATA[<p><span>FSA is a probabilistic multiple sequence alignment algorithm which uses a "distance-based" approach to aligning homologous protein, RNA or DNA sequences. Much as distance-based phylogenetic reconstruction methods like Neighbor-Joining build a phylogeny using only pairwise divergence estimates, FSA builds a multiple alignment using only pairwise estimations of homology. This is made possible by the sequence annealing technique for constructing a multiple alignment from pairwise comparisons, developed by Ariel Schwartz in&nbsp;</span><a href="http://www.eecs.berkeley.edu/Pubs/TechRpts/2007/EECS-2007-39.html">"Posterior Decoding Methods for Optimization and Control of Multiple Alignments</a><span>."</span></p>
<p>FSA brings the high accuracies previously available only for small-scale analyses of proteins or RNAs to large-scale problems such as aligning thousands of sequences or megabase-long sequences. FSA introduces several novel methods for constructing better alignments:</p>
<ul>
<li>FSA uses machine-learning techniques to estimate gap and substitution parameters on the fly for each set of input sequences. This "query-specific learning" alignment method makes FSA very robust: it can produce superior alignments of sets of homologous sequences which are subject to very different evolutionary constraints.</li>
<li>FSA is capable of aligning hundreds or even thousands of sequences using a randomized inference algorithm to reduce the computational cost of multiple alignment. This randomized inference can be over ten times faster than a direct approach with little loss of accuracy.</li>
<li>FSA can quickly align very long sequences using the "anchor annealing" technique for resolving anchors and projecting them with transitive anchoring. It then stitches together the alignment between the anchors using the methods described above.</li>
<li>The included GUI, MAD (Multiple Alignment Display), can display the intermediate alignments produced by FSA, where each character is colored according to the probability that it is correctly aligned (see the picture and&nbsp;<a href="http://fsa.sourceforge.net/images/Suchard_SIV.fsa.mov">movie</a>&nbsp;at the top of the page).</li>
</ul>
<p><span>You can see more information on the&nbsp;</span><a href="http://fsa.sourceforge.net/FAQ.html">FAQ</a><span>.&nbsp;</span></p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="http://fsa.sourceforge.net/" rel="nofollow">http://fsa.sourceforge.net/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34565/fogsaa-fast-optimal-global-sequence-alignment-algorithm</guid>
	<pubDate>Fri, 08 Dec 2017 14:41:08 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34565/fogsaa-fast-optimal-global-sequence-alignment-algorithm</link>
	<title><![CDATA[FOGSAA: Fast Optimal Global Sequence Alignment Algorithm]]></title>
	<description><![CDATA[<p>Sequence alignment algorithms are widely used to infer similarirty and the point of differences between pair of sequences. FOGSAA is a fast Global alignment algorithm. It is basically a branch and bound approach which starts branch expansion in a greedy way taking the symbols from the given pair of sequences (protein or nucleotide) and results in an optimal alignment faster than conventional dymanic programming techniques. It is also better than the heuristic methods with respect to alignment quality.</p><p>Address of the bookmark: <a href="http://www.isical.ac.in/~bioinfo_miu/FOGSAA.htm" rel="nofollow">http://www.isical.ac.in/~bioinfo_miu/FOGSAA.htm</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<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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