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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/29683?offset=190</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/19636/google-genomics</guid>
	<pubDate>Thu, 18 Dec 2014 11:05:42 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/19636/google-genomics</link>
	<title><![CDATA[Google Genomics]]></title>
	<description><![CDATA[<ul>
<li>
<p><strong>Explore genetic variation interactively.</strong> Compare entire cohorts in seconds with SQL-like queries. Compute transition/transversion ratios, genome-wide association, allelic frequency and more.</p>
</li>
<li>
<p><strong>Process big genomic data easily.</strong> Run batch analyses like principal component analysis and Hardy-Weinberg equilibrium on as many samples as you like, in minutes or hours, with just a little code.</p>
</li>
<li>
<p><strong>Use Google's infrastructure and big data expertise.</strong> Store one genome or a million using Google Genomics and take advantage of the same infrastructure that powers Search, Maps, YouTube, Gmail and Drive.</p>
</li>
<li>
<p><strong>Support emerging global standards.</strong> Google Genomics is implementing the API defined by the Global Alliance for Genomics and Health for visualization, analysis and more. Compliant software can access Google Genomics, local servers, or any other implementation.</p>
</li>
</ul><p>Address of the bookmark: <a href="https://cloud.google.com/genomics/" rel="nofollow">https://cloud.google.com/genomics/</a></p>]]></description>
	<dc:creator>Tenzin Paul</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/22416/rosenberg-lab</guid>
  <pubDate>Wed, 27 May 2015 17:52:24 -0500</pubDate>
  <link></link>
  <title><![CDATA[Rosenberg lab]]></title>
  <description><![CDATA[
<p>Research. Research in the lab focuses on mathematical, statistical, and computational problems in evolutionary biology and human genetics. Long-term interests of the lab include topics such as:</p>

<p>    Human genetic variation<br />    Inference of human evolutionary history from genetic markers<br />    Statistical analysis of population-genetic data<br />    Mathematical models of gene genealogies<br />    Theoretical population genetics<br />    Combinatorics of evolutionary trees<br />    The relationship between gene trees and species trees<br />    The role of human evolutionary genetics in the search for genes that contribute to disease-susceptibility <br />More at https://web.stanford.edu/group/rosenberglab/index.html</p>
]]></description>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/23633/biorg</guid>
  <pubDate>Tue, 04 Aug 2015 20:52:52 -0500</pubDate>
  <link></link>
  <title><![CDATA[BioRG]]></title>
  <description><![CDATA[
<p>This research group works on problems from the fields of Bioinformatics, Biotechnology, Data Mining, and Information Retrieval. The group's research projects includes Comparative Genomics of Bacterial genomes, Metagenomics, Genomic databases, Pattern Discovery in sequences and structures, micro-array data analysis, prediction of regulatory elements, primer design, probe design, phylogenetic analysis, medical image processing, image analysis, data integration, data mining, information retrieval, knowledge discovery in electronic medical records, and more. </p>

<p>More at http://biorg.cis.fiu.edu/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26525/ensembl-comparative-genomics-resources</guid>
	<pubDate>Sun, 28 Feb 2016 17:10:20 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26525/ensembl-comparative-genomics-resources</link>
	<title><![CDATA[Ensembl comparative genomics resources]]></title>
	<description><![CDATA[<div>
<p>The Ensembl comparative genomics resources are one such reference set that facilitates comprehensive and reproducible analysis of chordate genome data. Ensembl computes pairwise and multiple whole-genome alignments from which large-scale synteny, per-base conservation scores and constrained elements are obtained. Gene alignments are used to define Ensembl Protein Families, GeneTrees and homologies for both protein-coding and non-coding RNA genes. These resources are updated frequently and have a consistent informatics infrastructure and data presentation across all supported species. Specialized web-based visualizations are also available including synteny displays, collapsible gene tree plots, a gene family locator and different alignment views. The Ensembl comparative genomics infrastructure is extensively reused for the analysis of non-vertebrate species by other projects including Ensembl Genomes and Gramene and much of the information here is relevant to these projects. The consistency of the annotation across species and the focus on vertebrates makes Ensembl an ideal system to perform and support vertebrate comparative genomic analyses. We use robust software and pipelines to produce reference comparative data and make it freely available.</p>
<p><strong>Database URL:</strong> <a href="http://www.ensembl.org" target="pmc_ext">http://www.ensembl.org</a>.</p>
</div><p>Address of the bookmark: <a href="http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4761110/" rel="nofollow">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4761110/</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26325/crossmap</guid>
	<pubDate>Mon, 08 Feb 2016 15:47:00 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26325/crossmap</link>
	<title><![CDATA[CrossMap]]></title>
	<description><![CDATA[<p>CrossMap is a program for convenient conversion of genome coordinates (or annotation files) between <em>different assemblies</em> (such as Human <a href="http://www.ncbi.nlm.nih.gov/assembly/2928/">hg18 (NCBI36)</a> &lt;&gt; <a href="http://www.ncbi.nlm.nih.gov/assembly/2758/">hg19 (GRCh37)</a>, Mouse <a href="http://www.ncbi.nlm.nih.gov/assembly/165668/">mm9 (MGSCv37)</a> &lt;&gt; <a href="http://www.ncbi.nlm.nih.gov/assembly/327618/">mm10 (GRCm38)</a>).</p>
<p>It supports most commonly used file formats including SAM/BAM, Wiggle/BigWig, BED, GFF/GTF, VCF.</p>
<p>CrossMap is designed to liftover genome coordinates between assemblies. It&rsquo;s <em>not</em> a program for aligning sequences to reference genome.</p>
<p>We <em>do not</em> recommend using CrossMap to convert genome coordinates between species.</p>
<p>More at http://crossmap.sourceforge.net/</p><p>Address of the bookmark: <a href="http://crossmap.sourceforge.net/" rel="nofollow">http://crossmap.sourceforge.net/</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/27046/desai-lab</guid>
  <pubDate>Thu, 21 Apr 2016 10:21:07 -0500</pubDate>
  <link></link>
  <title><![CDATA[Desai Lab]]></title>
  <description><![CDATA[
<p>Evolutionary Dynamics and Population Genetics</p>

