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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/44589?offset=0</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38804/grabb-selective-assembly-of-genomic-regions-a-new-niche-for-genomic-research</guid>
	<pubDate>Sat, 26 Jan 2019 18:58:16 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38804/grabb-selective-assembly-of-genomic-regions-a-new-niche-for-genomic-research</link>
	<title><![CDATA[GRAbB: Selective Assembly of Genomic Regions, a New Niche for Genomic Research]]></title>
	<description><![CDATA[<p><span>GRAbB is shown to be more efficient than MITObim in terms of speed, memory and disk usage. The other functionalities (handling multiple targets simultaneously and extracting homologous regions) of the new program are not matched by other programs. The program is available with explanatory documentation at&nbsp;</span><a href="https://github.com/b-brankovics/grabb">https://github.com/b-brankovics/grabb</a><span>. GRAbB has been tested on Ubuntu (12.04 and 14.04), Fedora (23), CentOS (7.1.1503) and Mac OS X (10.7). Furthermore, GRAbB is available as a docker repository: brankovics/grabb (</span><a href="https://hub.docker.com/r/brankovics/grabb/">https://hub.docker.com/r/brankovics/grabb/</a><span>).</span></p><p>Address of the bookmark: <a href="https://github.com/b-brankovics/grabb" rel="nofollow">https://github.com/b-brankovics/grabb</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44292/gget</guid>
	<pubDate>Sat, 01 Apr 2023 09:42:07 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44292/gget</link>
	<title><![CDATA[gget]]></title>
	<description><![CDATA[<p><code>gget</code><span>&nbsp;is a free, open-source command-line tool and Python package that enables efficient querying of genomic databases.&nbsp;</span><code>gget</code><span>&nbsp;consists of a collection of separate but interoperable modules, each designed to facilitate one type of database querying in a single line of code.</span></p>
<p><span><img src="https://github.com/pachterlab/gget/raw/main/figures/gget_overview.png?raw=true" alt="image" style="border: 0px;"></span></p><p>Address of the bookmark: <a href="https://github.com/pachterlab/gget" rel="nofollow">https://github.com/pachterlab/gget</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36935/assemblytics-delta-file-to-analyze-alignments-of-an-assembly-to-another-assembly-or-a-reference-genome</guid>
	<pubDate>Thu, 14 Jun 2018 07:31:00 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36935/assemblytics-delta-file-to-analyze-alignments-of-an-assembly-to-another-assembly-or-a-reference-genome</link>
	<title><![CDATA[assemblytics: delta file to analyze alignments of an assembly to another assembly or a reference genome]]></title>
	<description><![CDATA[Download and install MUMmer
Align your assembly to a reference genome using nucmer (from MUMmer package)
$ nucmer -maxmatch -l 100 -c 500 REFERENCE.fa ASSEMBLY.fa -prefix OUT
Consult the MUMmer manual if you encounter problems

Optional: Gzip the delta file to speed up upload (usually 2-4X faster)
$ gzip OUT.delta
Then use the OUT.delta.gz file for upload.
Upload the .delta or delta.gz file (view example) to Assemblytics
Important: Use only contigs rather than scaffolds from the assembly. This will prevent false positives when the number of Ns in the scaffolded sequence does not match perfectly to the distance in the reference.

The unique sequence length required represents an anchor for determining if a sequence is unique enough to safely call variants from, which is an alternative to the mapping quality filter for read alignment.

