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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/39624?offset=20</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38041/synima-a-synteny-imaging-tool-for-annotated-genome-assemblies</guid>
	<pubDate>Tue, 30 Oct 2018 10:49:13 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38041/synima-a-synteny-imaging-tool-for-annotated-genome-assemblies</link>
	<title><![CDATA[Synima: a Synteny imaging tool for annotated genome assemblies]]></title>
	<description><![CDATA[<p><span>Synima written in Perl, which uses the graphical features of R. Synima takes orthologues computed from reciprocal best BLAST hits or OrthoMCL, and DAGchainer, and outputs an overview of genome-wide synteny in PDF. Each of these programs are included with the Synima package, and a pipeline for their use. Synima has a range of graphical parameters including size, colours, order, and labels, which are specified in a config file generated by the first run of Synima &ndash; and can be subsequently edited. Synima runs quickly on a command line to generate informative and publication quality figures. Synima is open source and freely available from&nbsp;</span><a href="https://github.com/rhysf/Synima" target="_blank">https://github.com/rhysf/Synima</a><span>&nbsp;under the MIT License.</span></p><p>Address of the bookmark: <a href="https://github.com/rhysf/Synima" rel="nofollow">https://github.com/rhysf/Synima</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38208/anitools-web-a-web-tool-for-fast-genome-comparison-within-multiple-bacterial-strains</guid>
	<pubDate>Wed, 14 Nov 2018 04:34:23 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38208/anitools-web-a-web-tool-for-fast-genome-comparison-within-multiple-bacterial-strains</link>
	<title><![CDATA[ANItools web: a web tool for fast genome comparison within multiple bacterial strains]]></title>
	<description><![CDATA[<p><span>ANItools is a software package written by PERL scripts that can be run in a Linux/Unix system. If you want to compare bacterial genomes and calculate their average nucleotide identity (ANI), you could download and run this program directly. Or you could send us the genome sequence by email. Then we will do the analysis work for you.</span></p>
<p><span>https://academic.oup.com/database/article/doi/10.1093/database/baw084/2630454</span></p><p>Address of the bookmark: <a href="http://ani.mypathogen.cn/" rel="nofollow">http://ani.mypathogen.cn/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38561/hawkeye-an-interactive-visual-analytics-tool-for-genome-assemblies</guid>
	<pubDate>Tue, 01 Jan 2019 11:56:17 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38561/hawkeye-an-interactive-visual-analytics-tool-for-genome-assemblies</link>
	<title><![CDATA[Hawkeye: an interactive visual analytics tool for genome assemblies]]></title>
	<description><![CDATA[<p><span>Genome sequencing remains an inexact science, and genome sequences can contain significant errors if they are not carefully examined. Hawkeye is our new visual analytics tool for genome assemblies, designed to aid in identifying and correcting assembly errors. Users can analyze all levels of an assembly along with summary statistics and assembly metrics, and are guided by a ranking component towards likely mis-assemblies. Hawkeye is freely available and released as part of the open source AMOS project&nbsp;</span><span><a href="http://amos.sourceforge.net/hawkeye"><span>http://amos.sourceforge.net/hawkeye</span></a></span><span>.</span></p>
<p>https://genomebiology.biomedcentral.com/articles/10.1186/gb-2007-8-3-r34</p><p>Address of the bookmark: <a href="http://amos.sourceforge.net/wiki/index.php?title=Hawkeye" rel="nofollow">http://amos.sourceforge.net/wiki/index.php?title=Hawkeye</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40994/biological-databases</guid>
	<pubDate>Wed, 12 Feb 2020 01:16:29 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40994/biological-databases</link>
	<title><![CDATA[Biological databases !]]></title>
	<description><![CDATA[<p>Now a days there are a lots of genomics databases available around the world. This bookmark is created to provide all links in one place ...</p>
<p>ftp://ftp.ncbi.nih.gov/genomes/</p>
