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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/39017?offset=40</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/44364/genbank-release-2570-is-now-available</guid>
	<pubDate>Wed, 23 Aug 2023 00:23:23 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/44364/genbank-release-2570-is-now-available</link>
	<title><![CDATA[GenBank release 257.0 is now available!]]></title>
	<description><![CDATA[<p><span>GenBank release 257.0 is now available! This release has 25.10 trillion bases and 3.69 billion records. Learn more:&nbsp;https://ncbiinsights.ncbi.nlm.nih.gov/2023/08/21/genbank-release-257/</span><a href="https://ow.ly/zHbV50PBE5o"><br /></a></p><p><a href="https://www.ncbi.nlm.nih.gov/genbank/?utm_source=ncbi_insights&amp;utm_medium=referral&amp;utm_campaign=genbank-release-20230821">GenBank</a>&nbsp;release 257.0 (8/15/2023) is now available on the&nbsp;<a href="https://ftp.ncbi.nlm.nih.gov/genbank/">NCBI FTP site</a>. This release has 25.10 trillion bases and 3.69 billion records.</p><p><strong>The current release has:</strong></p><ul>
<li>246,119,175 traditional records containing 2,112,058,517,945 base pairs of sequence data</li>
<li>2,631,493,489 WGS records containing 22,294,446,104,543 base pairs of sequence data</li>
<li>686,271,945 bulk-oriented TSA records containing 646,176,166,908 base pairs of sequence data</li>
<li>124,421,006 bulk-oriented TLS records containing 48,289,699,026 base pairs of sequence data</li>
</ul>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37751/kast-perform-alignment-free-k-tuple-frequency-comparisons-from-sequences</guid>
	<pubDate>Thu, 20 Sep 2018 08:56:35 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37751/kast-perform-alignment-free-k-tuple-frequency-comparisons-from-sequences</link>
	<title><![CDATA[KAST: Perform Alignment-free k-tuple frequency comparisons from sequences]]></title>
	<description><![CDATA[<p><span>Perform Alignment-free k-tuple frequency comparisons from sequences. This can be in the form of two input files (e.g. a reference and a query) or a single file for pairwise comparisons to be made.</span></p><p>Address of the bookmark: <a href="https://github.com/martinjvickers/KAST" rel="nofollow">https://github.com/martinjvickers/KAST</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38385/decipher-a-software-toolset-for-deciphering-and-managing-biological-sequences-efficiently-using-the-r</guid>
	<pubDate>Sun, 09 Dec 2018 19:06:17 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38385/decipher-a-software-toolset-for-deciphering-and-managing-biological-sequences-efficiently-using-the-r</link>
	<title><![CDATA[DECIPHER; a software toolset for deciphering and managing biological sequences efficiently using the R]]></title>
	<description><![CDATA[<p><span>DECIPHER is a software toolset that can be used for deciphering and managing biological sequences efficiently using the&nbsp;</span><a href="http://www.r-project.org/">R</a><span>&nbsp;programming language. The&nbsp;</span><a href="http://www.r-project.org/">R</a><span>&nbsp;package is distributed as platform independent source code under the&nbsp;</span><a href="http://www.gnu.org/copyleft/gpl.html">GPL version 3 license</a><span>. Some functionality of the program is accessible online through web tools.</span></p>
<p><span style="font-size: medium; text-align: justify;">&nbsp;</span></p><p>Address of the bookmark: <a href="http://www2.decipher.codes/" rel="nofollow">http://www2.decipher.codes/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39867/gepard-allows-the-calculation-of-dotplots-even-for-large-sequences-like-chromosomes-or-bacterial-genomes</guid>
	<pubDate>Mon, 26 Aug 2019 11:38:30 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39867/gepard-allows-the-calculation-of-dotplots-even-for-large-sequences-like-chromosomes-or-bacterial-genomes</link>
	<title><![CDATA[Gepard: allows the calculation of dotplots even for large sequences like chromosomes or bacterial genomes]]></title>
	<description><![CDATA[<p>Gepard (German: "cheetah", Backronym for "GEnome PAir - Rapid Dotter") allows the calculation of dotplots even for large sequences like chromosomes or bacterial genomes. Reference: Krumsiek J, Arnold R, Rattei T. Gepard: A rapid and sensitive tool for creating dotplots on genome scale. Bioinformatics 2007; 23(8): 1026-8. PMID:&nbsp;<a href="http://www.ncbi.nlm.nih.gov/pubmed/17309896" target="_blank">17309896</a></p>
