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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/32485?offset=450</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40531/shasta-long-read-assembler</guid>
	<pubDate>Tue, 14 Jan 2020 06:47:07 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40531/shasta-long-read-assembler</link>
	<title><![CDATA[Shasta long read assembler]]></title>
	<description><![CDATA[<p>The goal of the Shasta long read assembler is to rapidly produce accurate assembled sequence using as input DNA reads generated by&nbsp;<a href="https://nanoporetech.com/">Oxford Nanopore</a>&nbsp;flow cells.</p>
<p>Computational methods used by the Shasta assembler include:</p>
<ul>
<li>Using a&nbsp;<a href="https://en.wikipedia.org/wiki/Run-length_encoding">run-length</a>&nbsp;representation of the read sequence. This makes the assembly process more resilient to errors in homopolymer repeat counts, which are the most common type of errors in Oxford Nanopore reads.</li>
<li>Using in some phases of the computation a representation of the read sequence based on&nbsp;<em>markers</em>, a fixed subset of short k-mers (k &asymp; 10).</li>
</ul>
<p>More at&nbsp;<a href="https://chanzuckerberg.github.io/shasta/index.html">https://chanzuckerberg.github.io/shasta/index.html</a></p><p>Address of the bookmark: <a href="https://github.com/chanzuckerberg/shasta" rel="nofollow">https://github.com/chanzuckerberg/shasta</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/5220/paolo-ruggerone-lab</guid>
  <pubDate>Tue, 01 Oct 2013 14:15:53 -0500</pubDate>
  <link></link>
  <title><![CDATA[Paolo Ruggerone Lab]]></title>
  <description><![CDATA[
<p>Efflux pumps (RND family)</p>

<p>Functioning of efflux systems in Gram-negative bacteria<br />Determinants of the compound-efflux system interactions<br />Action of inhibitors on efflux systems<br />Structural and dynamical features of the efflux systems</p>

<p>TatA<br />Assembly of the TatA system<br />Study of the dynamical features of the charge zipper</p>

<p>Methods<br />Setup of a kinetic Monte Carlo (KMC) scheme to study the flux of antibiotics through porins and efflux systems<br />Setup of protocol to integrate MD results in a ligand-based approach</p>

<p>Viral inhibitors<br />Interactions of selected compounds with RNA-dependent RNA polymerases (RdRps) of HCV and BVDV<br />Assessment of the role of mutations in RdRps<br />Antimicrobial peptides</p>

<p>Interactions of antimicrobial peptides with membranes: structure and dynamics<br />Interactions between antimicrobial peptides in the presence of different membranes<br />Protein-protein interactions<br />Effects of mutations</p>

<p>Lab Page<br />http://www.dsf.unica.it/~paolo/Site/Home.html</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41275/shinychromosomea-gui-for-the-interactive-creation-of-non-circular-whole-genome-diagrams</guid>
	<pubDate>Sat, 29 Feb 2020 00:39:50 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41275/shinychromosomea-gui-for-the-interactive-creation-of-non-circular-whole-genome-diagrams</link>
	<title><![CDATA[shinyChromosome:a GUI for the interactive creation of non-circular whole genome diagrams]]></title>
	<description><![CDATA[<p><code>shinyChromosome</code> is a graphical user interface for interactive creation of non-circular whole genome diagrams developed using the R <strong>Shiny</strong> package.</p>
<p>To create single-genome plot by aligning genome data along all chromosomes of a single genome, go to the <code>Single-genome plot</code> menu.</p>
<p>To cretae two-genome plot for comparison of data across two genomes, go to the <code>Two-genome plot</code> menu.</p>
<p>For the detail format of input data, check the <code>Input data format</code> submenu of the <code>Help</code> menu.</p>
<p>shinyChromosome is deployed at <a href="http://150.109.59.144:3838/shinyChromosome/" target="_blank">http://150.109.59.144:3838/shinyChromosome/</a>, <a href="http://shinyChromosome.ncpgr.cn" target="_blank">http://shinyChromosome.ncpgr.cn</a>, and <a href="https://yimingyu.shinyapps.io/shinyChromosome" target="_blank">https://yimingyu.shinyapps.io/shinyChromosome</a> for online use. The source code and manual of shinyChromosome are freely available at <a href="https://github.com/venyao/shinyChromosome" target="_blank">https://github.com/venyao/shinyChromosome</a>.</p>
<p>https://yimingyu.shinyapps.io/shinychromosome/</p>
<p>https://www.sciencedirect.com/science/article/pii/S1672022919301883</p><p>Address of the bookmark: <a href="https://yimingyu.shinyapps.io/shinychromosome/" rel="nofollow">https://yimingyu.shinyapps.io/shinychromosome/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/5310/bergman-lab</guid>
  <pubDate>Thu, 03 Oct 2013 17:20:09 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bergman Lab]]></title>
  <description><![CDATA[
<p>Broad area of research:</p>

