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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/44525?offset=150</link>
	<atom:link href="https://bioinformaticsonline.com/related/44525?offset=150" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37572/gtdb-tk-a-toolkit-for-assigning-objective-taxonomic-classifications-to-bacterial-and-archaeal-genomes</guid>
	<pubDate>Wed, 22 Aug 2018 03:21:01 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37572/gtdb-tk-a-toolkit-for-assigning-objective-taxonomic-classifications-to-bacterial-and-archaeal-genomes</link>
	<title><![CDATA[GTDB-Tk: A toolkit for assigning objective taxonomic classifications to bacterial and archaeal genomes.]]></title>
	<description><![CDATA[<p>GTDB-Tk is a software toolkit for assigning objective taxonomic classifications to bacterial and archaeal genomes. It is computationally efficient and designed to work with recent advances that allow hundreds or thousands of metagenome-assembled genomes (MAGs) to be obtained directly from environmental samples. It can also be applied to isolate and single-cell genomes. The GTDB-Tk is open source and released under the GNU General Public License (Version 3).</p>
<p>GTDB-Tk is&nbsp;<span>under active development and validation</span>. Please independently confirm the GTDB-Tk predictions by manually inspecting the tree and bringing any discrepencies to our attention. Notifications about GTDB-Tk releases will be available through the ACE Twitter account (<a href="https://twitter.com/ace_uq">https://twitter.com/ace_uq</a>).</p><p>Address of the bookmark: <a href="https://github.com/Ecogenomics/GTDBTk" rel="nofollow">https://github.com/Ecogenomics/GTDBTk</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39856/tritex-sequence-assembly-pipeline-for-triticeae-genomes</guid>
	<pubDate>Tue, 20 Aug 2019 09:47:14 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39856/tritex-sequence-assembly-pipeline-for-triticeae-genomes</link>
	<title><![CDATA[TRITEX sequence assembly pipeline for Triticeae genomes]]></title>
	<description><![CDATA[<div>
<p>The pipeline is open-source and hosted in a public Bitbucket&nbsp;<a href="https://bitbucket.org/tritexassembly/tritexassembly.bitbucket.io/src/master/">repository</a>.</p>
</div>
<div>
<p>TRITEX has been run on highly inbred genotypes of barley (<em>Hordeum vulgare</em>), tetraploid wheat (<em>Triticum turgidum</em>) and hexaploid wheat (<em>T. aestivum</em>) with reasonable results: super-scaffold N50 values in the range of dozens of Mb and pseudomolecules with better gene space representation than a BAC-by-BAC assembly. It has never been tested and is not expected to work on heterozygous or autopolyploid genomes.</p>
</div>
<div>
<p>A protocol for generating chromosome-conformation capture sequencing (Hi-C) data suitable for use with the pipeline is described in&nbsp;<a href="https://bio-protocol.org/e2955">Himmelbach et al. 2018</a>. Refer to the&nbsp;<a href="https://www.10xgenomics.com/resources/technical-notes/">technical notes</a>&nbsp;of 10X Genomics on how to generate Chromium data.</p>
</div><p>Address of the bookmark: <a href="https://tritexassembly.bitbucket.io/" rel="nofollow">https://tritexassembly.bitbucket.io/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40699/kevler-reference-free-variant-discovery-in-large-eukaryotic-genomes</guid>
	<pubDate>Tue, 28 Jan 2020 03:21:53 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40699/kevler-reference-free-variant-discovery-in-large-eukaryotic-genomes</link>
	<title><![CDATA[Kevler: Reference-free variant discovery in large eukaryotic genomes]]></title>
	<description><![CDATA[<p><span>Welcome to&nbsp;</span><span>kevlar</span><span>, software for predicting&nbsp;</span><em>de novo</em><span>&nbsp;genetic variants without mapping reads to a reference genome! kevlar's&nbsp;</span><em>k</em><span>-mer abundance based method calls single nucleotide variants (SNVs), multinucleotide variants (MNVs), insertion/deletion variants (indels), and structural variants (SVs) simultaneously with a single simple model.&nbsp;</span></p>
<p><span>More at&nbsp;<a href="https://kevlar.readthedocs.io/en/latest/">https://kevlar.readthedocs.io/en/latest/</a></span></p>