<p><a href="http://cube.univie.ac.at/gepard">http://cube.univie.ac.at/gepard</a></p><p>Address of the bookmark: <a href="https://github.com/univieCUBE/gepard" rel="nofollow">https://github.com/univieCUBE/gepard</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41602/nucdiff-in-depth-characterization-and-annotation-of-differences-between-two-sets-of-dna-sequences</guid>
	<pubDate>Tue, 05 May 2020 10:35:48 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41602/nucdiff-in-depth-characterization-and-annotation-of-differences-between-two-sets-of-dna-sequences</link>
	<title><![CDATA[NucDiff: In-depth characterization and annotation of differences between two sets of DNA sequences]]></title>
	<description><![CDATA[<p>NucDiff locates and categorizes differences between two closely related nucleotide sequences. It is able to deal with very fragmented genomes, structural rearrangements and various local differences. These features make NucDiff to be perfectly suitable to compare assemblies with each other or with available reference genomes.</p>
<p>NucDiff provides information about the types of differences and their locations. It is possible to upload the results into genome browser for visualization and further inspection. It was written in Python and uses the NUCmer package from MUMmer[1] for sequence comparison.</p>
<p><br><br></p><p>Address of the bookmark: <a href="https://github.com/uio-cels/NucDiff" rel="nofollow">https://github.com/uio-cels/NucDiff</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44227/common-methods-to-discover-tandem-repeats</guid>
	<pubDate>Thu, 09 Mar 2023 02:40:52 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44227/common-methods-to-discover-tandem-repeats</link>
	<title><![CDATA[Common methods to discover tandem repeats]]></title>
	<description><![CDATA[<div><div><div><div><div><div><div><div><div><div><p>Tandem repeats are DNA sequences that are repeated in a contiguous manner in the genome. These sequences are often used as genetic markers and are important in many areas of genetics and genomics research. Here are some methods for discovering tandem repeats in genomes:</p><ol>
<li>
<p>Tandem Repeat Finder: Tandem Repeat Finder is a software tool that identifies tandem repeats in DNA sequences. It is available for free download and can be used on both nucleotide and protein sequences. The tool uses a statistical algorithm to identify repeats based on their length, copy number, and overall composition.</p>
</li>
<li>
<p>RepeatMasker: RepeatMasker is another software tool that can identify tandem repeats in DNA sequences. It works by comparing the input sequence to a database of known repeats and then identifies any tandem repeats that match those in the database.</p>
</li>
<li>
<p>PCR-based methods: Polymerase chain reaction (PCR) can be used to amplify and detect tandem repeats in genomic DNA. PCR primers are designed to flank the tandem repeat region, and amplification of the target DNA fragment can be visualized on a gel. This method can be useful for detecting novel tandem repeats and for genotyping.</p>
</li>
<li>
<p>Southern blotting: Southern blotting is a classic method for detecting DNA fragments in a sample. It can be used to detect tandem repeats by digesting genomic DNA with a restriction enzyme, separating the fragments by gel electrophoresis, and then probing the blot with a tandem repeat-specific probe.</p>
</li>
</ol><p>Overall, a combination of these methods can be used to comprehensively identify tandem repeats in genomes.</p></div></div></div></div></div></div></div></div></div></div>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44896/jaeger-an-accurate-and-fast-deep-learning-tool-to-detect-bacteriophage-sequences</guid>
	<pubDate>Sun, 31 Aug 2025 06:30:16 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44896/jaeger-an-accurate-and-fast-deep-learning-tool-to-detect-bacteriophage-sequences</link>
	<title><![CDATA[Jaeger : an accurate and fast deep-learning tool to detect bacteriophage sequences]]></title>