<p>Natural selection and other evolutionary forces lead to particular patterns of evolutionary dynamics, and they leave characteristic signatures on the genetic variation within populations.  We use a combination of theory and experiments to study the dynamics and population genetics of natural selection in asexual populations such as microbes and viruses. </p>

<p>We use both theory and experiments to study evolutionary dynamics and population genetics, particularly in situations where natural selection is pervasive.</p>

<p>http://desailab.oeb.harvard.edu/home</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27331/andi</guid>
	<pubDate>Fri, 13 May 2016 05:16:35 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27331/andi</link>
	<title><![CDATA[Andi]]></title>
	<description><![CDATA[<p>This is the <code>andi</code> program for estimating the evolutionary distance between closely related genomes. These distances can be used to rapidly infer phylogenies for big sets of genomes. Because <code>andi</code> does not compute full alignments, it is so efficient that it scales even up to thousands of bacterial genomes.</p>
<p>This readme covers all necessary instructions for the impatient to get <code>andi</code> up and running. For extensive instructions please consult the <a href="https://github.com/EvolBioInf/andi/blob/master/andi-manual.pdf">manual</a>.</p>
<p>More at https://github.com/evolbioinf/andi/</p><p>Address of the bookmark: <a href="http://bioinformatics.oxfordjournals.org/content/early/2015/01/13/bioinformatics.btu815.full" rel="nofollow">http://bioinformatics.oxfordjournals.org/content/early/2015/01/13/bioinformatics.btu815.full</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<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>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31278/metapred2cs</guid>
	<pubDate>Fri, 03 Mar 2017 05:15:07 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31278/metapred2cs</link>
	<title><![CDATA[MetaPred2CS]]></title>
	<description><![CDATA[<p style="text-align: justify;"><strong>MetaPred2CS Web server&nbsp;</strong>is a meta-predictor based on&nbsp;<a href="http://www.ncbi.nlm.nih.gov/pubmed/17160063">Support Vector Machine (SVM)</a>&nbsp;that combines 6 individual sequence based protein-protein interaction prediction methods to predict&nbsp;<strong>prokaryotic two-component system&nbsp;</strong>protein-protein interactions (PPIs). The methods implemented in MetaPred2CS are 2 co-evolutionary methods:&nbsp;<a href="http://www.ncbi.nlm.nih.gov/pubmed/11933068">in-silico two hybrid (i2h)</a>&nbsp;and&nbsp;<a href="http://www.ncbi.nlm.nih.gov/pubmed/11707606">mirror tree (MT)</a>&nbsp;methods and 4 genomics context based methods:&nbsp;<a href="http://www.ncbi.nlm.nih.gov/pubmed/15947018">phylogenetic profiling (PP)</a>,&nbsp;<a href="http://www.ncbi.nlm.nih.gov/pubmed/10573422">gene fusion (GF)</a>,&nbsp;<a href="http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.0030043">gene neighbourhood (GN)</a>&nbsp;and and&nbsp;<a href="http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.0030043">gene operon methods (GO)</a>.</p>
<p>&nbsp;http://metapred2cs.ibers.aber.ac.uk/</p><p>Address of the bookmark: <a href="https://github.com/martinjvickers/MetaPred2CS" rel="nofollow">https://github.com/martinjvickers/MetaPred2CS</a></p>]]></description>
	<dc:creator>Manisha Mishra</dc:creator>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29282/cosmic</guid>
	<pubDate>Sat, 01 Oct 2016 15:04:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29282/cosmic</link>
	<title><![CDATA[COSMIC]]></title>
	<description><![CDATA[<p>The accurate description and annotation of structural variants can be complex. &nbsp;This is due to the different resolution that variants are reported from traditional&nbsp;cytogenetic coordinates down to the actual base pair positions. Furthermore, multiple&nbsp;rearrangements in a single area of the genome can make cataloguing and interpreting&nbsp;their effects challenging.&nbsp;</p>
<p>The Rearrangement Overview page describes the one or more breakpoints which make up a structural&nbsp;variant. A breakpoint is defined as a region or point where the sample sequence has altered&nbsp;from the reference sequence. Minimum interpretation is made of this data. One variant event&nbsp;can consist of one or multiple breakpoints. The Syntax (shown above the table) gives a detailed description of the variant and its location &nbsp;(e.g. chr11:g.36585230_76606619del, a deletion of&nbsp;roughly 40Mb on chromosome 11). Syntax is based on HGVS mutation nomenclature recommendations&nbsp;[http://www.hgvs.org/rec.html].&nbsp;</p>
<p>http://cancer.sanger.ac.uk/cosmic/help/rearrangement/overview</p><p>Address of the bookmark: <a href="http://cancer.sanger.ac.uk/cosmic/help/rearrangement/overview" rel="nofollow">http://cancer.sanger.ac.uk/cosmic/help/rearrangement/overview</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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