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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/30249?offset=230</link>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/17501/nieduszynski-group</guid>
  <pubDate>Fri, 26 Sep 2014 19:35:06 -0500</pubDate>
  <link></link>
  <title><![CDATA[Nieduszynski Group]]></title>
  <description><![CDATA[
<p>Complete, accurate replication of the genome is essential for life. All chromosomes in eukaryotic cells must be duplicated and then segregated to daughter cells to ensure genetic integrity and produce the large number of cells that make up a multicellular organism. We are using genetic, genomic and computational methods to understand how chromosome replication is regulated to ensure genome stability. By focusing on the basic biology that underpins cell growth and division we aim to provide new insights that may help our understanding of diseases such as cancer and congenital disorders. </p>

<p>More http://www.nieduszynski.org/index.php<br />http://www.path.ox.ac.uk/research/cell-biology-and-pathology/conrad-nieduszynski-group</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/19555/a-3d-map-of-the-human-genome</guid>
	<pubDate>Fri, 12 Dec 2014 22:27:55 -0600</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/19555/a-3d-map-of-the-human-genome</link>
	<title><![CDATA[A 3D Map of the Human Genome]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/dES-ozV65u4" frameborder="0" allowfullscreen></iframe>Suhas Rao and Miriam Huntley (of the Aiden Lab) describe a 3D map of the human genome at kilobase resolution, revealing the principles of chromatin looping. Guest Origami Folding: Sarah Nyquist.

Suhas S.P. Rao*, Miriam H. Huntley*, Neva C. Durand, Elena K. Stamenova, Ivan D. Bochkov, James T. Robinson, Adrian L. Sanborn, Ido Machol, Arina D. Omer, Eric S. Lander, Erez Lieberman Aiden. (2014). A 3D Map of the Human Genome at Kilobase Resolution Reveals Principles of Chromatin Looping. Cell.]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/22793/sequencing-by-xpansion</guid>
	<pubDate>Wed, 17 Jun 2015 20:58:11 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/22793/sequencing-by-xpansion</link>
	<title><![CDATA[Sequencing By Xpansion]]></title>
	<description><![CDATA[<p>Sequencing By Xpansion (SBX) is a DNA sequencing method that uses a simple biochemical reaction to encode the sequence of a DNA molecule into a highly measurable surrogate called an Xpandomer. This single molecule approach produces enough Xpandomer in a single drop reaction to sequence an entire human genome 1000X over. To achieve this, an Xpandomer replaces each DNA sequence with a sequence of large, high signal reporter molecules using the SBX molecular expansion technology. The DNA sequence is then read out as the Xpandomer reporters pass sequentially through a nanopore detector. SBX is a molecular engineering platform that benefits from core design principles that separate the multiple molecular functions. This systems approach enables efficient development and incorporation of improvements to SBX and is key to reconfiguring and optimizing Xpandomer measurement for different detection platforms.</p><p>http://www.stratosgenomics.com/stratos-genomics-technology</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
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	<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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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27847/anvio</guid>
	<pubDate>Thu, 16 Jun 2016 18:15:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27847/anvio</link>
	<title><![CDATA[Anvio]]></title>
	<description><![CDATA[<p>In a nutshell</p>
<p>Anvi&rsquo;o is an analysis and visualization platform for &lsquo;omics data.</p>
<p>Please find the methods paper here: https://peerj.com/articles/1319/</p>
<p>Anvi&rsquo;o would not have been possible without the help of many people who directly or indirectly contributed to its development. Here is the acknowledgements section of our methods paper</p>
<p><span>An analysis and visualization platform for 'omics data</span><span>&nbsp;</span><span><a href="http://merenlab.org/projects/anvio">http://merenlab.org/projects/anvio</a></span></p>
<p><span>Paper&nbsp;https://peerj.com/articles/1839/</span></p><p>Address of the bookmark: <a href="https://github.com/meren/anvio" rel="nofollow">https://github.com/meren/anvio</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28415/scarpa</guid>
	<pubDate>Wed, 13 Jul 2016 07:59:25 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28415/scarpa</link>
	<title><![CDATA[Scarpa]]></title>
	<description><![CDATA[<p><strong>Scarpa</strong>&nbsp;is a stand-alone scaffolding tool for NGS data. It can be used together with virtually any genome assembler and any NGS read mapper that supports SAM format. Other features include support for multiple libraries and an option to estimate insert size distributions from data. Scarpa is available free of charge for academic and commercial use under the GNU General Public License (GPL).</p>
<p>See the&nbsp;<a href="http://compbio.cs.toronto.edu/hapsembler/hapsembler-2.21_manual.pdf">user manual</a>&nbsp;or the&nbsp;<a href="http://compbio.cs.toronto.edu/hapsembler/scarpa_paper.pdf">paper</a>&nbsp;for more information about Scarpa. Click&nbsp;<a href="http://compbio.cs.toronto.edu/hapsembler/ScarpaSupplementary.pdf">here</a>&nbsp;for the supplementary material.</p><p>Address of the bookmark: <a href="http://compbio.cs.toronto.edu/hapsembler/scarpa.html" rel="nofollow">http://compbio.cs.toronto.edu/hapsembler/scarpa.html</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29583/graph-genome-suite</guid>
