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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/38055?offset=10</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35907/alienness-rapid-detection-of-candidate-horizontal-gene-transfers-across-the-tree-of-life</guid>
	<pubDate>Mon, 12 Mar 2018 09:24:40 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35907/alienness-rapid-detection-of-candidate-horizontal-gene-transfers-across-the-tree-of-life</link>
	<title><![CDATA[alienness : Rapid Detection of Candidate Horizontal Gene Transfers across the Tree of Life]]></title>
	<description><![CDATA[<p><span>Horizontal gene transfer (HGT) is the transmission of genes between organisms by other means than parental to offspring inheritance. While it is prevalent in prokaryotes, HGT is less frequent in eukaryotes and particularly in Metazoa. Here, we propose Alienness, a taxonomy-aware web application available at&nbsp;</span>http://alienness.sophia.inra.fr</p>
<p>http://www.mdpi.com/2073-4425/8/10/248</p><p>Address of the bookmark: <a href="http://alienness.sophia.inra.fr/cgi/index.cgi" rel="nofollow">http://alienness.sophia.inra.fr/cgi/index.cgi</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44157/onezoom-tree-of-life-explorer</guid>
	<pubDate>Sat, 12 Nov 2022 09:29:08 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44157/onezoom-tree-of-life-explorer</link>
	<title><![CDATA[OneZoom tree of life explorer...]]></title>
	<description><![CDATA[<p>An interactive map of the evolutionary links between all living things known to science. Discover your favourites, see which species are under threat, and be amazed by the diversity of life on earth.</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://www.onezoom.org/" rel="nofollow">https://www.onezoom.org/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/36711/ancestral-sequence-reconstruction-steps</guid>
	<pubDate>Fri, 18 May 2018 08:28:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/36711/ancestral-sequence-reconstruction-steps</link>
	<title><![CDATA[Ancestral sequence reconstruction steps !]]></title>
	<description><![CDATA[<div><strong>Ancestral sequence reconstruction</strong>&nbsp;(<strong>ASR</strong>) &ndash; also known as&nbsp;<strong>ancestral gene</strong>/<strong>sequence reconstruction</strong>/<strong>resurrection</strong>&nbsp;&ndash; is a technique used in the study of&nbsp;molecular evolution. The method consists of the synthesis of an ancestral&nbsp;gene&nbsp;and expression of the corresponding ancestral&nbsp;protein.&nbsp;<a href="https://en.wikipedia.org/wiki/Ancestral_sequence_reconstruction#cite_note-thornton-1"></a>The idea of protein 'resurrection' was suggested in 1963 by Pauling and Zuckerkandl.<a href="https://en.wikipedia.org/wiki/Ancestral_sequence_reconstruction#cite_note-2"></a>&nbsp;Some early efforts were made in the eighties-nineties, led by the laboratory of&nbsp;Steven A. Benner, showing the potential of this technique &ndash; one that only started to be fulfilled in the post-genomic era.<a href="https://en.wikipedia.org/wiki/Ancestral_sequence_reconstruction#cite_note-3"></a>&nbsp;Thanks to the improvement of algorithms and of better sequencing and synthesis techniques, the method was developed further in the early 2000s to allow the resurrection of a greater variety of and much more ancient genes.<a href="https://en.wikipedia.org/wiki/Ancestral_sequence_reconstruction#cite_note-4"></a>&nbsp;Over the last decade, ancestral protein resurrection has developed as a strategy to reveal the mechanisms and dynamics of protein evolution.&nbsp;</div><div>&nbsp;</div><div>BEAST is the best way to predict the ancestral structure. but, I suggest following steps?</div><div>&nbsp;</div><div>1- Alignments "Mafft -&nbsp;<a href="https://www.researchgate.net/deref/http%3A%2F%2Fmafft.cbrc.jp%2Falignment%2Fsoftware%2Fsource.html" target="_blank">http://mafft.cbrc.jp/alignment/software/source.html</a>"</div><div>mafft --maxiterate 1000 --reorder --thread 24 --genafpair Dataset.fasta &gt; Dataset_Alig.fasta</div><div>&nbsp;</div><div>2- Your dataset has a good phylogenetic signal, is possible to perform with Tree-Puzzle "<a href="https://www.researchgate.net/deref/http%3A%2F%2Fwww.tree-puzzle.de" target="_blank">http://www.tree-puzzle.de</a>";</div><div>&nbsp;</div><div id="yui_3_14_1_1_1526649596608_1443">3 - This dataset which the saturation index, I perform with "<a href="https://www.researchgate.net/deref/http%3A%2F%2Fdambe.bio.uottawa.ca%2Fdambe.asp" target="_blank">http://dambe.bio.uottawa.ca/dambe.asp</a>";</div><div>&nbsp;</div><div>4- Has evidence of possible recombination in your dataset, the evaluate if this presence or absence, because this may to influence the grouping of clades, I perform with</div><div>---recombination</div><div>&nbsp;</div><div>4.1- Phi-test, implemented in SplitTree4"<a href="https://www.researchgate.net/deref/http%3A%2F%2Fwww.splitstree.org" target="_blank">http://www.splitstree.org</a>", (.nex file)</div><div>&nbsp;</div><div>4.2- GARD deployed in webserver in the DataMonkey "<a href="https://www.researchgate.net/deref/http%3A%2F%2Fwww.datamonkey.org%2F" target="_blank">http://www.datamonkey.org/</a>" - turning to the amino acid seaview -&gt; view proteins -&gt; save as ...) Ideally do a tree-based groups.