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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/34562?offset=110</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37579/cbs-comparative-microbial-genomics-group-biotools-download-page</guid>
	<pubDate>Wed, 22 Aug 2018 21:59:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37579/cbs-comparative-microbial-genomics-group-biotools-download-page</link>
	<title><![CDATA[CBS Comparative Microbial Genomics group - BioTools download page]]></title>
	<description><![CDATA[<div id="section2">
<p>he CMG-biotools system presents a stand-alone interface for comparative microbial genomics. The package is a customized operating system, based on Xubuntu 10.10, available through the open source Ubuntu project. The system can be installed on a virtual computer, allowing the user to run the system alongside any other operating system. Source codes for all programs are provided under GNU license, which makes it possible to transfer the programs to other systems if so desired. We here demonstrate the package by comparing and analyzing the diversity within the class&nbsp;<em>Negativicutes</em>, represented by 31 genomes including 10 genera. The analyses include 16S rRNA phylogeny, basic DNA and codon statistics, proteome comparisons using BLAST and graphical analyses of DNA structures.</p>
<p>&nbsp;Paper:&nbsp;http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0060120</p>
</div>
<div id="section3"><a name="" title="Conclusion"></a><span></span></div><p>Address of the bookmark: <a href="http://www.cbs.dtu.dk/biotools/CMGtools/" rel="nofollow">http://www.cbs.dtu.dk/biotools/CMGtools/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36852/mcmctree-a-phylogenetic-program-for-bayesian-estimation-of-species-divergence-times</guid>
	<pubDate>Sat, 02 Jun 2018 07:40:06 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36852/mcmctree-a-phylogenetic-program-for-bayesian-estimation-of-species-divergence-times</link>
	<title><![CDATA[MCMCTREE: a phylogenetic program for Bayesian estimation of species divergence times]]></title>
	<description><![CDATA[<p><a href="http://abacus.gene.ucl.ac.uk/software/paml.html" target="_blank">MCMCTREE</a><span>&nbsp;is a phylogenetic program for Bayesian estimation of species divergence times using soft fossil constraints under various molecular clock models. This is part of the&nbsp;</span><a href="http://abacus.gene.ucl.ac.uk/software/paml.html" target="_blank">PAML</a><span>&nbsp;package. In this tutorial I will analyze an easy example modified from dataset of&nbsp;</span><a href="http://www.ncbi.nlm.nih.gov/pubmed/20551041" target="_blank">Inoue et al. (2010)</a><span>. Here we conduct a commonly used time estimation method, "Approximate Likelihood Method", for the datasets including more than 10 species.</span></p><p>Address of the bookmark: <a href="http://www.fish-evol.com/mcmctreeExampleVert6/text1Eng.html" rel="nofollow">http://www.fish-evol.com/mcmctreeExampleVert6/text1Eng.html</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44513/mike-an-ultrafast-assembly-and-alignment-free-approach-for-phylogenetic-tree-construction</guid>
	<pubDate>Mon, 08 Apr 2024 06:19:52 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44513/mike-an-ultrafast-assembly-and-alignment-free-approach-for-phylogenetic-tree-construction</link>
	<title><![CDATA[MIKE: an ultrafast, assembly-, and alignment-free approach for phylogenetic tree construction]]></title>
	<description><![CDATA[<p><span>MIKE (MinHash-based&nbsp;</span><em>k</em><span>-mer algorithm). This algorithm is designed for the swift calculation of the Jaccard coefficient directly from raw sequencing reads and enables the construction of phylogenetic trees based on the resultant Jaccard coefficient. Simulation results highlight the superior speed of MIKE compared to existing state-of-the-art methods. We used MIKE to reconstruct a phylogenetic tree, incorporating 238 yeast, 303&nbsp;</span><em>Zea</em><span>, 141&nbsp;</span><em>Ficus</em><span>, 67&nbsp;</span><em>Oryza</em><span>, and 43&nbsp;</span><em>Saccharum spontaneum</em><span>&nbsp;samples. MIKE demonstrated accurate performance across varying evolutionary scales, reproductive modes, and ploidy levels, proving itself as a powerful tool for phylogenetic tree construction.</span></p><p>Address of the bookmark: <a href="https://github.com/Argonum-Clever2/mike" rel="nofollow">https://github.com/Argonum-Clever2/mike</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/26390/przeworski-lab</guid>
  <pubDate>Mon, 15 Feb 2016 05:41:54 -0600</pubDate>
  <link></link>
  <title><![CDATA[Przeworski lab]]></title>
  <description><![CDATA[
