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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/44329?offset=20</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34914/ra-assembler-a-de-novo-dna-assembler-for-third-generation-sequencing-data</guid>
	<pubDate>Wed, 27 Dec 2017 20:36:54 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34914/ra-assembler-a-de-novo-dna-assembler-for-third-generation-sequencing-data</link>
	<title><![CDATA[Ra assembler - a de novo DNA assembler for third generation sequencing data]]></title>
	<description><![CDATA[<p>Integration of the Ra assembler - a de novo DNA assembler for third generation sequencing data developed on Faculty of Electrical Engineering and Computing (FER), Ruder Boskovic Institute (RBI) and Genome Institute of Singapore (GIS).</p>
<p>Ra is in development since 2014 in the form of several separate components that used to be run individually.<br>This project aims to ease the usage of Ra by integrating it into a complete de novo assembly tool.</p>
<p>Unlike other state-of-the-art assemblers,&nbsp;<span>Ra does not have an error correction step.</span>&nbsp;Instead, it relies on detecting overlaps using a very sensitive and specific overlapper ("graphmap -w owler",&nbsp;<a href="https://github.com/isovic/graphmap">https://github.com/isovic/graphmap</a>) and constructing and reducing an overlap graph (Ra layout,&nbsp;<a href="https://github.com/mariokostelac/ra">https://github.com/mariokostelac/ra</a>).</p><p>Address of the bookmark: <a href="https://github.com/mariokostelac/ra-integrate/" rel="nofollow">https://github.com/mariokostelac/ra-integrate/</a></p>]]></description>
	<dc:creator>biogeek</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36607/tarean-a-computational-tool-for-identification-and-characterization-of-satellite-dna-from-unassembled-short-reads</guid>
	<pubDate>Tue, 15 May 2018 02:53:11 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36607/tarean-a-computational-tool-for-identification-and-characterization-of-satellite-dna-from-unassembled-short-reads</link>
	<title><![CDATA[TAREAN: A computational tool for identification and characterization of satellite DNA from unassembled short reads]]></title>
	<description><![CDATA[<p><strong>TA</strong>ndem&nbsp;<strong>RE</strong>peat&nbsp;<strong>AN</strong>alyzer -TAREAN &ndash; is a computational pipeline for&nbsp;<strong>unsupervised identification of satellite repeats</strong>&nbsp;from unassembled sequence reads. The pipeline uses low-pass whole genome sequence reads and performs their graph-based clustering. Resulting clusters, representing all types of repeats, are then examined for the presence of circular structures and putative satellite repeats are reported.</p>
<p><em><strong>How to use TAREAN</strong></em>:</p>
<ul>
<li>Install a local instance of the pipeline using its source code available from&nbsp;<a href="https://bitbucket.org/petrnovak/repex_tarean" target="_blank" title="TAREAN source code">bitbucket repository</a>.</li>
<li>Use&nbsp; public Galaxy-based server at&nbsp;<a href="https://repeatexplorer-elixir.cerit-sc.cz/" target="_blank">https://repeatexplorer-elixir.cerit-sc.cz/</a>. The server is provided in frame of the&nbsp;<a href="https://www.elixir-czech.cz/" target="_blank">Elixir CZ project</a>&nbsp;and is maintained by&nbsp;<a href="https://www.cesnet.cz/" target="_blank">CESNET</a>&nbsp;and&nbsp;<a href="https://www.cerit-sc.cz/en/index.html" target="_blank">CERIT-SC</a>. Simple registration is required to use this service.</li>
</ul>
<p>Development of TAREAN was supported by&nbsp;<a href="https://www.elixir-czech.cz/" target="_blank" title="ELIXIR-CZ">ELIXIR CZ</a>&nbsp;research infrastructure project (MEYS Grant No: LM2015047).</p>
<p><strong><em>References</em></strong></p>
<p>Novak, P., Avila Robledillo, L., Koblizkova, A., Vrbova, I., Neumann, P., Macas, J. (2017) &ndash;&nbsp;<a href="https://academic.oup.com/nar/article/3574061/" target="_blank">TAREAN: a computational tool for identification and characterization of satellite DNA from unassembled short reads</a>.&nbsp;<em>Nucleic Acids Res.</em>, doi:10.1093/nar/gkx257</p><p>Address of the bookmark: <a href="https://bitbucket.org/petrnovak/repex_tarean" rel="nofollow">https://bitbucket.org/petrnovak/repex_tarean</a></p>]]></description>