<p>https://hgdownload.soe.ucsc.edu/downloads.html</p><p>Address of the bookmark: <a href="ftp://ftp.ncbi.nih.gov/genomes/" rel="nofollow">ftp://ftp.ncbi.nih.gov/genomes/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43867/genomeqc-a-quality-assessment-tool-for-genome-assemblies-and-gene-structure-annotations</guid>
	<pubDate>Thu, 19 May 2022 04:29:05 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43867/genomeqc-a-quality-assessment-tool-for-genome-assemblies-and-gene-structure-annotations</link>
	<title><![CDATA[GenomeQC: a quality assessment tool for genome assemblies and gene structure annotations]]></title>
	<description><![CDATA[<p><span>The GenomeQC web application is implemented in R/Shiny version 1.5.9 and Python 3.6 and is freely available at&nbsp;</span><a href="https://genomeqc.maizegdb.org/">https://genomeqc.maizegdb.org/</a><span>&nbsp;under the GPL license. All source code and a containerized version of the GenomeQC pipeline is available in the GitHub repository&nbsp;</span><a href="https://github.com/HuffordLab/GenomeQC">https://github.com/HuffordLab/GenomeQC</a><span>.</span></p>
<p>https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-020-6568-2</p><p>Address of the bookmark: <a href="https://github.com/HuffordLab/GenomeQC" rel="nofollow">https://github.com/HuffordLab/GenomeQC</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44483/baclife-an-automated-genome-mining-tool-for-identification-of-lifestyle-associated-genes</guid>
	<pubDate>Fri, 15 Mar 2024 04:59:14 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44483/baclife-an-automated-genome-mining-tool-for-identification-of-lifestyle-associated-genes</link>
	<title><![CDATA[bacLIFE: an automated genome mining tool for identification of lifestyle associated genes]]></title>
	<description><![CDATA[<p style="margin-top: 0px; margin-bottom: 16px; color: #1f2328; font-size: 16px; font-style: normal; font-weight: 400; text-align: start; background-color: #ffffff;" dir="auto">bacLIFE is a streamlined computational workflow that annotates bacterial genomes and performs large-scale comparative genomics to predict bacterial lifestyles and to pinpoint candidate genes, denominated<span>&nbsp;</span><strong style="font-weight: var(--base-text-weight-semibold, 600);">lifestyle-associated genes (LAGs)</strong>, and biosynthetic gene clusters associated with each lifestyle detected. This whole process is divided into different modules:</p>
<ul style="margin-top: 0px; margin-bottom: 16px; color: #1f2328; font-size: 16px; font-style: normal; font-weight: 400; text-align: start; background-color: #ffffff;" dir="auto">
<li><strong style="font-weight: var(--base-text-weight-semibold, 600);">Clustering module</strong><span>&nbsp;</span>Predicts, clusters and annotates the genes of every input genome</li>
<li style="margin-top: 0.25em;"><strong style="font-weight: var(--base-text-weight-semibold, 600);">Lifestyle prediction</strong><span>&nbsp;</span>Employs a machine learning model to forecast bacterial lifestyle or other specified metadata</li>
<li style="margin-top: 0.25em;"><strong style="font-weight: var(--base-text-weight-semibold, 600);">Analitical module (Shiny app)</strong><span>&nbsp;</span>Results from the previous modules are embedded in a user-friendly interface for comprehensive and interactive comparative genomics.</li>
</ul>
<p style="margin-top: 0px; margin-bottom: 16px; color: #1f2328; font-size: 16px; font-style: normal; font-weight: 400; text-align: start; background-color: #ffffff;" dir="auto">You can find the complete wiki here [<a href="https://github.com/Carrion-lab/bacLIFE/wiki/bacLIFE-wiki">https://github.com/Carrion-lab/bacLIFE/wiki/bacLIFE-wiki</a>]</p><p>Address of the bookmark: <a href="https://github.com/Carrion-lab/bacLIFE" rel="nofollow">https://github.com/Carrion-lab/bacLIFE</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31881/gbtools-interactive-visualization-of-metagenome-bins-in-r</guid>
	<pubDate>Sun, 26 Mar 2017 15:41:31 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31881/gbtools-interactive-visualization-of-metagenome-bins-in-r</link>
	<title><![CDATA[gbtools: Interactive Visualization of Metagenome Bins in R]]></title>