<p>Genetic differences among individuals reflect the combined effects of mutation, recombination, population history and natural selection. As a result, studies of natural variation can provide important insights into evolutionary and genetic mechanisms: as examples, DNA sequence conservation among distantly related species can help identify functional roles too subtle to be detected in lab settings, while analyses of population variation allow for inferences about events that are too infrequent to be measured directly. Our research employs this general approach to learn about the dynamics of adaptation and the determinants of recombination and mutation, in humans and in other species.</p>

<p>More at http://przeworski.c2b2.columbia.edu/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/12944/orione-%E2%80%93-a-web-based-framework-for-ngs-analysis-in-microbiology</guid>
	<pubDate>Wed, 23 Jul 2014 06:43:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/12944/orione-%E2%80%93-a-web-based-framework-for-ngs-analysis-in-microbiology</link>
	<title><![CDATA[Orione – a web-based framework for NGS analysis in microbiology]]></title>
	<description><![CDATA[<p>End-to-end NGS microbiology data analysis requires a diversity of tools covering bacterial resequencing, de novo assembly, scaffolding, bacterial RNA-Seq, gene annotation and metagenomics. However, the construction of computational pipelines that use different software packages is difficult due to a lack of interoperability, reproducibility, and transparency. To overcome these limitations researchers at <a href="http://www.crs4.it/" target="_blank">CRS4</a>, Italy have developed Orione, a Galaxy-based framework consisting of publicly available research software and specifically designed pipelines to build complex, reproducible workflows for NGS microbiology data analysis. Enabling microbiology researchers to conduct their own custom analysis and data manipulation without software installation or programming, Orione provides new opportunities for data-intensive computational analyses in microbiology and metagenomics.</p>
<p>Reference</p>
<p>Cuccuru G1, Orsini M, Pinna A, Sbardellati A, Soranzo N, Travaglione A, Uva P, Zanetti G, Fotia G. (2014)<strong> Orione, a web-based framework for NGS analysis in microbiology.</strong> <em>Bioinformatics</em> [Epub ahead of print]. [<a href="http://bioinformatics.oxfordjournals.org/content/early/2014/03/10/bioinformatics.btu135.long" target="_blank">article</a>]</p><p>Address of the bookmark: <a href="http://orione.crs4.it/" rel="nofollow">http://orione.crs4.it/</a></p>]]></description>
	<dc:creator>Martin Jones</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26927/phylographer-graph-visualization-tool</guid>
	<pubDate>Wed, 06 Apr 2016 19:06:48 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26927/phylographer-graph-visualization-tool</link>
	<title><![CDATA[PhyloGrapher - Graph Visualization Tool]]></title>
	<description><![CDATA[<p><strong>PhyloGrapher</strong><span>&nbsp;is a program designed to visualize and study evolutionary relationships within families of homologous genes or proteins (elements).</span><strong>PhyloGrapher</strong><span>&nbsp;is a drawing tool that generates custom graphs for a given set of elements. In general, it is possible to use&nbsp;</span><strong>PhyloGrapher</strong><span>&nbsp;to visualize any type of relations between elements.&nbsp;</span></p>
<p><span>More at&nbsp;http://www.atgc.org/PhyloGrapher/PhyloGrapher_Welcome.html</span></p><p>Address of the bookmark: <a href="http://www.atgc.org/PhyloGrapher/PhyloGrapher_Welcome.html" rel="nofollow">http://www.atgc.org/PhyloGrapher/PhyloGrapher_Welcome.html</a></p>]]></description>
	<dc:creator>Jitendra Prajapati</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27821/blobsplorer</guid>
	<pubDate>Tue, 14 Jun 2016 10:28:58 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27821/blobsplorer</link>
	<title><![CDATA[Blobsplorer]]></title>
	<description><![CDATA[<p>Blobsplorer is a tool for interactive visualization of assembled DNA sequence data ("contigs") derived from (often unintentionally) mixed-species pools. It allows the simultaneous display of GC content, coverage, and taxonomic annotation for collections of contigs with a view to separating out those belonging to different taxa.</p>
<p>Blobsplorer is unlikely to be of use on its own as it requires contig data to be supplied in a format that involves considerable preprocessing (see below for a description). The easiest way to use Blobsplorer is as part of a workflow using scripts from <a href="https://github.com/blaxterlab/blobology">here</a>.</p><p>Address of the bookmark: <a href="http://nematodes.org/martin/blobsplorer/blobsplorer.html" rel="nofollow">http://nematodes.org/martin/blobsplorer/blobsplorer.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28200/machine-learning</guid>
