<?xml version='1.0'?><rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:georss="http://www.georss.org/georss" xmlns:atom="http://www.w3.org/2005/Atom" >
<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/32730?offset=1550</link>
	<atom:link href="https://bioinformaticsonline.com/related/32730?offset=1550" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44591/yamp-yet-another-metagenomic-pipeline</guid>
	<pubDate>Sat, 06 Jul 2024 04:26:00 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44591/yamp-yet-another-metagenomic-pipeline</link>
	<title><![CDATA[YAMP: Yet Another Metagenomic Pipeline]]></title>
	<description><![CDATA[<p><span>YAMP is constructed on&nbsp;</span><a href="https://www.nextflow.io/docs/latest/index.html">Nextflow</a><span>, a framework based on the dataflow programming model, which allows writing workflows that are highly parallel, easily portable (including on distributed systems), and very flexible and customisable, characteristics which have been inherited by YAMP. New modules can be added easily and the existing ones can be customised -- even though we have already provided default parameters deriving from our own experience.</span></p><p>Address of the bookmark: <a href="https://github.com/alesssia/YAMP" rel="nofollow">https://github.com/alesssia/YAMP</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/10659/gps-dna-tracking-university-of-sheffield</guid>
	<pubDate>Sat, 10 May 2014 04:33:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/10659/gps-dna-tracking-university-of-sheffield</link>
	<title><![CDATA[GPS DNA tracking - University of Sheffield]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/Aap-s1kle4Q" frameborder="0" allowfullscreen></iframe>University of Sheffield geneticist and bioinformatics expert Dr Eran Elhaik demonstrates the power of his new DNA research, which allows people to discover their genetic homeland from 1000 years ago. Find out more about our biological research here http://www.sheffield.ac.uk/aps]]></description>
	
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34525/hic-pro-an-optimized-and-flexible-pipeline-for-hi-c-data-processing</guid>
	<pubDate>Wed, 06 Dec 2017 01:05:21 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34525/hic-pro-an-optimized-and-flexible-pipeline-for-hi-c-data-processing</link>
	<title><![CDATA[HiC-Pro: an optimized and flexible pipeline for Hi-C data processing]]></title>
	<description><![CDATA[<p><span>HiC-Pro was designed to process Hi-C data, from raw fastq files (paired-end Illumina data) to the normalized contact maps. Since version 2.7.0, HiC-Pro supports the main Hi-C protocols, including digestion protocols as well as protocols that do not require restriction enzyme such as DNase Hi-C. In practice, HiC-Pro can be used to process dilution Hi-C, in situ Hi-C, DNase Hi-C, Micro-C, capture-C, capture Hi-C or HiChip data.</span></p>
<p>&nbsp;</p>
<p>http://nservant.github.io/HiC-Pro/</p><p>Address of the bookmark: <a href="http://nservant.github.io/HiC-Pro/" rel="nofollow">http://nservant.github.io/HiC-Pro/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/10741/managing-and-analyzing-next-generation-sequence-data</guid>
	<pubDate>Sat, 10 May 2014 06:28:06 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/10741/managing-and-analyzing-next-generation-sequence-data</link>
	<title><![CDATA[Managing and Analyzing Next-Generation Sequence Data]]></title>
	<description><![CDATA[<p>Centralized Bioinformatics Core Facilities provide shared resources for the computational and IT requirements of the investigators in their department or institution. As such, they must be able to effectively react to new types of experimental technology. Recently faced with an unprecedented flood of data generated by the next generation of DNA sequencers, these groups found it necessary to respond quickly and efficiently to the informatics and infrastructure demands. Centralized Facilities newly facing this challenge need to anticipate time and design considerations of necessary components, including infrastructure upgrades, staffing, and tools for data analyses and management ...</p>
<p>More at http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1000369</p><p>Address of the bookmark: <a href="http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1000369" rel="nofollow">http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1000369</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38762/katuali-is-a-flexible-consensus-pipeline-implemented-in-snakemake-to-basecall-assemble-and-polish-oxford-nanopore-technologies-sequencing-data</guid>
	<pubDate>Tue, 22 Jan 2019 06:26:55 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38762/katuali-is-a-flexible-consensus-pipeline-implemented-in-snakemake-to-basecall-assemble-and-polish-oxford-nanopore-technologies-sequencing-data</link>
	<title><![CDATA[Katuali is a flexible consensus pipeline implemented in Snakemake to basecall, assemble, and polish Oxford Nanopore Technologies&#039; sequencing data]]></title>
	<description><![CDATA[<ul>
<li>Run a pipeline processing fast5s to a consensus in a single command.</li>
<li>Recommended fixed "standard" and "fast" pipelines.</li>
<li>Interchange basecaller, assembler, and consensus components of the pipelines simply by changing the target filepath.</li>
<li>Seemless distribution of tasks over local or distributed compute.</li>
<li>Highly configurable.</li>
<li>Open source (Mozilla Public License 2.0).</li>
</ul>
<p>Documentation can be found at&nbsp;<a href="https://nanoporetech.github.io/katuali/">https://nanoporetech.github.io/katuali/</a>.</p><p>Address of the bookmark: <a href="https://github.com/nanoporetech/katuali" rel="nofollow">https://github.com/nanoporetech/katuali</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/12593/visiting-scientist-computational-genomics-two-positions</guid>
  <pubDate>Mon, 07 Jul 2014 22:53:41 -0500</pubDate>
  <link></link>
  <title><![CDATA[Visiting Scientist - Computational Genomics (two positions)]]></title>
  <description><![CDATA[
<p>Scientific/Managerial &amp; International Recruitment</p>