</div><div>&nbsp;</div><div>4.3- RDP4 for download and installation on Windows in "<a href="https://www.researchgate.net/deref/http%3A%2F%2Fweb.cbio.uct.ac.za%2F~darren%2Frdp.html" target="_blank">http://web.cbio.uct.ac.za/~darren/rdp.html</a>"</div><div>&nbsp;</div><div>4.4- Hyphy (Mac, Windows, Linux) in "<a href="https://www.researchgate.net/deref/http%3A%2F%2Fhyphy.org%2Fw%2Findex.php%2FDownload" target="_blank">http://hyphy.org/w/index.php/Download</a>"</div><div>&nbsp;</div><div>4.5- Path-o-Gen (temporal structure of a tree input file -&gt; arquivo.tre)</div><div>These steps above, I call of pre-processing to inferences phylogenetic...</div><div>&nbsp;</div><div>5- Perform phylogenetic tree, used Bayesian Inference with Molecular Clock, but is necessary Clock Testing:</div><div>&nbsp;</div><div>- This step is performed with program Beast (Beauti, Beast and TreeAnnotator), and Tracer_v1.5 more FigTree to inspection.</div><div>&nbsp;</div><div>- Tutorials:&nbsp;<a href="https://www.researchgate.net/deref/http%3A%2F%2Fbeast.bio.ed.ac.uk%2Ftutorials" target="_blank">http://beast.bio.ed.ac.uk/tutorials</a></div><div>- Downloads:&nbsp;<a href="https://www.researchgate.net/deref/http%3A%2F%2Fbeast.bio.ed.ac.uk%2Fdownloads" target="_blank">http://beast.bio.ed.ac.uk/downloads</a></div>]]></description>
	<dc:creator>Surabhi Chaudhary</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33960/mgra-breakpoint-graphs-and-ancestral-genome-reconstructions</guid>
	<pubDate>Tue, 25 Jul 2017 08:48:25 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33960/mgra-breakpoint-graphs-and-ancestral-genome-reconstructions</link>
	<title><![CDATA[MGRA: Breakpoint graphs and ancestral genome reconstructions]]></title>
	<description><![CDATA[<p>MGRA (Multiple Genome Rearrangements and Ancestors) is a tool for reconstruction of ancestor genomes and evolutionary history of extant genomes.</p>
<p>It takes as an input a set of genomes represented as sequences of genes (or synteny blocks) and produces such sequences for ancestral genomes at the internal nodes of the phylogenetic tree.</p>
<p>The phylogenetic tree may be also specified completely or partially, in the latter case MGRA can reconstruct conserved ancestral regions (CARs) of the ancestral genome of interest.</p>
<p>Since version 2 MGRA supports gene insertion and deletions in addition to genome rearrangements and allows the input genomes to have different gene content.</p>
<p>It also can reconstruct most plausible phylogenetic tree based on the rearrangement characters.</p><p>Address of the bookmark: <a href="http://mgra.cblab.org/" rel="nofollow">http://mgra.cblab.org/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/34685/tools-for-bacterial-whole-genome-annotation</guid>
	<pubDate>Sat, 16 Dec 2017 17:37:47 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/34685/tools-for-bacterial-whole-genome-annotation</link>
	<title><![CDATA[Tools for bacterial whole genome annotation]]></title>
	<description><![CDATA[<p><a href="http://rast.nmpdr.org/">RAST</a>&nbsp;&ndash;&nbsp;Web tool (upload contigs), uses the subsystems in the SEED database and&nbsp;provides detailed annotation and pathway analysis. Takes several hours per genome but I think this is the best way to get a high quality annotation (if you have only a few genomes to annotate).</p><p><a href="http://www.vicbioinformatics.com/software.prokka.shtml">Prokka</a>&nbsp;&ndash;&nbsp;Standalone command line tool, takes just a few minutes per genome.&nbsp;This is the best way to get good quality annotation in a flash, which is particularly useful if you have loads of genomes or need to annotate a pangenome or metagenome. Note however that the quality of functional information is not as good as RAST, and you&nbsp;will need several extra steps if you want to do&nbsp;functional profiling and pathway analysis of your genome(s)&hellip; which is in-built in RAST.</p><p>NCBI Prokaryotic Genome Annotation Pipeline is designed to annotate bacterial and archaeal genomes (chromosomes and plasmids).</p><p>Genome annotation is a multi-level process that includes prediction of protein-coding genes, as well as other functional genome units such as structural RNAs, tRNAs, small RNAs, pseudogenes, control regions, direct and inverted repeats, insertion sequences, transposons and other mobile elements.