	<pubDate>Fri, 28 Oct 2016 07:59:54 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29583/graph-genome-suite</link>
	<title><![CDATA[Graph Genome Suite]]></title>
	<description><![CDATA[<p><span>Seven Bridges is the biomedical data analysis company accelerating breakthroughs in genomics research for cancer, drug development and precision medicine. We build self-improving systems to analyze millions of genomes, including the&nbsp;</span><strong>Graph Genome Suite</strong><span>&nbsp;&mdash; the most advanced population genomics tools in the world.</span></p><p>Address of the bookmark: <a href="https://www.sbgenomics.com/graph/" rel="nofollow">https://www.sbgenomics.com/graph/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27216/yass-genomic-similarity-search-tool</guid>
	<pubDate>Mon, 02 May 2016 09:26:00 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27216/yass-genomic-similarity-search-tool</link>
	<title><![CDATA[YASS :: genomic similarity search tool]]></title>
	<description><![CDATA[<p>YASS is a genomic similarity search tool, for nucleic (DNA/RNA) sequences in fasta or plain text format (<em>it produces local pairwise alignments</em>). Like most of the heuristic pairwise local alignment tools for DNA sequences (FASTA, BLAST, PATTERNHUNTER, BLASTZ/LASTZ, LAST ...), YASS uses <em>seeds</em> to detect potential similarity regions, and then tries to extend them to local alignments. This genomic search tool uses <em>multiple transition constrained spaced seeds</em> that enable to search more fuzzy repeats, as non-coding DNA/RNA. Another simple, but interesting feature is that you can specify the seed pattern used in the search step (as provided for example by <a href="http://bioinfo.lifl.fr/yass/iedera.php">iedera</a>).</p>
<p>Main features of YASS are:</p>
<ul>
<li>multiple, possibly overlapping seeds and a new hit criterion to ensure a good sensitivity/selectivity trade-off</li>
<li>transition-constrained spaced seeds to improve sensitivity (transition mutations are purine to purine [<code>A&lt;-&gt;G</code>] or pyrimidine to pyrimidine [<code>C&lt;-&gt;T</code>])</li>
<li>using different scoring schemes with bit-score and E-value evaluated according to the sequence background frequencies</li>
<li>parameterizable <em>output</em> filter for low complexity repeats</li>
<li>reporting of various alignment statistical parameters (mutation bias along triplets, transition/transversion)</li>
<li>post-processing step to group gapped alignments</li>
</ul><p>Address of the bookmark: <a href="http://bioinfo.lifl.fr/yass/" rel="nofollow">http://bioinfo.lifl.fr/yass/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29635/r-graphs</guid>
	<pubDate>Fri, 04 Nov 2016 10:48:00 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29635/r-graphs</link>
	<title><![CDATA[R Graphs !!]]></title>
	<description><![CDATA[<p><span>The blog is a collection of script examples with example data and output plots. R produce excellent quality graphs for data analysis, science and business presentation, publications and other purposes. Self-help codes and examples are provided. Enjoy nice graphs !!</span></p><p>Address of the bookmark: <a href="http://rgraphgallery.blogspot.be/" rel="nofollow">http://rgraphgallery.blogspot.be/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29656/statistics-and-probability</guid>
	<pubDate>Tue, 08 Nov 2016 07:34:25 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29656/statistics-and-probability</link>
	<title><![CDATA[Statistics and probability]]></title>
	<description><![CDATA[<h3><span>Topics</span></h3>
<div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/displaying-describing-data">Displaying and describing data</a></div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/modeling-distributions-of-data">Modeling distributions of data</a></div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/describing-relationships-quantitative-data">Describing relationships in quantitative data</a></div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/designing-studies">Designing studies</a></div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/probability-library">Probability</a></div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/random-variables-stats-library">Random variables</a></div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/sampling-distributions-library">Sampling distributions</a></div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/confidence-intervals-one-sample">Confidence intervals (one sample)</a></div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/significance-tests-one-sample">Significance tests (one sample)</a></div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/significance-tests-confidence-intervals-two-samples">Significance tests and confidence intervals (two samples)</a></div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/inference-categorical-data-chi-square-tests">Inference for categorical data (chi-square tests)</a></div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/advanced-regression-inference-transforming">Advanced regression (inference and tran</a></div>
</div><p>Address of the bookmark: <a href="https://www.khanacademy.org/math/statistics-probability" rel="nofollow">https://www.khanacademy.org/math/statistics-probability</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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