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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/44479?offset=130</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34734/smash-an-alignment-free-tool-to-find-and-visualise-rearrangements-between-pairs-of-dna-sequences</guid>
	<pubDate>Thu, 21 Dec 2017 08:26:57 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34734/smash-an-alignment-free-tool-to-find-and-visualise-rearrangements-between-pairs-of-dna-sequences</link>
	<title><![CDATA[SMASH: An alignment-free tool to find and visualise rearrangements between pairs of DNA sequences]]></title>
	<description><![CDATA[<p style="text-align: justify;"><span>SMASH is a completely alignment-free method to find and visualise rearrangements between pairs of DNA sequences</span>. The detection is based on&nbsp;<span>relative compression</span>, namely using a FCM, also known as Markov model, of high context order (typically 20). The method has been approached with a tool (also called SMASH). For visualization, SMASH outputs a SVG image, with an ideogram output architecture, where the patterns are represented with several HSV values (only value varies). The following image, illustrating the information maps between human and chimpanzee for the several chromosomes, depicts an example:</p>
<p><a href="https://github.com/pratas/smash/blob/master/imgs/HC.png" target="_blank"><img src="https://github.com/pratas/smash/raw/master/imgs/HC.png" alt="ScreenShot" style="border: 0px;"></a></p>
<p>&nbsp;</p>
<h2>&nbsp;</h2><p>Address of the bookmark: <a href="https://github.com/pratas/smash" rel="nofollow">https://github.com/pratas/smash</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37788/s-plot2-creates-an-interactive-two-dimensional-heatmap-of-sequences</guid>
	<pubDate>Fri, 28 Sep 2018 05:36:19 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37788/s-plot2-creates-an-interactive-two-dimensional-heatmap-of-sequences</link>
	<title><![CDATA[S-plot2: creates an interactive, two-dimensional heatmap of sequences]]></title>
	<description><![CDATA[<p><span>S-plot2 creates an interactive, two-dimensional heatmap capturing the similarities and dissimilarities in nucleotide usage between genomic sequences (partial or complete). In S-plot2, whole eukaryotic chromosomes and smaller prokaryotic genomes can be efficiently compared. The tool includes functionality to extract, analyze, and automate BLAST queries of regions of interest within the heatmap. This facilitates the investigation of quickly evolving coding regions, novel coding regions, and laterally transferred elements.</span></p>
<p><span>http://www.putonti-lab.com/uploads/4/5/3/0/45307835/s-plot2_tutorial.pdf</span></p>
<p><span>http://journals.sagepub.com/doi/pdf/10.1177/1176934318797354</span></p><p>Address of the bookmark: <a href="https://bitbucket.org/lkalesinskas/splot" rel="nofollow">https://bitbucket.org/lkalesinskas/splot</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>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39624/cogent-a-tool-for-reconstructing-the-coding-genome-using-high-quality-full-length-transcriptome-sequences</guid>
	<pubDate>Tue, 18 Jun 2019 05:33:04 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39624/cogent-a-tool-for-reconstructing-the-coding-genome-using-high-quality-full-length-transcriptome-sequences</link>
	<title><![CDATA[Cogent: a tool for reconstructing the coding genome using high-quality full-length transcriptome sequences.]]></title>
	<description><![CDATA[<div id="yui_3_14_1_1_1560853173251_3865">Cogent is a tool that identifies gene&nbsp;families and reconstructs the coding genome using high-quality transcriptome data without a reference genome, and can be used to check&nbsp;assemblies&nbsp;for the presence of&nbsp;these known coding sequences.</div>
<div>&nbsp;</div>
<div>
<p>Cogent is a tool for reconstructing the coding genome using high-quality full-length transcriptome sequences. It is designed to be used on&nbsp;<a href="https://github.com/PacificBiosciences/cDNA_primer/wiki">Iso-Seq data</a>&nbsp;and in cases where there is no reference genome or the ref genome is highly incomplete.</p>
<p>See a&nbsp;<a href="https://www.dropbox.com/s/mn6hwhguh0pqceu/20160106_Cogent_developers_conference_slides_Cuttlefish.pdf?dl=0">recent presentation</a>&nbsp;on Cogent being applied to the Cuttlefish Iso-Seq data.</p>
<p><a href="https://www.dropbox.com/s/kz0gi7qg0w82k9a/20161026_Cogent_manuscript_forGitHub.pdf?dl=0">Cogent preliminary draft paper (updated 2016Dec version)</a>,&nbsp;<a href="https://www.dropbox.com/s/37412o8glvnfhf9/20161026_Cogent_ManuscriptPlusSupplement_forGitHub.pdf?dl=0">Supplementary</a></p>
