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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/23680?offset=1140</link>
	<atom:link href="https://bioinformaticsonline.com/related/23680?offset=1140" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/14191/scalpel</guid>
	<pubDate>Wed, 20 Aug 2014 02:07:58 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/14191/scalpel</link>
	<title><![CDATA[Scalpel]]></title>
	<description><![CDATA[<p>A team from Cold Spring Harbor Laboratory has released an algorithm, called Scalpel, for finding insertions and deletions in next generation sequencing data sets. Scalpel, which is open source and <a href="http://scalpel.sourceforge.net/" title="available for download">available for download</a> on SourceForge,&nbsp;<span>outperformed the popular tools GATK HaplotypeCaller and SOAPindel in test runs on both simulated and real whole human exomes.</span></p><p>Like other indel callers, Scalpel works by performing <em>de novo</em>&nbsp;assembly of regions of interest, so that misalignment to the reference genome cannot obscure the presence of an insertion or deletion. Scalpel's innovation is to repeatedly check its assembly before comparing to the reference genome, to account for simple sequence repeats that are a regular source of error in indel calling. When Scalpel assembles an exon, it collects reads that map to that exon (including partial matches), splits them into k-mers, and creates a de Bruijn graph to span the exon; however, if it detects repeats in the map, it iteratively increases the size of the k-mers by one base until the repeats are eliminated. This ensures that the final assembly of the exon is highly accurate while minimizing compute time.</p><p>The Cold Spring Harbor team's validation of Scalpel, <a href="http://www.nature.com/nmeth/journal/vaop/ncurrent/full/nmeth.3069.html" title="published over the weekend in Nature Methods">published over the weekend in <em>Nature Methods</em></a>, compares Scalpel's performance on a live whole exome against HaplotypeCaller and SOAPindel. The donor is an individual with serious neurological disorders, which may be linked to a high incidence of indels. One thousand indels from this individual's exome, called by one or more of the informatics pipelines, were selected for focused resequencing. This resequencing revealed a 77% true positive rate for Scalpel calls, dramatically better than the rates for either of the competing tools; Scalpel performed especially well with indels longer than five base pairs, a traditional weak point for indel callers.</p><p>Finally, the authors demonstrate Scalpel's use on a large set of genetic data from nearly 600 families who donated samples to the Simons Simplex Collection, a project of the Simons Foundation Autism Research Initiative. Scalpel found a very high enrichment for indels in children affected by autism, compared with their unaffected siblings, a pattern that persisted even after excluding common variants.</p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/43284/tech-and-bioinformatics-roles-at-basepaws</guid>
  <pubDate>Wed, 18 Aug 2021 23:34:25 -0500</pubDate>
  <link></link>
  <title><![CDATA[Tech and Bioinformatics roles at Basepaws]]></title>
  <description><![CDATA[
<p>Basepaws is an LA-based pet genomics company, quickly growing and focused on feline and canine at-home genetic and biome tests, along with many other projects and products in the works. Thank you for taking a look!</p>