<p>Genome Annotation and Functional Genomics</p>

<p>Bergman Lab is actively engaged in the development and application of computational methods to improve the annotation of functional biological features in genome sequences.  Bergman Lab work focuses on improving annotation of non-protein-coding regions of the genome including conserved noncoding sequences (CNSs), cis-regulatory modules (CRMs), transcription factor binding sites (TFBSs), transposable elements (TEs) and noncoding RNA (ncRNA) genes. Current projects include improving the (i) annotation of TEs in the fly and yeast genomes, (ii) annotation of CRMs and TFBSs in the fly genome, and (iii) analysis of transposon knockout collections in flies. Research in this area is supported by the EC FP7 programme.</p>

<p>Genome and Molecular Evolution<br />Text and Data Mining</p>

<p>More @ http://bergmanlab.smith.man.ac.uk/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41937/merqury-evaluate-genome-assemblies-with-k-mers</guid>
	<pubDate>Fri, 03 Jul 2020 19:29:34 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41937/merqury-evaluate-genome-assemblies-with-k-mers</link>
	<title><![CDATA[merqury: Evaluate genome assemblies with k-mers]]></title>
	<description><![CDATA[<p><span>Often, genome assembly projects have illumina whole genome sequencing reads available for the assembled individual. The k-mer spectrum of this read set can be used for independently evaluating assembly quality without the need of a high quality reference. Merqury provides a set of tools for this purpose.</span></p>
<p><span>More at&nbsp;<a href="https://www.biorxiv.org/content/10.1101/2020.03.15.992941v1.full">https://www.biorxiv.org/content/10.1101/2020.03.15.992941v1.full</a></span></p><p>Address of the bookmark: <a href="https://github.com/marbl/merqury" rel="nofollow">https://github.com/marbl/merqury</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/5436/the-anatomy-of-successful-computational-biology-software</guid>
	<pubDate>Thu, 10 Oct 2013 11:53:08 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/5436/the-anatomy-of-successful-computational-biology-software</link>
	<title><![CDATA[The anatomy of successful computational biology software]]></title>
	<description><![CDATA[<p>Creators of software widely used in computational biology discuss the factors that contributed to their success</p><p><em>Nature Biotechnology</em><span>&nbsp;spoke with Altschul and several other originators of computational biology software programs widely used today (</span><a href="http://www.nature.com/nbt/journal/v31/n10/full/nbt.2721.html#t1">Table 1</a><span>). The conversations explored what makes certain software tools successful, the unique challenges of developing them for biological research and how the field of computational biology, as a whole, can move research agendas forward. What follows is an edited compilation of interviews.</span></p><p>Detail @&nbsp;<a href="http://www.nature.com/nbt/journal/v31/n10/full/nbt.2721.html">http://www.nature.com/nbt/journal/v31/n10/full/nbt.2721.html</a></p><p>News Source @ Nature</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43055/infogenomer-integrative-reconstruction-of-cancer-genome-karyotypes</guid>
	<pubDate>Wed, 05 May 2021 01:02:18 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43055/infogenomer-integrative-reconstruction-of-cancer-genome-karyotypes</link>
	<title><![CDATA[InfoGenomeR: Integrative reconstruction of cancer genome karyotypes]]></title>
	<description><![CDATA[<p>InfoGenomeR is the Integrative Framework for Genome Reconstruction that uses a breakpoint graph to model the connectivity among genomic segments at the genome-wide scale. InfoGenomeR integrates cancer purity and ploidy, total CNAs, allele-specific CNAs, and haplotype information to identify the optimal breakpoint graph representing cancer genomes.</p>
<p><img src="https://github.com/YeonghunL/InfoGenomeR/raw/master/doc/overview.png" alt="image" style="border: 0px; border: 0px;"></p>
<p>More at&nbsp;https://www.nature.com/articles/s41467-021-22671-6</p><p>Address of the bookmark: <a href="https://github.com/dmcblab/InfoGenomeR" rel="nofollow">https://github.com/dmcblab/InfoGenomeR</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/5663/network-analysis-indian-statistical-institute</guid>
  <pubDate>Wed, 16 Oct 2013 08:06:50 -0500</pubDate>
  <link></link>
  <title><![CDATA[Network Analysis @ Indian Statistical Institute]]></title>
  <description><![CDATA[
<p>Indian Statistical Institute Kolkata invites applications for the following posts</p>