	<dc:creator>Surabhi Chaudhary</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37987/ropebwt2-incremental-construction-of-fm-index-for-dna-sequences</guid>
	<pubDate>Thu, 25 Oct 2018 04:48:54 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37987/ropebwt2-incremental-construction-of-fm-index-for-dna-sequences</link>
	<title><![CDATA[RopeBWT2: Incremental construction of FM-index for DNA sequences]]></title>
	<description><![CDATA[<p><span>RopeBWT2 is an tool for constructing the FM-index for a collection of DNA sequences. It works by incrementally inserting one or multiple sequences into an existing pseudo-BWT position by position, starting from the end of the sequences. This algorithm can be largely considered a mixture of&nbsp;</span><a href="http://dx.doi.org/10.1007/978-3-642-21458-5_20">BCR</a><span>&nbsp;and&nbsp;</span><a href="http://dfmi.sourceforge.net/">dynamic FM-index</a><span>. Nonetheless, ropeBWT2 is unique in that it may&nbsp;</span><em>implicitly</em><span>sort the input into reverse lexicographical order (RLO) or reverse-complement lexicographical order (RCLO) while building the index.</span></p><p>Address of the bookmark: <a href="https://github.com/lh3/ropebwt2" rel="nofollow">https://github.com/lh3/ropebwt2</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40611/deepvariant-an-analysis-pipeline-that-uses-a-deep-neural-network-to-call-genetic-variants-from-next-generation-dna-sequencing-data</guid>
	<pubDate>Sat, 25 Jan 2020 13:28:09 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40611/deepvariant-an-analysis-pipeline-that-uses-a-deep-neural-network-to-call-genetic-variants-from-next-generation-dna-sequencing-data</link>
	<title><![CDATA[DeepVariant : an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.]]></title>
	<description><![CDATA[<p><span>DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.</span></p>
<p><span><span>DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data. DeepVariant relies on&nbsp;</span><a href="https://github.com/google/nucleus">Nucleus</a><span>, a library of Python and C++ code for reading and writing data in common genomics file formats (like SAM and VCF) designed for painless integration with the&nbsp;</span><a href="https://www.tensorflow.org/">TensorFlow</a><span>&nbsp;machine learning framework.</span></span></p>
<p><span><a href="https://ai.googleblog.com/2017/12/deepvariant-highly-accurate-genomes.html">https://ai.googleblog.com/2017/12/deepvariant-highly-accurate-genomes.html</a></span></p>
<p><span><a href="https://www.biorxiv.org/content/10.1101/092890v6">https://www.biorxiv.org/content/10.1101/092890v6</a></span></p>
<p><span><img src="https://4.bp.blogspot.com/-2KlXZO60sWE/WiGc8qlZfxI/AAAAAAAACOs/s1pNiKI8jsAvJLr1E_po5udDO8eObm_awCLcBGAs/s640/image3.png" width="640" height="427" alt="image" style="border: 0px;"></span></p><p>Address of the bookmark: <a href="https://github.com/google/deepvariant" rel="nofollow">https://github.com/google/deepvariant</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41825/hnadock-a-nucleic-acid-docking-server-for-modeling-rnadna%E2%80%93rnadna-3d-complex-structures</guid>
	<pubDate>Thu, 04 Jun 2020 23:19:07 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41825/hnadock-a-nucleic-acid-docking-server-for-modeling-rnadna%E2%80%93rnadna-3d-complex-structures</link>
	<title><![CDATA[HNADOCK: a nucleic acid docking server for modeling RNA/DNA–RNA/DNA 3D complex structures]]></title>
	<description><![CDATA[<p><span>The HNADOCK server is to predict the binding complex structure between two nucleic acid molecules through a hierarchical docking algorihtm of an FFT-based global search strategy and an intrinsic scoring function for nucleic acid interactions. Users are required to provide the three-dimensional (3D) structures of the two molecules to be docked.&nbsp;</span></p><p>Address of the bookmark: <a href="http://huanglab.phys.hust.edu.cn/hnadock/" rel="nofollow">http://huanglab.phys.hust.edu.cn/hnadock/</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</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>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44663/svbyeye-r-package-to-visualize-alignments-between-two-or-multiple-dna-sequences</guid>
	<pubDate>Tue, 17 Sep 2024 02:34:57 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44663/svbyeye-r-package-to-visualize-alignments-between-two-or-multiple-dna-sequences</link>
