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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/44489?offset=510</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31209/dial</guid>
	<pubDate>Wed, 01 Mar 2017 08:42:28 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31209/dial</link>
	<title><![CDATA[DIAL]]></title>
	<description><![CDATA[<p>A computational pipeline for identifying single-base substitutions between two closely related genomes without the help of a reference genome. DIAL works even when the depth of coverage is insufficient for de novo assembly, and it can be extended to determine small insertions/deletions. Our main motivation is to use this tool to survey the genetic diversity of endangered species as the identified sequence differences can be used to design genotyping arrays to assist in the species' management.</p>
<p>http://www.bx.psu.edu/~ratan/</p><p>Address of the bookmark: <a href="http://www.bx.psu.edu/miller_lab/" rel="nofollow">http://www.bx.psu.edu/miller_lab/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32154/decostar-detection-of-co-evolution</guid>
	<pubDate>Fri, 14 Apr 2017 06:27:25 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32154/decostar-detection-of-co-evolution</link>
	<title><![CDATA[DeCoSTAR - Detection of Co-evolution]]></title>
	<description><![CDATA[<p><span>DeCoSTAR is a software which aims at reconstructing ancestral gene or genome organizations, in the form of sets of neighborhood relations -adjacencies- between pairs of ancestral genes or gene domains.</span><br><span>Ancestral genes or domains are deduced from reconciled gene trees in a context of birth, speciation, duplication, loss, transfer, which are either given as input or computed with the&nbsp;</span><a href="http://mbb.univ-montp2.fr/MBB/download_sources/16__TERA">ecceTERA package</a><span>, to which DeCoSTAR is integrated. DeCoSTAR constructs parsimonious scenarios of gains and breakages of adjacencies, and contains in particular all the features of previous software DeCo, DeCoLT, ArtDeCo and DeClone. It provides statistical supports on ancestral adjacencies, or the possibility to handle badly assembled genomes.&nbsp;</span><br><span>DeCoSTAR is able to reconstruct the histories of domains inside genes, including gene fusion and fission events, as well as ancestral genome structures for dozens of whole genomes from all kingdoms of life in a few minutes.</span></p><p>Address of the bookmark: <a href="http://pbil.univ-lyon1.fr/software/DeCoSTAR/" rel="nofollow">http://pbil.univ-lyon1.fr/software/DeCoSTAR/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33720/deschrambler</guid>
	<pubDate>Thu, 29 Jun 2017 11:54:59 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33720/deschrambler</link>
	<title><![CDATA[DESCHRAMBLER]]></title>
	<description><![CDATA[<p>DESCHRAMBLER is shown to produce highly accurate reconstructions using data simulation and by benchmarking it against other reconstruction tools</p>
<p>You can find the detail of reconstructed data at http://bioinfo.konkuk.ac.kr/DESCHRAMBLER/</p><p>Address of the bookmark: <a href="https://github.com/jkimlab/DESCHRAMBLER" rel="nofollow">https://github.com/jkimlab/DESCHRAMBLER</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36012/gmol-an-interactive-tool-for-3d-genome-structure-visualization</guid>
	<pubDate>Wed, 21 Mar 2018 12:25:20 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36012/gmol-an-interactive-tool-for-3d-genome-structure-visualization</link>
	<title><![CDATA[GMOL: An Interactive Tool for 3D Genome Structure Visualization]]></title>
	<description><![CDATA[<p><span>GMOL was developed based upon our multi-scale approach that allows a user to scale between six separate levels within the genome. With GMOL, a user can choose any unit at any scale and scale it up or down to visualize its structure and retrieve corresponding genome sequences.</span></p><p>Address of the bookmark: <a href="https://www.nature.com/articles/srep20802" rel="nofollow">https://www.nature.com/articles/srep20802</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36950/salsa-a-tool-to-scaffold-long-read-assemblies-with-hi-c</guid>
	<pubDate>Fri, 15 Jun 2018 04:01:15 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36950/salsa-a-tool-to-scaffold-long-read-assemblies-with-hi-c</link>
	<title><![CDATA[SALSA: A tool to scaffold long read assemblies with Hi-C]]></title>
	<description><![CDATA[This code is used to scaffold your assemblies using Hi-C data. This version implements some improvements in the original SALSA algorithm. If you want to use the old version, it can be found in the old_salsa branch.

To use the latest version, first run the following commands:

  cd SALSA
  make
To run the code, you will need Python 2.7, BOOST libraries and Networkx(version lower than 1.2).

If you consider using this tool, please cite our publication which describes the methods used for scaffolding.