<p>ICRISAT seeks applications from Indian nationals Visiting Scientist-Computational Genomics (2 positions), to be part of a team of Centre of Excellence in Genomics (CEG), (www.icrisat.org/ceg) to work on legume genomics projects.  The positions will be based at ICRISAT’s Headquarters in Patancheru, Hyderabad, India.</p>

<p>ICRISAT is a non-profit, non-political organization that conducts agricultural research for development in Asia and sub-Saharan Africa with a wide array of partners throughout the world. Covering 6.5 million square kilometers of land in 55 countries, the semi-arid tropics is home to over 2 billion people, with 650 million of these are the poorest of the poor. ICRISAT and its partners help empower those living in the semi-arid tropics, especially smallholder farmers, to overcome poverty, hunger, malnutrition and a degraded environment through more efficient and profitable agriculture. ICRISAT is headquartered in Greater Hyderabad, Andhra Pradesh, India and belongs to the Consortium of Centers supported by the Consultative Group on International Agricultural Research (CGIAR).</p>

<p>The Job: Responsibilities for these positions include:</p>

<p>    Analyzing and handling large-scale next generation sequencing DNA and RNA data<br />    Data mining and development of pipelines and troubleshooting<br />    Genome diversity analysis such as SNPs, Indels, Structural Variations, population structure<br />    Genome wide association study (GWAS) related analysis- LD analysis, hapmap and trait mapping<br />    Expression analysis based on RNA-Seq data, annotation, gene ontology and metabolic pathway analysis<br />    Epigenome analysis, small RNA identification<br />    Gene family analysis, sequence level protein analysis, orthology/paralogy and molecular modelling<br />    Compiling and analysis of results, writing reports and research papers</p>

<p>The Person:  Ph.D. or MSc/MTech/PGDCA with two years research experience in Biotechnology, Computational biology, Agricultural/ Plant Biotechnology, Genetics, Molecular Biology or related discipline. Good knowledge of programming/scripting in at least two of following languages: Perl, C, C++, R, Shell Scripting and Python is plus.</p>

<p>How to apply: Please apply latest by 20 July 2014.  The application should include the name of the position applied for, a letter of motivation, a full Curriculum Vita (CV), and the names and contact information of three references that are knowledgeable of the candidate’s professional qualifications and work experience. Technical details and more information about these positions can be obtained from R.K.VARSHNEY@CGIAR.ORG. All applications will be acknowledged, however only short listed candidates will be contacted.</p>