	<description><![CDATA[<p><span>Jaeger is a tool that utilizes homology-free machine learning to identify phage genome sequences that are hidden within metagenomes. It is capable of detecting both phages and prophages within metagenomic assemblies.</span></p><p>Address of the bookmark: <a href="https://github.com/MGXlab/Jaeger" rel="nofollow">https://github.com/MGXlab/Jaeger</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/2759/dynamic-programming-alignment</guid>
	<pubDate>Thu, 22 Aug 2013 09:38:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/2759/dynamic-programming-alignment</link>
	<title><![CDATA[Dynamic Programming Alignment]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/EWJnDMKBEv0" frameborder="0" allowfullscreen></iframe>lecture 9, Chem. C100, Spring 2013, UCLA]]></description>
	
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27333/satsuma-highly-sensitive-whole-genome-synteny-alignments</guid>
	<pubDate>Fri, 13 May 2016 05:25:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27333/satsuma-highly-sensitive-whole-genome-synteny-alignments</link>
	<title><![CDATA[SATSUMA : Highly sensitive whole-genome synteny alignments.]]></title>
	<description><![CDATA[<p>Satsuma is a whole-genome synteny alignment program. It takes two genomes, computes alignments, and then keeps only the parts that are orthologous, i.e. following the conserved order and orientation of features, such as protein coding genes, non-coding genes, or neutral sequences. Satsuma does not require any pre-processing, such as repeat masking, since it will automatically detect ambiguous mappings.<br> <br> Satsuma has parallelization built-in and is designed to run on multi-core architectures. The run-time for aligning two bird-size genomes (~1.2 Gb) is around two days on 24 CPUs. <br> <br> You can find the manual <a href="http://satsuma.sourceforge.net/manual.html">here</a>.<br> Download the latest source code from <a href="https://sourceforge.net/projects/satsuma/">here.</a><br> Stable versions can also be downloaded from the <a href="https://www.broadinstitute.org/science/programs/genome-biology/spines">Broad Institute's</a> web site.<br> <br> An incomplete list of questions and answers (yes, these have really been asked by our users! Please feel free to add your own by e-mailing us) is <a href="http://satsuma.sourceforge.net/faq.html">here</a>.<br> <br> If you use Satsuma in your research, please cite:<br> <a href="http://bioinformatics.oxfordjournals.org/content/26/9/1145.long">Grabherr, M. G., Russell, P., Meyer, M., Mauceli, E., Alf&ouml;ldi, J., Di Palma, F., &amp; Lindblad-Toh, K. (2010). Genome-wide synteny through highly sensitive sequence alignment: Satsuma. Bioinformatics, 26(9), 1145-51</a>.</p>
<p><strong>Tutorial at http://evomics.org/learning/genomics/satsuma/</strong></p><p>Address of the bookmark: <a href="http://satsuma.sourceforge.net/" rel="nofollow">http://satsuma.sourceforge.net/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30555/yaha</guid>
	<pubDate>Fri, 20 Jan 2017 05:38:05 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30555/yaha</link>
	<title><![CDATA[YAHA]]></title>
	<description><![CDATA[<p>YAHA, a fast and flexible hash-based aligner. YAHA is as fast and accurate as BWA-SW at finding the single best alignment per query and is dramatically faster and more sensitive than both SSAHA2 and MegaBLAST at finding all possible alignments. Unlike other aligners that report all, or one, alignment per query, or that use simple heuristics to select alignments, YAHA uses a directed acyclic graph to find the optimal set of alignments that cover a query using a biologically relevant breakpoint penalty. YAHA can also report multiple mappings per defined segment of the query. We show that YAHA detects more breakpoints in less time than BWA-SW across all SV classes, and especially excels at complex SVs comprising multiple breakpoints.</p>
<p><strong>Availability:</strong> YAHA is currently supported on 64-bit Linux systems. Binaries and sample data are freely available for download from <a href="http://faculty.virginia.edu/irahall/YAHA" target="pmc_ext">http://faculty.virginia.edu/irahall/YAHA</a>.</p>
<p><strong>Contact:</strong></p>
<p>http://genome.wustl.edu/people/groups/detail/hall-lab/</p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3463118/" rel="nofollow">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3463118/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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