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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/41991?offset=260</link>
	<atom:link href="https://bioinformaticsonline.com/related/41991?offset=260" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32948/simba-a-web-tool-for-managing-bacterial-genome-assembly-generated-by-ion-pgm-sequencing-technology</guid>
	<pubDate>Tue, 23 May 2017 05:28:56 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32948/simba-a-web-tool-for-managing-bacterial-genome-assembly-generated-by-ion-pgm-sequencing-technology</link>
	<title><![CDATA[SIMBA: a web tool for managing bacterial genome assembly generated by Ion PGM sequencing technology]]></title>
	<description><![CDATA[<p><span>SIMBA</span><span>, SImple Manager for Bacterial Assemblies, is a Web interface for managing assembly projects of bacterial genomes. SIMBA was created to assist bioinformaticians to assemble bacterial genomes sequenced with NextGeneration Sequencing (NGS) platforms quickly, easily and effectively. SIMBA also is open source tool, i.e., can be freely downloaded, shared and modified.</span></p>
<p>https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-016-1344-7</p><p>Address of the bookmark: <a href="http://ufmg-simba.sourceforge.net/" rel="nofollow">http://ufmg-simba.sourceforge.net/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/12870/nuclear-dynamics-lab</guid>
  <pubDate>Thu, 17 Jul 2014 15:03:27 -0500</pubDate>
  <link></link>
  <title><![CDATA[Nuclear Dynamics Lab]]></title>
  <description><![CDATA[
<p>Lab focus is to elucidate fundamental principles, new mechanisms, machineries and emergent properties that are involved in maintaining the genome and gene expression programmes for improvements in lifelong health and well-being for all.</p>