<p>Please see&nbsp;<a href="https://github.com/Magdoll/Cogent/wiki">wiki</a>&nbsp;for details on usage.</p>
</div><p>Address of the bookmark: <a href="https://github.com/Magdoll/Cogent" rel="nofollow">https://github.com/Magdoll/Cogent</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/41230/curated-set-of-ribosomal-rna-rrna-reference-sequences-targeted-loci-with-verifiable-organism</guid>
	<pubDate>Sun, 23 Feb 2020 02:17:30 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/41230/curated-set-of-ribosomal-rna-rrna-reference-sequences-targeted-loci-with-verifiable-organism</link>
	<title><![CDATA[Curated set of ribosomal RNA (rRNA) reference sequences (targeted loci) with verifiable organism]]></title>
	<description><![CDATA[<p>MCBI have a curated set of ribosomal RNA (rRNA) reference sequences (targeted loci) with verifiable organism sources and current names. This set is critical for correctly identifying and classifying prokaryotic (bacteria and archaea) and fungal samples. To provide easy access to these sequences, we recently added a separate rRNA/ITS databases section on the nucleotide BLAST page for these targeted sequences that makes it convenient to quickly identify source organisms. The new databases are: </p><p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; *16S ribosomal RNA (Bacteria and Archaea)</p><p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; *18S ribosomal RNA sequences (SSU) from Fungi type and reference material&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</p><p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; *28S ribosomal RNA sequences (LSU) from Fungi type and reference material</p><p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; *Internal transcribed spacer region (ITS) from Fungi type and reference material</p><p>You can also download these from the BLAST db FTP area.&nbsp; See the <a href="https://go.usa.gov/xdEBX" target="_blank">NCBI Insights post</a> for more detail. </p><p>Useful links</p><p>-----------------</p><p><a href="https://go.usa.gov/xdEj5" target="_blank">BLAST form with rRNA/ITS databases</a></p><p><a href="https://ftp.ncbi.nlm.nih.gov/blast/db/" target="_blank">BLAST db download</a></p><p><a href="https://www.ncbi.nlm.nih.gov/refseq/targetedloci/" target="_blank">Targeted loci</a></p><p><span style="color: black;">If you have any questions or concerns, please contact <a href="mailto:blast-help@ncbi.nlm.nih.gov" target="_blank" title="Follow link">blast-help@ncbi.nlm.nih.gov<sup><span style="color: black; text-decoration: none;"><img src="https://mail.google.com/mail/u/0?ui=2&amp;ik=024a8aa0b9&amp;attid=0.1&amp;permmsgid=msg-f:1659255165855446848&amp;th=1706dbc8408bb740&amp;view=fimg&amp;sz=s0-l75-ft&amp;attbid=ANGjdJ_drW2ArYDNLoHrQh36gm6rp2Std8ZUSplCzP6bYQSQYBsQfZ_85vOujXOdTRdaLxrR7QeEBVUbyACPBJHhFUeIglX8G7Ew7TcclzhvO7fJhiz7sIdkkDgZ7QA&amp;disp=emb" alt="https://jira.ncbi.nlm.nih.gov/images/icons/mail_small.gif" width="13" height="12" style="border: 0px;"></span></sup></a></span></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
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	<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/blog/view/44234/steps-to-find-palindrome-in-genomes</guid>
	<pubDate>Thu, 09 Mar 2023 02:56:54 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44234/steps-to-find-palindrome-in-genomes</link>
	<title><![CDATA[Steps to find palindrome in genomes !]]></title>
	<description><![CDATA[<div><div><div><div><div><div><div><div><div><div><p>Palindromes are sequences of nucleotides that read the same backward as forward. They can be present in genomes and have various biological functions. Here are some methods for discovering palindromes in genomes:</p><ol>
<li>
<p>Direct sequence search: One of the simplest ways to discover palindromes is to search the genome sequence directly for palindromic sequences using pattern matching tools, such as regular expressions or string algorithms. This approach can be useful for discovering simple palindromes, but may miss more complex palindromic structures.</p>
</li>
<li>
<p>Dot plot analysis: Dot plot analysis is a graphical method that can be used to identify palindromic regions in a genome. It involves plotting the genome sequence against itself and examining the diagonal patterns that emerge. Palindromic regions will appear as symmetrical patterns along the diagonal.</p>
</li>
<li>