	<pubDate>Fri, 01 Jul 2016 12:57:12 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28200/machine-learning</link>
	<title><![CDATA[Machine Learning !!!]]></title>
	<description><![CDATA[<p>In machine learning, computers apply&nbsp;<strong>statistical learning</strong>&nbsp;techniques to automatically identify patterns in data. These techniques can be used to make highly accurate predictions.</p>
<p><em>Keep scrolling.</em>&nbsp;Using a data set about homes, we will create a machine learning model to distinguish homes in New York from homes in San Francisco.</p><p>Address of the bookmark: <a href="http://www.r2d3.us/visual-intro-to-machine-learning-part-1/" rel="nofollow">http://www.r2d3.us/visual-intro-to-machine-learning-part-1/</a></p>]]></description>
	<dc:creator>Gudiya Pal</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29485/ribbon</guid>
	<pubDate>Fri, 21 Oct 2016 04:54:30 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29485/ribbon</link>
	<title><![CDATA[Ribbon !!]]></title>
	<description><![CDATA[<p><span>Visualization has played an extremely important role in the current genomic revolution to inspect and understand variants, expression patterns, evolutionary changes, and a number of other relationships. However, most of the information in read-to-reference or genome-genome alignments is lost for structural variations in the one-dimensional views of most genome browsers showing only reference coordinates. Instead, structural variations captured by long reads or assembled contigs often need more context to understand, including alignments and other genomic information from multiple chromosomes. We have addressed this problem by creating Ribbon (genomeribbon.com) an interactive online visualization tool that displays alignments along both reference and query sequences, along with any associated variant calls in the sample. This way Ribbon shows patterns in alignments of many reads across multiple chromosomes, while allowing detailed inspection of individual reads (Supplementary Note 1). For example, here we show a gene fusion in the SK-BR-3 breast cancer cell line linking the genes CYTH1 and EIF3H. While it has been found in the transcriptome previously, genome sequencing did not identify a direct chromosomal fusion between these two genes. After SMRT sequencing, Ribbon shows that there are indeed long reads that span from one gene to the other, going through not one but two variants, for the first time showing the genomic link between these two genes (Figure 1a). More gene fusions of this cancer cell line are investigated in Supplementary Note 2. Figure 1b shows another complex event in this sample made simple in Ribbon: the translocation of a 4.4 kb sequence deleted from chr19 and inserted into chr16 (Figure 1b). Thus, Ribbon enables understanding of complex variants, and it may also help in the detection of sequencing and sample preparation issues, testing of aligners and variant-callers, and rapid curation of structural variant candidates (Supplementary Note 3). In addition to SAM and BAM files with long, short, or paired-end reads, Ribbon can also load coordinate files from whole genome aligners such as MUMmer. Therefore, Ribbon can be used to test assembly algorithms or inspect the similarity between species. Supplementary Note 4 shows a comparison of gorilla and human genomes using Ribbon, highlighting major structural differences. In conclusion, Ribbon is a powerful interactive web tool for viewing complex genomic alignments.</span></p>
<p>Script at&nbsp;https://github.com/MariaNattestad/ribbon</p><p>Address of the bookmark: <a href="http://genomeribbon.com/" rel="nofollow">http://genomeribbon.com/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33789/i-pv-interactive-protein-sequence-visualization</guid>
	<pubDate>Mon, 03 Jul 2017 07:52:51 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33789/i-pv-interactive-protein-sequence-visualization</link>
	<title><![CDATA[I-PV: Interactive Protein Sequence Visualization]]></title>
	<description><![CDATA[<p><span>I-PV is a interactive data visualization software designed for inspection of protein sequences and mutation information. It is mainly used for Genetics and Bioinformatics. So what exactly makes it standout?</span></p>
<p><span>http://i-pv.org/ipv_rec</span></p><p>Address of the bookmark: <a href="http://i-pv.org/" rel="nofollow">http://i-pv.org/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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