<p>Apply here https://recruit.zoho.com/ats/Portal.na?digest=T642sgLYWZOStExJ77cPrcM*sIMGZETWw4yPxngbmHA-</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41030/slr-superscaffolder-a-scaffold-assemble-pipeline-for-stlfr-reads</guid>
	<pubDate>Fri, 14 Feb 2020 14:23:30 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41030/slr-superscaffolder-a-scaffold-assemble-pipeline-for-stlfr-reads</link>
	<title><![CDATA[SLR-superscaffolder: A scaffold assemble pipeline for stLFR reads.]]></title>
	<description><![CDATA[<p>This is a scaffold assembler designed for stLFR reads[1]. It uses the link-reads information from stLFR reads to assemble contigs to scaffolds.</p>
<p>Here is an illustration of this pipeline:</p>
<p>&nbsp;<img src="https://github.com/BGI-Qingdao/SLR-superscaffolder/raw/master/image.png" alt="image" style="border: 0px;"></p><p>Address of the bookmark: <a href="https://github.com/BGI-Qingdao/SLR-superscaffolder" rel="nofollow">https://github.com/BGI-Qingdao/SLR-superscaffolder</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/11030/r-programming-and-jobs-website</guid>
	<pubDate>Sun, 25 May 2014 14:43:57 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/11030/r-programming-and-jobs-website</link>
	<title><![CDATA[R programming and Jobs website]]></title>
	<description><![CDATA[<p>Welcome to the R Jobs section of ProgrammingR.com. If your organization has an R employment opportunity that you would like to have posted here, submit it via the <a href="http://www.programmingr.com/contact" title="contact page">contact page</a>. Prospective employees: use the contact information provided in the position listing to apply or contact the hiring organization.</p><p>Address of the bookmark: <a href="http://www.programmingr.com/category/stype/r-job-listings/" rel="nofollow">http://www.programmingr.com/category/stype/r-job-listings/</a></p>]]></description>
	<dc:creator>Pragati Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42038/pyparanoid-a-pipeline-for-rapid-identification-of-homologous-gene-families-in-a-set-of-genomes</guid>
	<pubDate>Thu, 13 Aug 2020 10:06:19 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42038/pyparanoid-a-pipeline-for-rapid-identification-of-homologous-gene-families-in-a-set-of-genomes</link>
	<title><![CDATA[PyParanoid: a pipeline for rapid identification of homologous gene families in a set of genomes]]></title>
	<description><![CDATA[<p>PyParanoid is a pipeline for rapid identification of homologous gene families in a set of genomes - a central task of any comparative genomics analysis. The "gold standard" for identifying homologs is to use reciprocal best hits (RBHs) which depends on performing a all-vs-all sequence comparison, usually using BLAST, to determine homology. However, these methods are computationally expensive, requiring&nbsp;O(n2)&nbsp;resources to identify RBHs. This is problematic, as the modern deluge of sequencing data means that comparative genomics analyses could be performed on datasets of thousands of strains.</p><p>Address of the bookmark: <a href="https://github.com/ryanmelnyk/PyParanoid" rel="nofollow">https://github.com/ryanmelnyk/PyParanoid</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43353/judi-just-do-it</guid>
	<pubDate>Mon, 06 Sep 2021 02:44:35 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43353/judi-just-do-it</link>
	<title><![CDATA[JUDI: Just Do It]]></title>
	<description><![CDATA[<p><em>judi</em><span>&nbsp;comes from the idea of bringing the power and efficiency of&nbsp;</span><em>doit</em><span>&nbsp;to execute any kind of task under many combinations of parameter settings.</span></p>
<p><span>https://github.com/ncbi/JUDI</span></p><p>Address of the bookmark: <a href="https://github.com/ncbi/JUDI" rel="nofollow">https://github.com/ncbi/JUDI</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

</channel>
</rss>