http://assemblytics.com/<p>Address of the bookmark: <a href="http://assemblytics.com/" rel="nofollow">http://assemblytics.com/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26587/last</guid>
	<pubDate>Wed, 09 Mar 2016 14:27:01 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26587/last</link>
	<title><![CDATA[LAST]]></title>
	<description><![CDATA[<p style="text-align: center;"><img src="http://last.cbrc.jp/lastwebfig.png" alt="sketch of  similar regions in sequences" style="border: 0px;"></p>
<p>LAST can:</p>
<ul>
<li>Handle <strong>big</strong> sequence data, e.g:
<ul>
<li>Compare two vertebrate genomes</li>
<li>Align billions of DNA reads to a genome</li>
</ul>
</li>
<li>Indicate the <a href="http://lastweb.cbrc.jp/about.html">reliability</a> of each aligned column.</li>
<li>Use sequence quality data <a href="http://nar.oxfordjournals.org/content/38/7/e100.abstract">properly</a>.</li>
<li>Compare DNA to proteins, with frameshifts.</li>
<li>Compare PSSMs to sequences</li>
<li>Calculate the likelihood of chance similarities between random sequences.</li>
<li>Do split and spliced alignment.</li>
<li><a href="http://last.cbrc.jp/doc/last-train.html">Train</a> alignment parameters for unusual kinds of sequence (e.g. nanopore).</li>
</ul><p>Address of the bookmark: <a href="http://last.cbrc.jp/" rel="nofollow">http://last.cbrc.jp/</a></p>]]></description>
	<dc:creator>Archana Malhotra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43799/kast</guid>
	<pubDate>Wed, 23 Feb 2022 08:28:36 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43799/kast</link>
	<title><![CDATA[KAST]]></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>Neel</dc:creator>
</item>
<item>
	<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>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/44342/ncbi-datasets%E2%80%AFpages</guid>
	<pubDate>Wed, 12 Jul 2023 06:29:31 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/44342/ncbi-datasets%E2%80%AFpages</link>
	<title><![CDATA[NCBI Datasets pages]]></title>
	<description><![CDATA[<p>Update! Assembly and Genome record pages now redirect to new NCBI Datasets pages. NCBI Datasets is a new resource that makes it easier to find and download genome data. Learn more: https://ncbiinsights.ncbi.nlm.nih.gov/2023/07/11/ncbi-datasets-genome-assembly-pages/&nbsp;<a href="https://ow.ly/GU3o50P8QH4"></a><a href="https://www.linkedin.com/feed/hashtag/?keywords=ncbicgr&amp;highlightedUpdateUrns=urn%3Ali%3Aactivity%3A7084592728260386816">#NCBICGR</a></p><p><span>Effective July 10, 2023, NCBI&rsquo;s Assembly and Genome record pages now redirect to&nbsp;</span>new<a href="https://www.ncbi.nlm.nih.gov/datasets/?utm_source=ncbi_insights&amp;utm_medium=referral&amp;utm_campaign=datasets-genome-assembly-redirect-20230711"> NCBI Datasets </a><span>pages. As&nbsp;</span><a href="https://ncbiinsights.ncbi.nlm.nih.gov/2023/03/07/ncbi-datasets-genome-taxonomy-pages/?utm_source=ncbi_insights&amp;utm_medium=referral&amp;utm_campaign=datasets-genome-assembly-redirect-20230711">previously announced</a><span>, these updates are part of our ongoing effort to modernize and improve your user experience. NCBI Datasets is a new resource that makes it easier to find and download genome data.  </span><span>&nbsp;</span></p><h5>The following pages have been updated:</h5><ul>
<li><span>The NCBI Assembly record pages now redirect to the new </span><a href="https://www.ncbi.nlm.nih.gov/datasets/genome/GCF_023065955.2/?utm_source=ncbi_insights&amp;utm_medium=referral&amp;utm_campaign=datasets-genome-assembly-redirect-20230711"><span>NCBI Datasets</span><strong><span> </span></strong><span>Genome</span></a><span> </span><span>record pages that describe assembled genomes and provide links to related NCBI tools such as Genome Data Viewer and BLAST. </span><span>&nbsp;</span></li>
<li><span>The NCBI</span><strong> </strong><span>Genome record pages now redirect to the </span><a href="https://www.ncbi.nlm.nih.gov/datasets/taxonomy/9644/?utm_source=ncbi_insights&amp;utm_medium=referral&amp;utm_campaign=datasets-genome-assembly-redirect-20230711"><span>NCBI Datasets</span><strong><span> </span></strong><span>Taxonomy</span></a><span> </span><span>record pages that provide a taxonomy-focused portal to genes, genomes, and additional NCBI resources.  </span><span>&nbsp;</span></li>
</ul><p><span>During this transition, you will have the option to return to the legacy Genome and Assembly record pages. We will remove the legacy pages in early 2024. </span><span>&nbsp;</span></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37820/s-plot2-rapid-visual-and-statistical-analysis-of-genomic-sequences</guid>
	<pubDate>Tue, 02 Oct 2018 17:57:27 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37820/s-plot2-rapid-visual-and-statistical-analysis-of-genomic-sequences</link>
	<title><![CDATA[S-plot2: Rapid Visual and Statistical Analysis of Genomic 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>Address of the bookmark: <a href="https://bitbucket.org/lkalesinskas/splot" rel="nofollow">https://bitbucket.org/lkalesinskas/splot</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44555/ultra-ultra-locates-tandemly-repetitive-areas-effective-labeling-of-repetitive-genomic-sequence</guid>
	<pubDate>Sat, 08 Jun 2024 16:03:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44555/ultra-ultra-locates-tandemly-repetitive-areas-effective-labeling-of-repetitive-genomic-sequence</link>
	<title><![CDATA[ULTRA (ULTRA Locates Tandemly Repetitive Areas) : Effective Labeling of Repetitive Genomic Sequence]]></title>
	<description><![CDATA[<p dir="auto">ULTRA is a tool to find and annotate tandem repeats inside genomic sequence. It is able to find repeats of any length and of any period (up to a maximum period of 4000). It can find highly decayed repeats missed by other software, and it will also be able to find very large repeats in highly repetitive sequence, regardless of the size of sequence or length of repeats. ULTRA offers meaningful annotation scores and can produce annotation P-values at user request.</p>
<p dir="auto">More at&nbsp;https://www.biorxiv.org/content/10.1101/2024.06.03.597269v1</p><p>Address of the bookmark: <a href="https://github.com/TravisWheelerLab/ULTRA" rel="nofollow">https://github.com/TravisWheelerLab/ULTRA</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33983/web-apollo-a-web-based-genomic-annotation-editing-platform</guid>
	<pubDate>Fri, 28 Jul 2017 04:48:17 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33983/web-apollo-a-web-based-genomic-annotation-editing-platform</link>
	<title><![CDATA[Web Apollo: a web-based genomic annotation editing platform]]></title>
	<description><![CDATA[<p><span>Web Apollo is the first instantaneous, collaborative genomic annotation editor available on the web. One of the natural consequences following from current advances in sequencing technology is that there are more and more researchers sequencing new genomes. These researchers require tools to describe the functional features of their newly sequenced genomes. With Web Apollo researchers can use any of the common browsers (for example, Chrome or Firefox) to jointly analyze and precisely describe the features of a genome in real time, whether they are in the same room or working from opposite sides of the world.</span></p><p>Address of the bookmark: <a href="http://genomearchitect.github.io/" rel="nofollow">http://genomearchitect.github.io/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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