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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/26828/bioinfolab</guid>
  <pubDate>Fri, 25 Mar 2016 11:05:35 -0500</pubDate>
  <link></link>
  <title><![CDATA[BioinfoLab]]></title>
  <description><![CDATA[
<p>Laboratory of Statistics and Computational tools for Bioinformatics</p>

<p>The Laboratory of Statistics and Computational tools for Bioinformatics (BioinfoLab) is hosted at the Istituto per le Applicazioni del Calcolo "Mauro Picone" - CNR . The laboratory has been officially opened in 2012 with the support of Programma Operativo Nazionale "Ricerca e Competitività" 2007-2013 (PON "R&amp;C"), and it incorporates several expertise and research activities started since 2007, and supported by several CNR projects. Main interest of BioinfoLab is to develop novel statistical methods and computational tools for the analysis of high dimensional data arising from "Multi-omics" applications. In particular, current activities involve the analysis of ChIP-seq and RNA-seq experiments. </p>

<p>More at http://bioinfo.na.iac.cnr.it/BioinfoLab/index.html</p>
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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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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/26569/genome-stability-laboratory</guid>
  <pubDate>Mon, 07 Mar 2016 04:16:32 -0600</pubDate>
  <link></link>
  <title><![CDATA[Genome Stability Laboratory]]></title>
  <description><![CDATA[
<p>The bakers yeast, Saccharomyces cerevisiae is an ideal model organism to understand mechanisms of meiotic chromosome segregation. In S. cerevisiae and in mammals, the majority of meiotic crossovers are formed through a highly conserved MSH4p-MSH5p, MLH1p-MLH3p dependent pathway. We are interested in charactering the role of these complexes in crossover formation and distribution among all homolog pairs. Errors in this process are linked to congenital birth defects in humans such as Down's syndrome.Our laboratory is also interested in understanding the effect of genetic background on mutation rate variation using S. cerevisiae as a model. These studies are relevant for understanding cancer progression, genome evolution and architecture. We use high- throughput genomic methods as well as classical genetics to achieve these aims. </p>

<p>More at http://faculty.iisertvm.ac.in/~nishantkt/index.html</p>
]]></description>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/26499/katju-lab</guid>
  <pubDate>Fri, 26 Feb 2016 03:25:32 -0600</pubDate>
  <link></link>
  <title><![CDATA[Katju Lab]]></title>
  <description><![CDATA[
<p>TheLab seek to understand the genetic factors contributing to genomic variation and phenotypic diversity.  To this end, we employ molecular and bioinformatic tools to study evolutionary processes at the level of populations, both experimental and natural, and genomes.  Our research interests encompass a wide range of topics, including the evolution of organellar and nuclear genomes, gene duplication and the origin of novel function, and the fitness and phenotypic consequences of mutation in evolution. For details regards ongoing projects, please see the Research page.</p>

<p>http://katjulab.com/research.html</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/26456/the-mills-lab</guid>
  <pubDate>Wed, 24 Feb 2016 16:18:38 -0600</pubDate>
  <link></link>
  <title><![CDATA[The Mills lab]]></title>
  <description><![CDATA[
<p>The laboratory is focused on the discovery and analysis of structural variation (SVs) from genomic sequence data. As part of the 1000 Genomes Project and other endeavors, we have helped produce initial fine-scale maps using a variety of SV discovery approaches including: (i) paired-end mapping (or read pair analysis) based on abnormally mapped pairs of clone ends; (ii) read-depth analysis, which detects deletions and duplications through analysis of the read depth-of-coverage; (iii) split read analysis, which detects SVs by evaluating gapped sequence alignments; and (iv) sequence assembly, which enables the discovery of novel (non-reference) sequence insertions.</p>

<p>http://millslab.org/research.html</p>
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