<p>More at http://www.babraham.ac.uk/our-research/nuclear-dynamics/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36594/fragscaff-genome-assembly-with-contiguity-preserving-transposition</guid>
	<pubDate>Mon, 14 May 2018 04:28:14 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36594/fragscaff-genome-assembly-with-contiguity-preserving-transposition</link>
	<title><![CDATA[fragScaff: Genome Assembly with Contiguity Preserving Transposition]]></title>
	<description><![CDATA[<p>Contiguity preserving transposition and sequencing (CPT-seq) is an entirely in vitro means of generating libraries comprised of 9216 indexed pools, each of which contains thousands of sparsely sequenced long fragments ranging from 5 kilobases to &gt;1 megabase. This software, fragScaff, leverages coincidences between the content of different pools as a source of contiguity information for scaffolding de novo genome assemblies. FragScaff is complementary to Lachesis, providing midrange contiguity to support robust, accurate chromosome-scale de novo genome assemblies without the need for laborious in vivo cloning steps.</p>
<p>Further information about fragScaff, including source code, is available at:<a href="https://sourceforge.net/projects/fragscaff/files/">https://sourceforge.net/projects/fragscaff/files</a>.</p>
<p>Manuscript describing fragScaff was published as: Adey A, Kitzman JO, Burton JN, Daza R, Kumar A, Christiansen L, Ronaghi M, Amini S, L Gunderson K, Steemers FJ, Shendure J#.&nbsp;<em>In vitro, long-range sequence information for de novo genome assembly via transposase contiguity.</em>&nbsp;Genome Research 2014 Dec;24(12):2041-9. doi:&nbsp;<a href="http://dx.doi.org/10.1101/gr.178319.114">10.1101/gr.178319.114</a>. PubMed PMID:&nbsp;<a href="http://www.ncbi.nlm.nih.gov/pubmed/25327137">25327137</a>.</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/fragscaff/files/" rel="nofollow">https://sourceforge.net/projects/fragscaff/files/</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/pages/view/44637/tools-to-access-the-quality-of-your-assembled-genome</guid>
	<pubDate>Thu, 08 Aug 2024 23:31:18 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/44637/tools-to-access-the-quality-of-your-assembled-genome</link>
	<title><![CDATA[Tools to access the quality of your assembled genome !]]></title>
	<description><![CDATA[<ul dir="auto">
<li><a href="https://github.com/linsalrob/fasta_validator">FASTA VALIDATOR</a>&nbsp;+&nbsp;<a href="https://github.com/shenwei356/seqkit">SEQKIT RMDUP</a>: FASTA validation</li>
<li><a href="https://genometools.org/tools/gt_gff3validator.html">GENOMETOOLS GT GFF3VALIDATOR</a>: GFF3 validation</li>
<li><a href="https://github.com/PlantandFoodResearch/assemblathon2-analysis/blob/a93cba25d847434f7eadc04e63b58c567c46a56d/assemblathon_stats.pl">ASSEMBLATHON STATS</a>: Assembly statistics</li>
<li><a href="https://genometools.org/tools/gt_stat.html">GENOMETOOLS GT STAT</a>: Annotation statistics</li>
<li><a href="https://github.com/ncbi/fcs">NCBI FCS ADAPTOR</a>: Adaptor contamination pass/fail</li>
<li><a href="https://github.com/ncbi/fcs">NCBI FCS GX</a>: Foreign organism contamination pass/fail</li>
<li><a href="https://gitlab.com/ezlab/busco">BUSCO</a>: Gene-space completeness estimation</li>
<li><a href="https://github.com/tolkit/telomeric-identifier">TIDK</a>: Telomere repeat identification</li>
<li><a href="https://github.com/oushujun/LTR_retriever/blob/master/LAI">LAI</a>: Continuity of repetitive sequences</li>
<li><a href="https://github.com/DerrickWood/kraken2">KRAKEN2</a>: Taxonomy classification</li>
<li><a href="https://github.com/igvteam/juicebox.js">HIC CONTACT MAP</a>: Alignment and visualisation of HiC data</li>
<li><a href="https://github.com/mummer4/mummer">MUMMER</a>&nbsp;&rarr;&nbsp;<a href="http://circos.ca/documentation/">CIRCOS</a>&nbsp;+&nbsp;<a href="https://plotly.com/">DOTPLOT</a>&nbsp;&amp;&nbsp;<a href="https://github.com/lh3/minimap2">MINIMAP2</a>&nbsp;&rarr;&nbsp;<a href="https://github.com/schneebergerlab/plotsr">PLOTSR</a>: Synteny analysis</li>
<li><a href="https://github.com/marbl/merqury">MERQURY</a>: K-mer completeness, consensus quality and phasing assessment</li>
</ul>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<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>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37759/pandaseq-is-a-program-to-align-illumina-reads-optionally-with-pcr-primers-embedded-in-the-sequence-and-reconstruct-an-overlapping-sequence</guid>
	<pubDate>Fri, 21 Sep 2018 10:19:52 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37759/pandaseq-is-a-program-to-align-illumina-reads-optionally-with-pcr-primers-embedded-in-the-sequence-and-reconstruct-an-overlapping-sequence</link>
	<title><![CDATA[PANDASEQ is a program to align Illumina reads, optionally with PCR primers embedded in the sequence, and reconstruct an overlapping sequence.]]></title>
	<description><![CDATA[<p>Development packages for zlib and libbz2 are needed, as well as a standard compiler environment. On Ubuntu, this can be installed via:</p>
<pre><code>sudo apt-get install build-essential libtool automake zlib1g-dev libbz2-dev pkg-config
</code></pre>
<p>On MacOS, the Apple Developer tools and Fink (or MacPorts or Brew) must be installed, then:</p>
<pre><code>sudo fink install bzip2-dev pkgconfig</code></pre><p>Address of the bookmark: <a href="https://github.com/neufeld/pandaseq" rel="nofollow">https://github.com/neufeld/pandaseq</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39372/irnad-a-computational-tool-for-identifying-d-modification-sites-in-rna-sequence</guid>
	<pubDate>Thu, 16 May 2019 00:20:07 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39372/irnad-a-computational-tool-for-identifying-d-modification-sites-in-rna-sequence</link>
	<title><![CDATA[iRNAD: a computational tool for identifying D modification sites in RNA sequence]]></title>
	<description><![CDATA[<p><span>iRNAD, for identifying D modification sites in RNA sequence. In this predictor, the RNA samples derived from five species were encoded by nucleotide chemical property and nucleotide density. Support vector machine was utilized to perform the classification.&nbsp;</span></p>
<p><span><a href="http://lin-group.cn/server/iRNAD/">http://lin-group.cn/server/iRNAD/</a></span></p><p>Address of the bookmark: <a href="http://lin-group.cn/server/iRNAD/" rel="nofollow">http://lin-group.cn/server/iRNAD/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/24762/postdoctoral-fellowship-in-bioinformatics-at-pesolelab</guid>
  <pubDate>Thu, 01 Oct 2015 07:20:48 -0500</pubDate>
  <link></link>
  <title><![CDATA[Postdoctoral Fellowship in Bioinformatics at pesolelab]]></title>
  <description><![CDATA[
<p>Job Description: Bioinformatics postdoc positions are available in the area of genomics with main focus on exome and RNAseq technologies by ultra high-throughput sequencing platforms. Successful applicants should have the following qualities:</p>

<p>1) demonstrated experience in Bioinformatics research,<br />2) programing experience (python and/or R, C and C++ are very welcome),<br />3) knowledge of Linux/Unix environment,<br />4) experience in handling deep-seq data,<br />5) highly motivated and hard working, and<br />6) interested to work with a multi-disciplinary team combining bioinformatics, genomics, computational biology approaches with experimental biology.</p>

<p>Our research interest covers different areas of bioinformatics and genomics in order to achieve a deeper understanding of gene and genome structure and function (please look at our PubMed publications for more details about our research http://www.ncbi.nlm.nih.gov/pubmed/?term=pesole+g).</p>

<p>Interested applicants should email the curriculum vitae to Prof. Graziano Pesole at graziano.pesole@uniba.it or Dr. Ernesto Picardi at Ernesto.picardi@uniba.it.</p>

<p>Start date: immediate</p>

<p>Duration: up to 24 months<br />Contact Person (Referent): Ernesto Picardi<br />Ref. E-Mail: ernesto.picardi@uniba.it<br />Tel: +390805443308<br />Fax: +390805443317</p>

<p>Group Web Page: http://www.pesolelab.it/</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>

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