<p>Bioinformatics : https://www.linkedin.com/jobs/view/2681785372/</p>

<p>Engineer: https://www.linkedin.com/jobs/view/2681796993/</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/44352/bioinformatics-tools-for-genome-assembly</guid>
	<pubDate>Mon, 24 Jul 2023 07:04:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/44352/bioinformatics-tools-for-genome-assembly</link>
	<title><![CDATA[Bioinformatics tools for genome assembly !]]></title>
	<description><![CDATA[<p>There are numerous genome assembly tools available, each with its strengths and weaknesses. Here is a list of some widely used genome assembly tools as of my last update in September 2021:</p><ol>
<li>
<p><span>SPAdes:</span> An assembler specifically designed for single-cell and multi-cell bacterial genomes, as well as small eukaryotic genomes.</p>
</li>
<li>
<p><span>ABySS:</span> A parallelized assembler for large genomes that uses de Bruijn graphs.</p>
</li>
<li>
<p><span>Velvet:</span> Another de Bruijn graph-based assembler optimized for short-read sequencing data.</p>
</li>
<li>
<p><span>SOAPdenovo:</span> A de Bruijn graph-based assembler designed for short reads, widely used for assembling large and complex genomes.</p>
</li>
<li>
<p><span>MaSuRCA:</span> A hybrid assembler that combines data from multiple sequencing technologies, such as Illumina and PacBio.</p>
</li>
<li>
<p><span>Canu:</span> A long-read assembler optimized for PacBio and Oxford Nanopore sequencing data.</p>
</li>
<li>
<p><span>Flye:</span> A long-read assembler suitable for bacterial and small eukaryotic genomes.</p>
</li>
<li>
<p><span>SMARTdenovo:</span> An assembler designed for long reads, particularly suited for PacBio data.</p>
</li>
<li>
<p><span>SPAdes Long Read (SPAdesLR):</span> An extension of SPAdes for long-read data, such as those from PacBio or Nanopore.</p>
</li>
<li>
<p><span>Minia:</span> An assembler optimized for low memory consumption, suitable for small and medium-sized genomes.</p>
</li>
<li>
<p><span>Unicycler:</span> A hybrid assembler that combines short and long reads for circular bacterial genome assembly.</p>
</li>
<li>
<p><span>wtdbg2:</span> A de Bruijn graph assembler for long reads, efficient for very large genomes.</p>
</li>
<li>
<p><span>Shasta:</span> A long-read assembler that uses the Overlap-Layout-Consensus approach, suitable for PacBio and Nanopore data.</p>
</li>
<li>
<p><span>Sparc:</span> An assembler designed to handle noisy long reads from Nanopore sequencing.</p>
</li>
<li>
<p><span>CANA:</span> An assembler for metagenomic data, particularly for complex and diverse microbial communities.</p>
</li>
<li>
<p><span>Ra</span> Assembler: A metagenome assembler for long reads, designed for highly complex metagenomic samples.</p>
</li>
</ol><p>Please note that the field of bioinformatics is constantly evolving, and new assembly tools may have emerged since my last update. Additionally, the performance of these tools can vary depending on the characteristics of the sequencing data and the genome being assembled. When selecting an assembly tool, consider the specific requirements of your project, the available data types, and the computational resources at your disposal. Always refer to the respective tool's documentation and publications for the most up-to-date information and recommendations.</p>]]></description>
	<dc:creator>BioStar</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/44407/mopga-2024-visiting-fellowship-program-for-early-career-researchers</guid>
  <pubDate>Fri, 10 Nov 2023 02:30:22 -0600</pubDate>
  <link></link>
  <title><![CDATA[MOPGA 2024 Visiting Fellowship Program for Early Career Researchers]]></title>
  <description><![CDATA[
<p>France, as a major player in the fight against climate change and guarantor of the spirit of the Paris Agreement, is launching a new MOPGA visiting fellowship program geared towards strengthening scientific contributions to climate change issues raised by the COPs. </p>

<p>This seventh Make Our Planet Great Again (MOPGA) call for applications is intended to welcome at least 40 early career researchers wishing to carry out their research in France. The program is funded by the French Ministry for Europe and Foreign Affairs, in collaboration with the French Ministry for Higher Education and Research, and implemented by Campus France. </p>

<p>The MOPGA 2024 Visiting Fellowship Program for Early Career Researchers will support researchers working on topics listed in the "Research Themes" section.</p>

<p>More at https://www.campusfrance.org/en/mopga-2024</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/4107/natasa-przulj-lab</guid>
  <pubDate>Fri, 30 Aug 2013 06:29:17 -0500</pubDate>
  <link></link>
  <title><![CDATA[Nataša Pržulj Lab]]></title>
  <description><![CDATA[
<p>Nataša Pržulj Lab's research involves applications of graph theory, mathematical modeling, and computational techniques to solving large-scale problems in computational and systems biology.They are interested in computational and theoretical solutions to practical problems in many areas of systems biology, planar cell polarity, proteomics, cancer informatics, and drug discovery and design.</p>