	<title><![CDATA[SVbyEye: R Package to visualize alignments between two or multiple DNA sequences]]></title>
	<description><![CDATA[<p dir="auto">R Package to visualize alignments between two or multiple DNA sequences including<br>a number of functionalities to facilitate processing of alignments in PAF format.</p>
<p dir="auto"><span>SVbyEye, an open-source R package to visualize and annotate sequence-to-sequence alignments along with various functionalities to process alignments in PAF format. The tool facilitates the characterization of complex SVs in the context of sequence homology helping resolve the mechanisms underlying their formation. Availability and implementation SVbyEye is available at https://github.com/daewoooo/SVbyEye.</span></p>
<p dir="auto">Author: David Porubsky</p><p>Address of the bookmark: <a href="https://github.com/daewoooo/SVbyEye" rel="nofollow">https://github.com/daewoooo/SVbyEye</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/42693/dna-rna-meme</guid>
	<pubDate>Thu, 28 Jan 2021 11:23:14 -0600</pubDate>
	<link>https://bioinformaticsonline.com/file/view/42693/dna-rna-meme</link>
	<title><![CDATA[DNA RNA MEME]]></title>
	<description><![CDATA[<p>Explain the DNA and RNA with picture ...</p>]]></description>
	<dc:creator>Neel</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/42693" length="41627" type="image/jpeg" />
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34420/rita-rapid-identification-of-high-confidence-taxonomic-assignments-for-metagenomic-data</guid>
	<pubDate>Mon, 27 Nov 2017 08:25:33 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34420/rita-rapid-identification-of-high-confidence-taxonomic-assignments-for-metagenomic-data</link>
	<title><![CDATA[RITA: Rapid identification of high-confidence taxonomic assignments for metagenomic data]]></title>
	<description><![CDATA[<p>RITA is a standalone software package and Web server for taxonomic assignment of metagenomic sequence reads. By combining homology predictions from BLAST or UBLAST with compositional classifications from a Naive Bayes classifier, RITA is able to achieve very high accuracy on short reads. Unlike other hybrid approaches which combine these predictions for all sequences to be classified, RITA uses a pipeline to first identify cases where both types of classifier are in agreement, which constitute the highest-confidence set. Sequences not classified in this manner are subjected to a series of downstream classification steps.</p>
<p>This work has been accepted for publication:</p>
<p>MacDonald NJ, Parks DH, and Beiko RG. Rapid identification of taxonomic assignments. Accepted to&nbsp;<em>Nucleic Acids Research</em>&nbsp;April 4, 2012.</p>
<p>If you have any questions or bug reports, please let us know at &lt;beiko@cs.dal.ca&gt;.</p><p>Address of the bookmark: <a href="http://kiwi.cs.dal.ca/Software/RITA" rel="nofollow">http://kiwi.cs.dal.ca/Software/RITA</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33011/grinder-biogrinder-a-versatile-omics-shotgun-and-amplicon-sequencing-read-simulator</guid>
	<pubDate>Wed, 24 May 2017 08:41:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33011/grinder-biogrinder-a-versatile-omics-shotgun-and-amplicon-sequencing-read-simulator</link>
	<title><![CDATA[Grinder / Biogrinder - A versatile omics shotgun and amplicon sequencing read simulator]]></title>
	<description><![CDATA[<p><span>Grinder is a versatile program to create random shotgun and amplicon sequence libraries based on DNA, RNA or proteic reference sequences provided in a FASTA file. </span></p>
<p><span>Grinder can produce genomic, metagenomic, transcriptomic, metatranscriptomic, proteomic, metaproteomic shotgun and amplicon datasets from current sequencing technologies such as Sanger, 454, Illumina. These simulated datasets can be used to test the accuracy of bioinformatic tools under specific hypothesis, e.g. with or without sequencing errors, or with low or high community diversity. Grinder may also be used to help decide between alternative sequencing methods for a sequence-based project, e.g. should the library be paired-end or not, how many reads should be sequenced.</span></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/biogrinder/files/biogrinder/" rel="nofollow">https://sourceforge.net/projects/biogrinder/files/biogrinder/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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