<p><span><a href="https://www.cell.com/iscience/pdf/S2589-0042(19)30259-7.pdf">https://www.cell.com/iscience/pdf/S2589-0042(19)30259-7.pdf</a></span></p><p>Address of the bookmark: <a href="https://github.com/kevlar-dev/kevlar" rel="nofollow">https://github.com/kevlar-dev/kevlar</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41686/catbat-tool-for-taxonomic-classification-of-contigs-and-metagenome-assembled-genomes-mags</guid>
	<pubDate>Mon, 18 May 2020 10:53:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41686/catbat-tool-for-taxonomic-classification-of-contigs-and-metagenome-assembled-genomes-mags</link>
	<title><![CDATA[CAT/BAT: tool for taxonomic classification of contigs and metagenome-assembled genomes (MAGs)]]></title>
	<description><![CDATA[<p>Contig Annotation Tool (CAT) and Bin Annotation Tool (BAT) are pipelines for the taxonomic classification of long DNA sequences and metagenome assembled genomes (MAGs/bins) of both known and (highly) unknown microorganisms, as generated by contemporary metagenomics studies. The core algorithm of both programs involves gene calling, mapping of predicted ORFs against the nr protein database, and voting-based classification of the entire contig / MAG based on classification of the individual ORFs. CAT and BAT can be run from intermediate steps if files are formated appropriately (see <a href="https://github.com/dutilh/CAT#usage">Usage</a>).</p><p>Address of the bookmark: <a href="https://github.com/dutilh/CAT" rel="nofollow">https://github.com/dutilh/CAT</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/42325/published-a-dataset-of-363-genomes-from-approximately-92-percent-of-bird-families</guid>
	<pubDate>Thu, 19 Nov 2020 07:04:41 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/42325/published-a-dataset-of-363-genomes-from-approximately-92-percent-of-bird-families</link>
	<title><![CDATA[Published a dataset of 363 genomes from approximately 92 percent of bird families]]></title>
	<description><![CDATA[<div>A research team published a dataset of 363 genomes from approximately 92 percent of bird families and showed the significance of sampling dense organisms for biodiversity research. The study was jointly conducted by Chinese and international institutions and museums and was led by researchers from the Kunming Institute of Zoology (KIZ) of the Chinese Academy of Sciences (CAS). Total of 267 were newly published among the 363 sequenced genomes.&nbsp;They were mainly taken from samples of avian tissue kept in museums around the world, enabling researchers to sequence rare and endangered birds' genomes.</div><div>&nbsp;</div><div>Its descendants have adapted to a wide variety of ecological niches since the first bird formed more than 150 million years ago, giving rise to small, hovering hummingbirds, plunge-diving pelicans and showy paradise birds. More than 10,000 bird species live on the planet today - and now scientists are well on their way to capturing a full genetic image of that diversity.</div><div>&nbsp;</div><div>B10K is expanding its efforts to encompass the next stage of avian classification with 363 genomes complete. The team will sequence thousands of extra genomes in this process, attempting to represent each of the approximately 2,300 bird genera.</div><div>&nbsp;</div><div><img src="https://media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41586-020-2873-9/MediaObjects/41586_2020_2873_Fig1_HTML.png?as=webp" alt="image" style="border: 0px;"></div><div>&nbsp;</div><div>The genomic resource is expected to provide new insights on evolutionary processes in cross-species comparative studies and assist in efforts to protect species, according to the research findings reported as a cover story in the journal Nature.</div><div>&nbsp;</div><div>Ref at&nbsp;Dense sampling of bird diversity increases power of comparative genomics&nbsp;https://www.nature.com/articles/s41586-020-2873-9</div>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44318/proksee-in-depth-characterization-and-visualization-of-bacterial-genomes</guid>
	<pubDate>Tue, 09 May 2023 19:38:52 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44318/proksee-in-depth-characterization-and-visualization-of-bacterial-genomes</link>
	<title><![CDATA[Proksee: in-depth characterization and visualization of bacterial genomes]]></title>
	<description><![CDATA[<p><span>Proksee is an expert system for genome assembly, annotation and visualization. To begin using Proksee, provide a complete genome sequence, sequencing reads or a CGView/Proksee map JSON file.</span></p><p>Address of the bookmark: <a href="https://proksee.ca/" rel="nofollow">https://proksee.ca/</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28269/4dgenome</guid>