<p>More at http://www.doc.ic.ac.uk/~natasha/index.html</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/24984/ra-bioinformatics-at-nii</guid>
  <pubDate>Thu, 22 Oct 2015 01:56:26 -0500</pubDate>
  <link></link>
  <title><![CDATA[RA Bioinformatics at NII]]></title>
  <description><![CDATA[
<p>NATIONAL INSTITUTE OF IMMUNOLOGY</p>

<p>NEW DELHI-110067</p>

<p>Applications are invited for the position of Research Associate (RA) for the following time-bound sponsored project as per the details given below:</p>

<p>1. BTIS project entitled, “National Infrastructural Facility in the Area of Immunology” funded by DBT</p>

<p>Research Associate (One Position only)</p>

<p>Dr. Debasisa Mohanty Staff Scientist-VI deb@nii.res.in</p>

<p>Educational Qualifications: Ph.D in Bioinformatics or Biological Sciences or Biotechnology with research experience and publication record in indexed peer reviewed journals in the area of bioinformatics or computational biology.</p>

<p>Emoluments: The selected candidates will draw consolidated emoluments as per Institute Rules, depending upon qualifications &amp; experience Research Associate: Rs. 36,000/- per month plus 30% HRA</p>

<p>Job description &amp; Desired Knowledge: The candidate should be well versed in Programming in PERL/C++, HTML, CGI, web sever and portal development, computational analysis of protein structure &amp; function, molecular dynamics simulations and use of high performance computing systems.</p>

<p>General Terms &amp; Conditions:-</p>

<p>1. The candidates selected for the above posts will be on contract for one year or duration of the project whichever is shorter, at a time.</p>

<p>2. No hostel/ housing facility will be provided.</p>

<p>3. Applicants may clearly mention the category they belong to i.e. SC/ST/OBC/PH and attach documentary proof of the same.</p>

<p>4. No TA/DA will be paid for attending the interview, if called for.</p>

<p>5. Apart from sending application in the prescribed format given below, candidates should send complete Curriculum Vitae along with the names of three referees. Curriculum Vitae should contain details of the experimental expertise and list of publications. 6. Canvassing in any form will be a disqualification.</p>

<p>HOW TO APPLY Interested candidates may apply directly, STRICTLY IN THE PRESCRIBED FORMAT GIVEN BELOW, through e-mail, to the Investigator of the project, clearly indicating the name of the project along with their complete C.V., Email ID, fax numbers, telephone numbers. Only Short listed candidates will be called for interview and they required to submit attested copies of all their certificates and a Demand Draft of Rs 100/- drawn on Canara Bank or Indian Bank payable at Delhi/New Delhi in favour of the Director, NII (SC/ST/PH and Women candidates are exempted from payment of fees) subject to submission of documentary proof), at the time of interview. (E-MAIL APPLICATIONS SHOULD MENTION BTIS-RA 2015 IN THE SUBJECT LINE)</p>

