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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/39872?offset=110</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/8639/edit-dna</guid>
	<pubDate>Wed, 05 Mar 2014 02:27:54 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/8639/edit-dna</link>
	<title><![CDATA[Edit DNA !!!]]></title>
	<description><![CDATA[<p>A genome-engineering tool known as Crispr may allow scientists to alter the DNA of humans, animals and plants, a research breakthrough that promises to make a significant impact on science and fighting diseases, according to a <a href="http://www.nytimes.com/2014/03/04/health/a-powerful-new-way-to-edit-dna.html">March 3 story in the <em>New York Times</em></a>. Scientists hope Crispr might also be used for genomic surgery, as it were, to correct errant genes that cause disease.</p><p>A rescently publication paper ( http://jb.asm.org/content/169/12/5429.long )shows significance of an unusual repeated DNA sequences next to a gene in a common bacterium, and their scientific significance. The sequences, it turns out, are part of a sophisticated immune system that bacteria use to fight viruses. And that system, whose very existence was unknown until about seven years ago, may provide scientists with unprecedented power to rewrite the code of life. This means a genome can be edited, much as a writer might change words or fix spelling errors. It allows &ldquo;customizing the genome of any cell or any species at will,&rdquo;.</p><p>Reference:</p><p>http://www.prweb.com/releases/2014/03/prweb11636031.htm</p><p>http://www.nytimes.com/2014/03/04/health/a-powerful-new-way-to-edit-dna.html?hpw&amp;rref=health</p><p>http://jb.asm.org/content/169/12/5429.long</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/23838/scripted-dna</guid>
	<pubDate>Mon, 17 Aug 2015 17:44:04 -0500</pubDate>
	<link>https://bioinformaticsonline.com/file/view/23838/scripted-dna</link>
	<title><![CDATA[Scripted DNA !!!]]></title>
	<description><![CDATA[<p>As per bioinformatician DNA is partially scripted ;) You dont believe in it. Please have a look at image carefully:)</p>]]></description>
	<dc:creator>Jit</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/23838" length="13498" type="image/gif" />
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32465/tetra-nucleotide-analysis</guid>
	<pubDate>Thu, 04 May 2017 05:07:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32465/tetra-nucleotide-analysis</link>
	<title><![CDATA[Tetra-Nucleotide Analysis]]></title>
	<description><![CDATA[<p>A tetra-nucleotide is a fragment of DNA sequence with 4 bases (e.g. AGTC or TTGG). Pride&nbsp;<em>et al.</em>&nbsp;(2003) showed that the frequency of tetra-nucleotides in bacterial genomes contain useful, albeit weak, phylogenetic signals. Even though tetra-nucleotide analysis (TNA) utilizes the information of whole genome, it is evident that it cannot replace other alignment-based phylogenetic methods such as&nbsp;<a href="https://chunlab.wordpress.com/orthoani/">OrthoANI</a>&nbsp;or&nbsp;16S rRNA phylogeny. However, TNA can be useful for&nbsp;phylogenetic characterization when whole genome or 16S rRNA gene information is not available. For example, a partial genomic fragment obtained from a metagenome can be identified by TNA (Teeling&nbsp;<em>et al.</em>, 2004). TNA is also fast enough that it can be&nbsp;used&nbsp;as a search engine against a large genome database.</p><p>Address of the bookmark: <a href="https://chunlab.wordpress.com/tetra-nucleotide-analysis/" rel="nofollow">https://chunlab.wordpress.com/tetra-nucleotide-analysis/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34386/slidesort-bpr</guid>
	<pubDate>Mon, 20 Nov 2017 09:19:52 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34386/slidesort-bpr</link>
	<title><![CDATA[SLIDESORT-BPR]]></title>
	<description><![CDATA[<p>Chromosomal rearrangement events are caused by abnormal breaking and rejoining of DNA molecules. They are responsible for many of the cancer related diseases. Detecting the DNA breaking and repairing mechanism, therefore, may offer vital clues about the pathologic causes and diagnostic/therapeutic target of these diseases. But this effort also poses considerable challenges, because the structural variations and the genomes are different from one person to another. Intermediate comparison via reference genome could lead to the loss information. Unlike the current methods which make use the reference genome, we developed a method to detect the breakpoint reads directly from observing the differences between two (or more) NGS short reads samples. Slidesort-BPR is a command line tool implemented in C++.</p><p>Address of the bookmark: <a href="https://github.com/ewijaya/slidesort-bpr" rel="nofollow">https://github.com/ewijaya/slidesort-bpr</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
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	<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>