</p><p><a href="https://www.ncbi.nlm.nih.gov/genome/annotation_prok/">PGAP</a>: NCBI has developed an automatic prokaryotic genome annotation pipeline that combines&nbsp;<em>ab initio</em>&nbsp;gene prediction algorithms with homology based methods. The first version of NCBI Prokaryotic Genome Automatic Annotation Pipeline (PGAAP;&nbsp;<a href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=pubmed&amp;dopt=Abstract&amp;list_uids=18416670">see Pubmed Article</a>) developed in 2005 has been replaced with an upgraded version that is capable of processing a larger data volume.&nbsp; NCBI's annotation pipeline depends on several internal databases and is not currently available for download or use outside of the NCBI environment.</p><p><a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC453985">BEACON</a> (automated tool for Bacterial GEnome Annotation ComparisON), a fast tool for an automated and a systematic comparison of different annotations of single genomes. The extended annotation assigns putative functions to many genes with unknown functions. BEACON is available under GNU General Public License version 3.0 and is accessible at:&nbsp;<a href="http://www.cbrc.kaust.edu.sa/BEACON/" target="pmc_ext">http://www.cbrc.kaust.edu.sa/BEACON/</a>.</p><p><a href="http://www.kegg.jp/blastkoala/">BlastKOLA</a>: Assigns K numbers to the user's sequence data by BLAST searches, respectively, against a nonredundant set of KEGG GENES. KOALA (KEGG Orthology And Links Annotation) is KEGG's internal annotation tool for K number assignment of KEGG GENES using SSEARCH computation. Annotate Sequence in KEGG Mapper and Pathogen Checker in KEGG Pathogen are special interfaces to this server and can be executed in an interactive mode. BlastKOALA is suitable for annotating fully sequenced genomes.</p><p><a href="http://www.sanger.ac.uk/science/tools/pagit">PAGIT</a>: Provides a toolkit for improving the quality of genome assemblies created via an assembly software. PAGIT compiled four tools: (i) ABACAS which classifies and orientates contigs and estimates the sizes of gaps between them; (ii) IMAGE uses paired-end reads to extend contigs and close gaps within the scaffolds; (iii) ICORN for identifying and correcting small errors in consensus sequences and; (iv) RATT for help annotation. The software was mainly created to analyze parasite genomes of up to about 300 Mb.</p><p><a href="http://www.yandell-lab.org/software/maker.html">MAKER: </a>A portable and easily configurable genome annotation pipeline. MAKER allows smaller eukaryotic and prokaryotic genome projects to independently annotate their genomes and to create genome databases. It identifies repeats, aligns ESTs and proteins to a genome, produces ab-initio gene predictions and automatically synthesizes these data into gene annotations having evidence-based quality values. MAKER's inputs are minimal and its ouputs can be directly loaded into a Generic Model Organism Database (GMOD). They can also be viewed in the Apollo genome browser; this feature of MAKER provides an easy means to annotate, view and edit individual contigs and BACs without the overhead of a database. MAKER is available for download and can be tested online via the MAKER Web Annotation Service (MWAS).</p><p><a href="https://www.sciencedirect.com/science/article/pii/S0167701215001207">MyPro</a> is a software pipeline for high-quality prokaryotic genome assembly and annotation. It was validated on 18 oral streptococcal strains to produce submission-ready, annotated draft genomes. MyPro installed as a virtual machine and supported by updated databases will enable biologists to perform quality prokaryotic genome assembly and annotation with ease.</p>]]></description>
	<dc:creator>Radha Agarkar</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42042/cluego-a-cytoscape-plug-in-that-visualizes-the-non-redundant-biological-terms-for-large-clusters-of-genes</guid>
	<pubDate>Thu, 13 Aug 2020 10:24:29 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42042/cluego-a-cytoscape-plug-in-that-visualizes-the-non-redundant-biological-terms-for-large-clusters-of-genes</link>
	<title><![CDATA[ClueGO: a Cytoscape plug-in that visualizes the non-redundant biological terms for large clusters of genes]]></title>