	<pubDate>Mon, 04 Jul 2016 00:44:55 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28269/4dgenome</link>
	<title><![CDATA[4DGenome]]></title>
	<description><![CDATA[<p><span>Records in 4DGenome are compiled through comprehensive literature curation of experimentally-derived and computationally-predicted interactions. The current release contains 4,433,071 experimentally-derived and 3,605,176 computationally-predicted interactions in 5 organisms. Experimental data cover both high throughput datasets and individiual focused studies.&nbsp;</span><br><br><span>All interaction data are freely available in a standardized file format. Records can be queried by genomic regions, gene names, organism, and detection technology.&nbsp;</span></p><p>Address of the bookmark: <a href="http://4dgenome.research.chop.edu/" rel="nofollow">http://4dgenome.research.chop.edu/</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/4574/tools-to-detect-synteny-blocks-regions-among-multiple-genomes</guid>
	<pubDate>Mon, 16 Sep 2013 17:12:02 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/4574/tools-to-detect-synteny-blocks-regions-among-multiple-genomes</link>
	<title><![CDATA[Tools to detect synteny blocks regions among multiple genomes]]></title>
	<description><![CDATA[<p>The synteny block (which etymologically means &ldquo;on the same ribbon&rdquo;) is a collection of contiguous genes located on the same chromosome. These block regions have mostly been preserved by genome rearrangements, and so synteny blocks from two related species (e.g., humans and mice) will be roughly similar but flipped around on the respective genomes. Ovcharenko et. al. define it as &lsquo;any conserved sequence blocks, regardless of whether it encompasses multiple genes, an area containing single genes, or areas devoid of known genes to be considers as synteny block as long as there is conservation at the sequence level. Today, however, biologists usually refer to synteny as the conservation of blocks of order within two sets of chromosomes that are being compared with each other. This concept can also be referred to as shared synteny. The NHBLI/NCBI Glossary define synteny as &ldquo;Two genes which occur on the same chromosome are syntenic; however, syntenic genes may or may not be "linked."</p><p>Now a day, geneticists have developed a language of their own. They are pouring lots of money and energy to read the entire genomic text and understand the gods own code ATGC. It is somewhat fascinating, not only for geneticist but also for non-biologist to know that there are several conserved blocks in genome which remain conserved over hundreds of millions of years. There have been several researches on conserved blocks and non-conserved regions to understand the mechanism and importance of all these regions (http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2675965/). The finding indicates conservation and rearrangements of certain evolutionary important genes play an important role in evolution/adaptive changes (http://www.nature.com/nature/journal/v491/n7424/abs/nature11622.html https://academic.oup.com/gbe/article/8/8/2442/2198198/Novel-Insights-into-Chromosome-Evolution-in-Birds , http://science.sciencemag.org/content/346/6215/1311).</p><p>But the puzzle remains open, how to correctly define the synteny (presence of two or more genes on the same chromosome) and conserved synteny (presence of two or more genes on chromosome of each of the two species) on several genomes.</p><p><img src="http://bioinformaticsonline.com/mod/photo/syntenyImg.jpg" alt="image" width="720" height="179" style="border: 0px; border: 0px;"></p><p>Figure: Image generated with Evolution Highway (EH) tool http://eh-demo.ncsa.illinois.edu/&nbsp;</p><p>Keeping the new approach to define conserved synteny in mind there have been various algorithms developed to identify the conserved homologous synteny blocks (HSB) amongst species. Some of them which were commonly used for synteny detections are:</p><p>SyntenyTracker ( http://www-app.igb.uiuc.edu/labs/lewin/donthu/Synteny_assign/html/),</p><p>SyntenyTracker was shown to be an efficient and accurate automated tool for defining HSBs using datasets that may contain minor errors resulting from limitations in map construction methodologies.