Ghurye, J., Pop, M., Koren, S., Bickhart, D., &amp; Chin, C. S. (2017). Scaffolding of long read assemblies using long range contact information. BMC genomics, 18(1), 527. Link

Ghurye, J., Rhie, A., Walenz, B.P., Schmitt, A., Selvaraj, S., Pop, M., Phillippy, A.M. and Koren, S., 2018. Integrating Hi-C links with assembly graphs for chromosome-scale assembly. bioRxiv, p.261149 Link

For any queries, please either ask on github issue page or send an email to Jay Ghurye (jayg@cs.umd.edu).<p>Address of the bookmark: <a href="https://github.com/machinegun/SALSA" rel="nofollow">https://github.com/machinegun/SALSA</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38039/vgsc-a-web-based-vector-graph-toolkit-of-genome-synteny-and-collinearity</guid>
	<pubDate>Tue, 30 Oct 2018 10:46:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38039/vgsc-a-web-based-vector-graph-toolkit-of-genome-synteny-and-collinearity</link>
	<title><![CDATA[VGSC: A Web-Based Vector Graph Toolkit of Genome Synteny and Collinearity]]></title>
	<description><![CDATA[<p><span>VGSC, the Vector Graph toolkit of genome Synteny and Collinearity, and its online service, to visualize the synteny and collinearity in the common graphical format, including both raster (JPEG, Bitmap, and PNG) and vector graphic (SVG, EPS, and PDF).</span><em>&nbsp;</em></p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4783527/" rel="nofollow">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4783527/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38515/genome-annotation-using-maker-tutorial</guid>
	<pubDate>Thu, 20 Dec 2018 17:39:23 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38515/genome-annotation-using-maker-tutorial</link>
	<title><![CDATA[Genome Annotation using MAKER tutorial !]]></title>
	<description><![CDATA[<p><a href="http://www.yandell-lab.org/software/maker.html">MAKER</a><span>&nbsp;is a great tool for annotating a reference genome using empirical and&nbsp;</span><em>ab initio</em><span>gene predictions.&nbsp;</span><a href="http://gmod.org/wiki/Main_Page">GMOD</a><span>, the umbrella organization that includes MAKER, has some nice tutorials online for running MAKER. However, these were quite simplified examples and it took a bit of effort to wrap my head completely around everything. Here I will describe a&nbsp;</span><em>de novo</em><span>&nbsp;genome annotation for&nbsp;</span><em>Boa constrictor</em><span>&nbsp;in detail, so that there is a record and that it is easy to use this as a guide to annotate any genome.</span></p><p>Address of the bookmark: <a href="https://www.biostars.org/p/261203/" rel="nofollow">https://www.biostars.org/p/261203/</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39250/darwin-wga-a-co-processor-provides-increased-sensitivity-in-whole-genome-alignments-with-high-speedup</guid>
	<pubDate>Sat, 13 Apr 2019 08:55:31 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39250/darwin-wga-a-co-processor-provides-increased-sensitivity-in-whole-genome-alignments-with-high-speedup</link>
	<title><![CDATA[Darwin-WGA: A Co-processor Provides Increased Sensitivity in Whole Genome Alignments with High Speedup]]></title>
	<description><![CDATA[<p>Darwin-WGA, is the first hardware accelerator for whole genome alignment and accelerates the gapped filtering stage. Darwin-WGA also employs GACT-X, a novel algorithm used in the extension stage to align arbitrarily long genome sequences using a small on-chip memory, that provides better quality alignments at 2&times; improvement in memory and speed over the previously published GACT algorithm. Implemented on an FPGA, Darwin-WGA provides up to 24&times; improvement (performance/$) in WGA over iso-sensitive software.</p>
<p><a href="https://stanford.edu/~yatisht/pubs/darwin-wga.pdf">https://stanford.edu/~yatisht/pubs/darwin-wga.pdf</a></p><p>Address of the bookmark: <a href="https://github.com/gsneha26/Darwin-WGA" rel="nofollow">https://github.com/gsneha26/Darwin-WGA</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/40609/genome-informatics-section-lab</guid>
  <pubDate>Sat, 25 Jan 2020 06:38:23 -0600</pubDate>
  <link></link>
  <title><![CDATA[Genome Informatics Section Lab !]]></title>
  <description><![CDATA[
<p>Our section develops and applies computational methods for the analysis of massive genomics datasets, focusing on the challenges of genome sequencing and comparative genomics. We aim to improve such foundational processes and translate emerging genomic technologies into practice.</p>

<p>The Genome Informatics Section is hiring! Come join our outstanding team at the NIH’s National Human Genome Research Institute and contribute to the development of new reference genomes and computational methods for DNA sequencing and analysis. Both postdoc and PhD students positions are available. More information and application instructions follow below.</p>

<p>More at https://genomeinformatics.github.io/</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/42326/edanchin-lab</guid>
  <pubDate>Thu, 19 Nov 2020 08:00:07 -0600</pubDate>
  <link></link>
  <title><![CDATA[Edanchin Lab]]></title>
  <description><![CDATA[
<p>My main topics of interest are:</p>

<p>The impact of non tree-like evolution such as horizontal gene transfers and hybridization on species biology<br />Evolution and adaptation of animals in the absence of sexual reproduction and the underlying mechanisms<br />Genomic signatures of adaptation to a parasitic life-style</p>

<p>More at https://edanchin.org/</p>
]]></description>
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