	<description><![CDATA[<p>ClueGO is a Cytoscape plug-in that visualizes the non-redundant biological terms for large clusters of genes in a functionally grouped network and it can be used in combination with GOlorize. The identifiers can be uploaded from a text file or interactively from a network of Cytoscape. The type of identifiers supported can be easely extended by the user. ClueGO performs single cluster analysis and comparison of clusters. From the ontology sources used, the terms are selected by different filter criteria. The related terms which share similar associated genes can be fused to reduce redundancy. The ClueGO network is created with kappa statistics and reflects the relationships between the terms based on the similarity of their associated genes. On the network, the node colour can be switched between functional groups and clusters distribution. ClueGO charts are underlying the specificity and the common aspects of the biological role. The significance of the terms and groups is automatically calculated. ClueGO is easy updatable with the newest files from Gene Ontology and KEGG.</p><p>Address of the bookmark: <a href="http://www.ici.upmc.fr/cluego/" rel="nofollow">http://www.ici.upmc.fr/cluego/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43620/ncbi-datasets-cli-quickstart-command-line-tools</guid>
	<pubDate>Tue, 07 Dec 2021 02:51:26 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43620/ncbi-datasets-cli-quickstart-command-line-tools</link>
	<title><![CDATA[ncbi-datasets-cli -- Quickstart: command line tools !]]></title>
	<description><![CDATA[<p><span>Install and use the NCBI Datasets command line tools</span></p>
<p>The NCBI Datasets datasets command line tools are&nbsp;<a href="https://www.ncbi.nlm.nih.gov/datasets/docs/v1/reference-docs/command-line/datasets/">datasets</a>&nbsp;and&nbsp;<a href="https://www.ncbi.nlm.nih.gov/datasets/docs/v1/reference-docs/command-line/dataformat/">dataformat</a>&nbsp;.</p>
<p>Use&nbsp;<span>datasets</span>&nbsp;to download biological sequence data across all domains of life from NCBI.</p>
<p>Use&nbsp;<span>dataformat</span>&nbsp;to convert metadata from&nbsp;<a href="https://jsonlines.org/" target="_blank">JSON Lines</a>&nbsp;format to other formats.</p>
<p><strong>Conda download:</strong></p>
<p>https://anaconda.org/conda-forge/ncbi-datasets-cli</p>
<p><strong>Buld Download</strong></p>
<p>&nbsp;https://www.ncbi.nlm.nih.gov/datasets/builder/?tax_id=29979</p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/datasets/docs/v1/quickstarts/command-line-tools/" rel="nofollow">https://www.ncbi.nlm.nih.gov/datasets/docs/v1/quickstarts/command-line-tools/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<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>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/26827/kamaleshwar-singh-lab</guid>
  <pubDate>Fri, 25 Mar 2016 10:46:49 -0500</pubDate>
  <link></link>
  <title><![CDATA[Kamaleshwar Singh Lab]]></title>
  <description><![CDATA[
<p>The focus of Dr. Singh’s research and teaching is on the molecular mechanistic basis for environmental carcinogen-induced genetic (DNA damage) and epigenetic changes, and susceptibility to human cancer development</p>

<p>More at http://www.tiehh.ttu.edu/dr.-kamaleshwar-singh.html</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27959/darkhorse</guid>
	<pubDate>Wed, 22 Jun 2016 05:37:38 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27959/darkhorse</link>
	<title><![CDATA[DarkHorse]]></title>
	<description><![CDATA[<p><em>DarkHorse</em>&nbsp;is a bioinformatic method for rapid, automated identification and ranking of phylogenetically atypical proteins on a genome-wide basis. It works by selecting potential ortholog matches from a reference database of amino acid sequences, then using these matches to calculate a lineage probability index (LPI) score for each genome protein.</p>
<p>LPI scores are inversely proportional to the phylogenetic distance between database match sequences and the query genome. These scores are useful not only for large-scale<em>de novo</em>&nbsp;predictions of horizontally transferred proteins, but can also serve as an independent quality control test for potential horizontal transfer candidates identified by alternative methods, especially those based on nucleic acid signatures. Candidates having high LPI scores are unlikely to have been horizontally transferred, since they are highly conserved among closely related organisms.</p>
<p>One unique and powerful feature of the DarkHorse HGT Candidate database is the opportunity to explore the phylogenetic background of potential HGT donors as well as recipients. The breadth of the database allows not only query sequences, but also their database match partners to be evaluated for sequence similarity or novelty compared to taxonomically related organisms.</p>
<p><em>DarkHorse</em>&nbsp;is configurable for varying degrees of phylogenetic granularity and protein sequence conservation. Users should consult the&nbsp;<a href="http://darkhorse.ucsd.edu/#references">references</a>&nbsp;cited below for a complete explanation of parameter selection and result interpretation. A brief&nbsp;<a href="http://darkhorse.ucsd.edu/tutorial.html">tutorial</a>&nbsp;page is also available on-line.</p><p>Address of the bookmark: <a href="http://darkhorse.ucsd.edu/download.html" rel="nofollow">http://darkhorse.ucsd.edu/download.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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