<p>LAST DATE OF RECEIPT OF APPLICATIONS: 29th October, 2015</p>

<p>Advertisement:</p>

<p>www1.nii.res.in/sites/default/files/projectappointments-Dr.Mohanty-29oct2015.pdf</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35418/karyoploter-plot-whole-genomes-with-arbitrary-data</guid>
	<pubDate>Fri, 02 Feb 2018 03:24:28 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35418/karyoploter-plot-whole-genomes-with-arbitrary-data</link>
	<title><![CDATA[karyoploteR: plot whole genomes with arbitrary data]]></title>
	<description><![CDATA[<p><span><a href="http://bioconductor.org/packages/karyoploteR">karyoploteR</a></span><span>&nbsp;is an R package to create karyoplots, that is, representations of whole genomes with arbitrary data plotted on them. It is inspired by the R base graphics system and does not depend on other graphics packages. The aim of karyoploteR is to offer the user an easy way to plot data along the genome to get broad genome-wide view to facilitate the identification of genome wide relations and distributions.</span></p><p>Address of the bookmark: <a href="https://bernatgel.github.io/karyoploter_tutorial/" rel="nofollow">https://bernatgel.github.io/karyoploter_tutorial/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34488/scripts-for-the-analysis-of-hgt-in-genome-sequence-data</guid>
	<pubDate>Wed, 29 Nov 2017 16:44:10 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34488/scripts-for-the-analysis-of-hgt-in-genome-sequence-data</link>
	<title><![CDATA[Scripts for the analysis of HGT in genome sequence data.]]></title>
	<description><![CDATA[<p><span>Scripts for the analysis of HGT in genome sequence data</span></p><p>Address of the bookmark: <a href="https://github.com/reubwn/hgt" rel="nofollow">https://github.com/reubwn/hgt</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36271/heap-a-highly-sensitive-and-accurate-snp-detection-tool-for-low-coverage-high-throughput-sequencing-data</guid>
	<pubDate>Thu, 19 Apr 2018 08:06:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36271/heap-a-highly-sensitive-and-accurate-snp-detection-tool-for-low-coverage-high-throughput-sequencing-data</link>
	<title><![CDATA[Heap: a highly sensitive and accurate SNP detection tool for low-coverage high-throughput sequencing data]]></title>
	<description><![CDATA[<p><span>Heap, that enables robustly sensitive and accurate calling of SNPs, particularly with a low coverage NGS data, which must be aligned to the reference genome sequences in advance. To reduce false positive SNPs, Heap determines genotypes and calls SNPs at each site except for sites at the both end of reads or containing a minor allele supported by only one read. Performance comparison with existing tools showed that Heap achieved the highest F-scores with low coverage (7X) restriction-site associated DNA sequencing reads of sorghum and rice individuals. This will facilitate cost-effective GWAS and GP studies in this NGS era. Code and documentation of Heap are freely available from&nbsp;</span><a href="https://github.com/meiji-bioinf/heap">https://github.com/meiji-bioinf/heap</a><span>&nbsp;and our web site (</span><a href="http://bioinf.mind.meiji.ac.jp/lab/en/tools.html">http://bioinf.mind.meiji.ac.jp/lab/en/tools.html</a><span>).</span></p><p>Address of the bookmark: <a href="https://github.com/meiji-bioinf/heap" rel="nofollow">https://github.com/meiji-bioinf/heap</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37259/epiviz-an-interactive-visualization-tool-for-functional-genomics-data</guid>
	<pubDate>Mon, 09 Jul 2018 05:27:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37259/epiviz-an-interactive-visualization-tool-for-functional-genomics-data</link>
	<title><![CDATA[Epiviz: an interactive visualization tool for functional genomics data.]]></title>
	<description><![CDATA[<p><span>Epiviz is an interactive visualization tool for functional genomics data. It supports genome navigation like other genome browsers, but allows multiple visualizations of data within genomic regions using scatterplots, heatmaps and other user-supplied visualizations. It also includes data from the&nbsp;</span><a href="http://barcode.luhs.org/" target="_blank">Gene Expression Barcode project</a><span>&nbsp;for transcriptome visualization. It has a flexible plugin framework so users can add</span><a href="http://d3js.org/" target="_blank">d3</a><span>&nbsp;visualizations. You can see a video tour&nbsp;</span><a href="http://youtu.be/099c4wUxozA" target="_blank">here</a><span>.</span></p>
<p><span>https://bioconductor.org/packages/release/bioc/html/epivizr.html</span></p>
<p><span>https://github.com/epiviz</span></p>
<p><span>https://github.com/epiviz/epiviz</span></p><p>Address of the bookmark: <a href="https://epiviz.github.io/" rel="nofollow">https://epiviz.github.io/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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