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	<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/40856/3d-de-novo-assembly-3d-dna-pipeline</guid>
	<pubDate>Sun, 02 Feb 2020 13:41:55 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40856/3d-de-novo-assembly-3d-dna-pipeline</link>
	<title><![CDATA[3D de novo assembly (3D DNA) pipeline]]></title>
	<description><![CDATA[<p>For a detailed description of the pipeline and how it integrates with other tools designed by the Aiden Lab see&nbsp;<a href="http://aidenlab.org/assembly/manual_180322.pdf">Genome Assembly Cookbook</a>&nbsp;on&nbsp;<a href="http://aidenlab.org/assembly">http://aidenlab.org/assembly</a>.</p>
<p>For the original version of the pipeline and to reproduce the Hs2-HiC and the AaegL4 genomes reported in&nbsp;<a href="http://science.sciencemag.org/content/356/6333/92">(Dudchenko et al.,&nbsp;<em>Science</em>, 2017)</a>&nbsp;see the&nbsp;<a href="https://github.com/theaidenlab/3d-dna/tree/745779bdf64db6e55bddb70c24e9b58825938c33">original commit</a>.</p>
<p>For the detailed description of the merge section see&nbsp;<a href="https://github.com/theaidenlab/AGWG-merge">https://github.com/theaidenlab/AGWG-merge</a>.</p><p>Address of the bookmark: <a href="https://github.com/theaidenlab/3d-dna" rel="nofollow">https://github.com/theaidenlab/3d-dna</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/42023/encode3-a-collection-of-research-articles-and-related-content-describing-the-encyclopedia-of-dna-elements-its-datasets-and-tools</guid>
	<pubDate>Sat, 08 Aug 2020 08:25:21 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/42023/encode3-a-collection-of-research-articles-and-related-content-describing-the-encyclopedia-of-dna-elements-its-datasets-and-tools</link>
	<title><![CDATA[ENCODE3: A collection of research articles and related content describing the Encyclopedia of DNA Elements, its datasets and tools.]]></title>
	<description><![CDATA[<p>How cells, tissues and organisms interpret the information encoded in the genome has vital implications for our understanding of development, health and disease. Launched in 2003, the ENCyclopedia Of DNA Elements (ENCODE) project has the aim of mapping the functional elements in the human genome (later expanded to include model organisms).</p><p>During the first phase of ENCODE, published in 2007, microarray-based technologies were used to detect regions associated with transcription factors, certain histone modifications and open chromatin within a pre-specified 1% of the human genome.</p><p>ENCODE&rsquo;s second phase saw a switch to sequencing-based technologies, the addition of new assay types and the analysis of functional elements genome-wide, described in a collection of research articles in 2012.</p><p><span>The&nbsp;</span><a href="https://www.nature.com/articles/s41586-020-2493-4">Encyclopedia paper of ENCODE 3</a><span>, published in&nbsp;</span><em>Nature</em><span>, gives an overview of the various assays that were performed in human and mouse cell lines and tissues and describes a Registry of human and mouse candidate&nbsp;</span><em>cis</em><span>-regulatory elements (cCREs).</span></p><p>More at&nbsp;<a href="https://www.nature.com/immersive/d42859-020-00027-2/index.html">https://www.nature.com/immersive/d42859-020-00027-2/index.html</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44329/metabuli-%EB%B6%84%EB%A6%AC-improves-metagenomic-read-classification</guid>
	<pubDate>Sat, 03 Jun 2023 20:15:04 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44329/metabuli-%EB%B6%84%EB%A6%AC-improves-metagenomic-read-classification</link>
	<title><![CDATA[Metabuli 분리 improves metagenomic read classification]]></title>
	<description><![CDATA[<p><span>Metabuli 분리 improves metagenomic read classification through metamers, DNA-AA k-mers, to be sensitive and specific, recovering 99% and 98% of DNA or AA classifiers.</span></p>
<p>&nbsp;</p>
<p><span><span>Metabuli is metagenomic classifier that jointly analyze both DNA and amino acid (AA) sequences. DNA-based classifiers can make specific classifications, exploiting point mutations to distinguish close taxa. AA-based classifiers have higher sensitivity in detecting homology between query and reference sequences, leverageing higher conservation of AA sequences. Metabuli combines the information of both sequence types using a novel k-mer structure,&nbsp;</span><em>metamer</em><span>, to enable both specific and sensitive characterization of metagenomic samples. In addition, it can classify reads against a database of any size as long as it fits in the hard disk.</span> </span></p><p>Address of the bookmark: <a href="https://github.com/steineggerlab/Metabuli" rel="nofollow">https://github.com/steineggerlab/Metabuli</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
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	<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" />
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