</p><p>CoGe (http://genomevolution.org/CoGe/SynFind.pl )</p><p>Satsuma (http://evomics.org/learning/genomics/satsuma/)</p><p>Cinteny (http://cinteny.cchmc.org/) ,</p><p>Cinteny server can be used for finding regions syntenic across multiple genomes and measuring the extent of genome rearrangement using reversal distance as a measure.</p><p>OrthoCluster (http://krono.act.uji.es/noticias/orthocluster-a-new-tool-for-mining-syntenic-blocks)</p><p>A new tool for mining syntenic blocks in comparative genomics</p><p>SynMap (http://genomevolution.org/wiki/index.php/SynMap),</p><p>SyMAP (http://www.symapdb.org/)</p><p>SyMAP (Synteny Mapping and Analysis Program) v4.0 is an automated system for identifying and displaying genome synteny alignments. The genomes may be represented by sequenced chromosomes (pseudomolecules), by draft sequence contigs, or by FPC physical maps (with BAC-end or marker sequence).</p><p>http://genomevolution.org/CoGe/SynMap.pl</p><p>RegionMiner (http://www.genomatix.de/online_help/help_regionminer/orthologous.html)</p><p>SyntenyMiner is being developed as an application to visualize and interrogate comparisons among multiple complete genome sequences. http://syntenyminer.sourceforge.net/</p><p>AutoGRAPH ( http://autograph.genouest.org/),</p><p>AutoGRAPH is an integrated web server for multi-species comparative genomic analysis. It is designed for constructing and visualizing synteny maps between two or three species, determination and display of macrosynteny and microsynteny relationships among species, and for highlighting evolutionary breakpoints.</p><p>SynChro(http://www.lgm.upmc.fr/CHROnicle/SynChro.html)</p><p>SynChro is a tool designed to define conserved synteny blocks. It reconstructs synteny blocks between pairwise comparison of multiple genomes. The reconstructed synteny blocks may overlap each other, be included in one another or duplicated due to micro-rearrangements.</p><p>SyntenyView ( http://www.cbs.dtu.dk/dtucourse/cookbooks/nikob/exercises/gf1_output_5.html),</p><p>Ensembl 'SyntenyView' shows conservation of large-scale gene order between species pairs. A brief summary of the calculation method appears at the bottom of this help page.&nbsp; The left of a 'SyntenyView' page displays a diagram of chromosomes with blocks of conserved synteny. The right of a page shows homology matches between individual genes within syntenic blocks.</p><p>SynBrowse ( http://www.synbrowse.org/),</p><p>SynBrowse (Synteny Browser) is a generic sequence comparison tool for visualizing genome alignments both within and between species. It is intended to help scientists study and analyze synteny, homologous genes and other conserved elements between sequences. This software is useful in studying genome duplication and evolution. It can also aid in identifying uncharacterized genes, putative regulatory elements and novel structural features of study species by comparing to a well annotated reference sequence, thus enabling genome curators to refine and edit annotations of species that have incomplete genome annotations.</p><p>Sibelia (http://arxiv.org/abs/1307.7941).</p><p>A comparative genomic tool: It assists biologists in analysing the genomic variations that correlate with pathogens, or the genomic changes that help microorganisms adapt in different environments. Sibelia will also be helpful for the evolutionary and genome rearrangement studies for multiple strains of microorganisms.</p><p>GSV (http://cas-bioinfo.cas.unt.edu/gsv/homepage.php)</p><p>Genome Synteny Viewer allows users to upload files which contain synteny regions between two or more genomes and interactively visualize the synteny between them. GSV also allows users to upload annotation files to visualize annotated regions in addition to synteny regions.</p><p>MicroSyn (http://www.lgm.upmc.fr/CHROnicle/SynChro.html)</p><p>MicroSyn software as a means of detecting microsynteny in adjacent genomic regions surrounding genes in gene families. MicroSyn searches for conserved, flanking colinear homologous gene pairs between two genomic fragments to determine the relationship between two members in a gene family.