<p>2013 Oct Advertisement from Indian Statistical Institute</p>

<p>Post: Network Analysis</p>

<p>No. of Positions:  01</p>

<p>Educational Qualifications:</p>

<p>Candidate should have passed BE/B.Tech Or Equivalent in Computer Science / Electrical Engineering / Electronics / Information Technology / Bioinformatics / Biotechnology with throughout first Class<br />Experience:</p>

<p>(details of experience required)<br />Pay Scale: INR Rs.16000-20000/-P.M.</p>

<p>Walk-In-Interview : 22 Oct 2013 at 10:30 AM</p>

<p>Download Official Notification:<br />http://www.isical.ac.in/JobApplicationFiles/MIU_0310201311433700.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43364/ragtag-a-collection-of-software-tools-for-scaffolding-and-improving-modern-genome-assemblies</guid>
	<pubDate>Sat, 11 Sep 2021 00:28:14 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43364/ragtag-a-collection-of-software-tools-for-scaffolding-and-improving-modern-genome-assemblies</link>
	<title><![CDATA[RagTag: a collection of software tools for scaffolding and improving modern genome assemblies]]></title>
	<description><![CDATA[<p>RagTag is a collection of software tools for scaffolding and improving modern genome assemblies. Tasks include:</p>
<ul>
<li>Homology-based misassembly&nbsp;<a href="https://github.com/malonge/RagTag/wiki/correct">correction</a></li>
<li>Homology-based assembly&nbsp;<a href="https://github.com/malonge/RagTag/wiki/scaffold">scaffolding</a>&nbsp;and&nbsp;<a href="https://github.com/malonge/RagTag/wiki/patch">patching</a></li>
<li>Scaffold&nbsp;<a href="https://github.com/malonge/RagTag/wiki/merge">merging</a></li>
</ul><p>Address of the bookmark: <a href="https://github.com/malonge/RagTag" rel="nofollow">https://github.com/malonge/RagTag</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/5748/troyanskaya-lab</guid>
  <pubDate>Fri, 18 Oct 2013 10:57:40 -0500</pubDate>
  <link></link>
  <title><![CDATA[Troyanskaya  Lab]]></title>
  <description><![CDATA[
<p>In our research, we combine computational methods with an experimental component in a unified effort to develop comprehensive descriptions of genetic systems of cellular controls, including those whose malfunctioning becomes the basis of genetic disorders, such as cancer, and others whose failure might produce developmental defects in model systems.</p>

<p>Research Interest<br />Genomic Data Integration</p>

<p>Microarray Analysis</p>

<p>Gene and Protein Function Prediction</p>

<p>Detection and Analysis of Chromosomal Abnormalities and Functional Evolution</p>

<p>Integration of Computation and Experiments</p>

<p>Identification of Biological Networks and Pathways</p>

<p>Evaluation and Validation of Computational Predictions</p>

<p>Scalable Visualization-Based Data Analysis</p>

<p>More @ http://reducio.princeton.edu/cm/<br />PI page @ http://reducio.princeton.edu/cm/ogt</p>
]]></description>
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