<p>Restriction enzyme analysis: Some restriction enzymes, such as EcoRI and HindIII, recognize palindromic sequences and cleave DNA at these sites. By digesting the genome with these enzymes and examining the resulting fragments, palindromic regions can be identified.</p>
</li>
<li>
<p>Next-generation sequencing: High-throughput sequencing technologies, such as PacBio and Oxford Nanopore, can generate long reads that can span entire palindromic regions. By mapping these reads to the genome, palindromic regions can be identified and characterized.</p>
</li>
<li>
<p>Comparative genomics: Comparing the genomes of related species can also reveal palindromic regions that are conserved across evolutionarily divergent lineages. This approach can help identify functional palindromes that are under selective pressure.</p>
</li>
</ol><p>Overall, the discovery of palindromic sequences in genomes can be accomplished using a variety of methods, each with their own advantages and limitations. A combination of these methods can provide a comprehensive understanding of the palindromic landscape of a genome.</p></div></div></div></div></div></div></div></div></div></div>]]></description>
	<dc:creator>BioStar</dc:creator>
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	<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/37302/fastani-fast-alignment-free-computation-of-whole-genome-average-nucleotide-identity-ani</guid>
	<pubDate>Fri, 13 Jul 2018 17:27:01 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37302/fastani-fast-alignment-free-computation-of-whole-genome-average-nucleotide-identity-ani</link>
	<title><![CDATA[FastANI:  fast alignment-free computation of whole-genome Average Nucleotide Identity (ANI)]]></title>
	<description><![CDATA[<p><span>FastANI is developed for fast alignment-free computation of whole-genome Average Nucleotide Identity (ANI). ANI is defined as mean nucleotide identity of orthologous gene pairs shared between two microbial genomes. FastANI supports pairwise comparison of both complete and draft genome assemblies. Its underlying procedure follows a similar workflow as described by&nbsp;</span><a href="http://www.ncbi.nlm.nih.gov/pubmed/17220447">Goris et al. 2007</a><span>. However, it avoids expensive sequence alignments and uses&nbsp;</span><a href="https://github.com/marbl/MashMap">Mashmap</a><span>&nbsp;as its MinHash based sequence mapping engine to compute the orthologous mappings and alignment identity estimates. Based on our experiments with complete and draft genomes, its accuracy is on par with&nbsp;</span><a href="http://enve-omics.ce.gatech.edu/ani/">BLAST-based ANI solver</a><span>&nbsp;and it achieves two to three orders of magnitude speedup. Therefore, it is useful for pairwise ANI computation of large number of genome pairs. More details about its speed, accuracy and potential applications are described here: "</span><a href="https://doi.org/10.1101/225342">High-throughput ANI Analysis of 90K Prokaryotic Genomes Reveals Clear Species Boundaries</a><span>".</span></p><p>Address of the bookmark: <a href="https://github.com/ParBLiSS/FastANI" rel="nofollow">https://github.com/ParBLiSS/FastANI</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40814/accesssyri-finding-genomic-rearrangements-and-local-sequence-differences-from-whole-genome-assemblies</guid>
	<pubDate>Sat, 01 Feb 2020 13:38:49 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40814/accesssyri-finding-genomic-rearrangements-and-local-sequence-differences-from-whole-genome-assemblies</link>
	<title><![CDATA[AccessSyRI: finding genomic rearrangements and local sequence differences from whole-genome assemblies]]></title>
	<description><![CDATA[<p><span>Access</span><span>SyRI: finding genomic rearrangements and</span><span>local sequence differences from whole-</span><span>genome assemblies</span><span><br></span></p>
<p><span><span>SyRI, a pairwise whole-genome comparison tool for chromosome-level assemblies. SyRI starts by finding rearranged regions and then searches for differences in the sequences, which are distinguished for residing in syntenic or rearranged regions. This distinction is important as rearranged regions are inherited differently compared to syntenic regions.</span></span></p>
<p><span><a href="https://genomebiology.biomedcentral.com/articles/10.1186/s13059-019-1911-0">https://genomebiology.biomedcentral.com/articles/10.1186/s13059-019-1911-0</a></span></p><p>Address of the bookmark: <a href="https://github.com/schneebergerlab/syri" rel="nofollow">https://github.com/schneebergerlab/syri</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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