</p><p>SynOrth (http://synorth.genereg.net/)</p><p>Synorth [s n &ocirc;rth], named in combination of "synteny" and "ortholog", is designed for the study of evolutionary changes of genomic regulatory blocks (GRBs) in vertebrate genomes, and especially the changes following the whole-genome duplication in teleost fish, by tracing the ortholog genes gain and loss in ancient synteny blocks.</p><p>SyDiG (http://www.ncbi.nlm.nih.gov/pubmed/21441096)</p><p>Uncovering Synteny in Distant Genomes.</p><p>MapSynteny&nbsp; (http://www.automatizacionysistemas.com/download.html)</p><p>MapSynteny is a macro in MS Excel&reg; able to create images to show the relationship between genetic maps and large sequences (scaffolds, chromosomes, BACs, etc.). Based on tab &ndash; delimited BLAST results and some formulas, a suitable image of syntenic relationships or physical mapping can be obtained. http://www.automatizacionysistemas.com/Poster_MapSynteny.pdf</p><p>One of the best synteny tutorial for beginer @&nbsp;http://www.nature.com/scitable/topicpage/synteny-inferring-ancestral-genomes-44022</p><p>Reference:</p><p><a href="http://www.nature.com/scitable/topicpage/synteny-inferring-ancestral-genomes-44022">http://www.nature.com/scitable/topicpage/synteny-inferring-ancestral-genomes-44022</a></p><p><a href="http://www.nature.com/nature/journal/v491/n7424/full/nature11622.html">http://www.nature.com/nature/journal/v491/n7424/full/nature11622.html</a></p><p><a href="http://en.wikipedia.org/wiki/Synteny">http://en.wikipedia.org/wiki/Synteny</a></p><p><a href="http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2675965/">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2675965/</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29276/murasaki</guid>
	<pubDate>Fri, 30 Sep 2016 10:22:30 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29276/murasaki</link>
	<title><![CDATA[Murasaki]]></title>
	<description><![CDATA[<p>Murasaki is an anchor alignment program that is</p>
<ul style="margin-left: 16px;">
<li>exteremely fast (17 CPU hours for whole Human x Mouse genome (with 40 nodes: 35 wall minutes), or 8 mammals in 21 CPU hours (42 wall minutes))</li>
<li>scalable (Arbitrarily parallelizable across multiple nodes using MPI)</li>
<li>memory efficient. (Even a single node with 16GB of ram can handle over 1Gbp of sequence)</li>
<li>unlimited by pattern length or selection</li>
<li>repeat tolerant</li>
</ul>
<p><img src="http://murasaki.dna.bio.keio.ac.jp/9mammals-small.png" width="500" height="375" alt="image" style="border: 0px;"></p><p>Address of the bookmark: <a href="http://murasaki.dna.bio.keio.ac.jp/wiki/index.php?Murasaki" rel="nofollow">http://murasaki.dna.bio.keio.ac.jp/wiki/index.php?Murasaki</a></p>]]></description>
	<dc:creator>Anjana</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30550/genomering-alignment-visualization-based-on-supergenome-coordinates</guid>
	<pubDate>Wed, 18 Jan 2017 10:24:10 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30550/genomering-alignment-visualization-based-on-supergenome-coordinates</link>
	<title><![CDATA[GenomeRing: alignment visualization based on SuperGenome coordinates]]></title>
	<description><![CDATA[<p>The number of completely sequenced genomes is continuously rising, allowing for comparative analyses of genomic variation. Such analyses are often based on whole-genome alignments to elucidate structural differences arising from insertions, deletions or from rearrangement events. Computational tools that can visualize genome alignments in a meaningful manner are needed to help researchers gain new insights into the underlying data. Such visualizations typically are either realized in a linear fashion as in genome browsers or by using a circular approach, where relationships between genomic regions are indicated by arcs. Both methods allow for the integration of additional information such as experimental data or annotations. However, providing a visualization that still allows for a quick and comprehensive interpretation of all important genomic variations together with various supplemental data, which may be highly heterogeneous, remains a challenge.</p>
<p>More at https://academic.oup.com/bioinformatics/article/28/12/i7/268598/GenomeRing-alignment-visualization-based-on</p><p>Address of the bookmark: <a href="http://it.informatik.uni-tuebingen.de/?page_id=185" rel="nofollow">http://it.informatik.uni-tuebingen.de/?page_id=185</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>

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