	<description><![CDATA[<p><span>We have developed gbtools, a software package that allows users to visualize metagenomic assemblies by plotting coverage (sequencing depth) and GC values of contigs, and also to annotate the plots with taxonomic information. Different sets of annotations, including taxonomic assignments from conserved marker genes or SSU rRNA genes, can be imported simultaneously; users can choose which annotations to plot. Bins can be manually defined from plots, or be imported from third-party binning tools and overlaid onto plots, such that results from different methods can be compared side-by-side. gbtools reports summary statistics of bins including marker gene completeness, and allows the user to add or subtract bins with each other.&nbsp;</span></p>
<p><span>Tool at&nbsp;https://github.com/kbseah/genome-bin-tools</span></p><p>Address of the bookmark: <a href="http://journal.frontiersin.org/article/10.3389/fmicb.2015.01451/full" rel="nofollow">http://journal.frontiersin.org/article/10.3389/fmicb.2015.01451/full</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36594/fragscaff-genome-assembly-with-contiguity-preserving-transposition</guid>
	<pubDate>Mon, 14 May 2018 04:28:14 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36594/fragscaff-genome-assembly-with-contiguity-preserving-transposition</link>
	<title><![CDATA[fragScaff: Genome Assembly with Contiguity Preserving Transposition]]></title>
	<description><![CDATA[<p>Contiguity preserving transposition and sequencing (CPT-seq) is an entirely in vitro means of generating libraries comprised of 9216 indexed pools, each of which contains thousands of sparsely sequenced long fragments ranging from 5 kilobases to &gt;1 megabase. This software, fragScaff, leverages coincidences between the content of different pools as a source of contiguity information for scaffolding de novo genome assemblies. FragScaff is complementary to Lachesis, providing midrange contiguity to support robust, accurate chromosome-scale de novo genome assemblies without the need for laborious in vivo cloning steps.</p>
<p>Further information about fragScaff, including source code, is available at:<a href="https://sourceforge.net/projects/fragscaff/files/">https://sourceforge.net/projects/fragscaff/files</a>.</p>
<p>Manuscript describing fragScaff was published as: Adey A, Kitzman JO, Burton JN, Daza R, Kumar A, Christiansen L, Ronaghi M, Amini S, L Gunderson K, Steemers FJ, Shendure J#.&nbsp;<em>In vitro, long-range sequence information for de novo genome assembly via transposase contiguity.</em>&nbsp;Genome Research 2014 Dec;24(12):2041-9. doi:&nbsp;<a href="http://dx.doi.org/10.1101/gr.178319.114">10.1101/gr.178319.114</a>. PubMed PMID:&nbsp;<a href="http://www.ncbi.nlm.nih.gov/pubmed/25327137">25327137</a>.</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/fragscaff/files/" rel="nofollow">https://sourceforge.net/projects/fragscaff/files/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44491/cgviewjs-is-a-circular-genome-viewing-tool</guid>
	<pubDate>Wed, 27 Mar 2024 11:16:24 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44491/cgviewjs-is-a-circular-genome-viewing-tool</link>
	<title><![CDATA[CGView.js is a Circular Genome Viewing tool]]></title>
	<description><![CDATA[<p>CGView.js is a&nbsp;<span>C</span>ircular&nbsp;<span>G</span>enome&nbsp;<span>View</span>ing tool for visualizing and interacting with small genomes. This software is an adaptation of the Java program&nbsp;<a href="https://paulstothard.github.io/cgview/">CGView</a>.</p>
<div>
<p>CGView.js is the genome viewer of Proksee, an expert system for genome assembly, annotation and visualization.</p>
<a href="https://proksee.ca/"></a></div>
<h1 id="features">Features</h1>
<ul>
<li>
<p>Circular and linear views of genomes</p>
</li>
<li>
<p>Capable of drawing genomes up to 10 Mbp with 1000's of features and 100's contigs</p>
</li>
<li>
<p>Smooth zooming down to the sequence level</p>
</li>
<li>
<p>Easily generate features and plots directly form the sequence (e.g. ORFs, GC-content and GC-Skew)</p>
</li>
<li>
<p>Save high resolution PNG maps up to 8000x8000px</p>
</li>
<li>
<p>Fully documented API for interacting with CGView.js maps</p>
</li>
</ul><p>Address of the bookmark: <a href="https://js.cgview.ca/" rel="nofollow">https://js.cgview.ca/</a></p>]]></description>
	<dc:creator>LEGE</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>

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