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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/8382?offset=960</link>
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	<item>
	<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>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43243/interactive-bioinformatics-resources</guid>
	<pubDate>Thu, 12 Aug 2021 00:09:00 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43243/interactive-bioinformatics-resources</link>
	<title><![CDATA[Interactive Bioinformatics Resources !]]></title>
	<description><![CDATA[<p>Learn how to use bioinformatics tools right from your browser.<br>Everything runs in a sandbox, so you can experiment all you want.</p>
<p>More at sandbox.bio</p><p>Address of the bookmark: <a href="http://sandbox.bio" rel="nofollow">http://sandbox.bio</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44279/bioinformatics-training-material</guid>
	<pubDate>Sat, 18 Mar 2023 11:26:18 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44279/bioinformatics-training-material</link>
	<title><![CDATA[Bioinformatics Training Material !]]></title>
	<description><![CDATA[<p><span>Glittr</span>&nbsp;is a curated list of bioinformatics training material.<br>All material is:</p>
<ul>
<li>In a GitHub or GitLab repository</li>
<li>Free to use</li>
<li>Written in markdown or similar</li>
</ul>
<p><span>NOTE:</span>&nbsp;This list of courses is selected only based on the above criteria.<br>There are no checks on quality.</p>
<p>https://glittr.org/?per_page=25&amp;sort_by=stargazers&amp;sort_direction=desc</p><p>Address of the bookmark: <a href="https://glittr.org/?per_page=25&amp;sort_by=stargazers&amp;sort_direction=desc" rel="nofollow">https://glittr.org/?per_page=25&amp;sort_by=stargazers&amp;sort_direction=desc</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44516/16srna-database-download</guid>
	<pubDate>Wed, 24 Apr 2024 04:33:15 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44516/16srna-database-download</link>
	<title><![CDATA[16sRNA Database Download]]></title>
	<description><![CDATA[<p>Downloading 16S rRNA databases can be crucial for various bioinformatics analyses, especially in microbiome research. However, it's important to note that databases can vary based on your specific needs, such as the taxonomic coverage you require or the type of analysis you're performing. Here's a general guideline on how you can obtain 16S rRNA databases:</p><ol>
<li>
<p><span>NCBI (National Center for Biotechnology Information)</span>:</p>
<ul>
<li>NCBI provides various databases related to genetic information, including 16S rRNA sequences.</li>
<li>You can access the 16S ribosomal RNA sequences from NCBI's Nucleotide database (<a href="https://www.ncbi.nlm.nih.gov/nucleotide/" target="_new">https://www.ncbi.nlm.nih.gov/nucleotide/</a>).</li>
<li>Perform a search using keywords like "16S rRNA" or specific bacterial names to find relevant sequences.</li>
<li>You can download sequences individually or in batches using the provided tools.</li>
</ul>
</li>
<li>
<p><span>GreenGenes</span>:</p>
<ul>
<li>GreenGenes is a widely used 16S rRNA gene sequence database.</li>
<li>You can access it at <a target="_new">http://greengenes.secondgenome.com/</a>.</li>
<li>GreenGenes provides precompiled databases for various purposes, including classification, alignment, and phylogenetic analysis.</li>
</ul>
</li>
<li>
<p><span>SILVA</span>:</p>
<ul>
<li>SILVA (<a href="https://www.arb-silva.de/" target="_new">https://www.arb-silva.de/</a>) is another comprehensive database for ribosomal RNA (rRNA) sequences.</li>
<li>It covers not only 16S rRNA but also other ribosomal RNA sequences.</li>
<li>SILVA provides precompiled databases for various purposes, including taxonomic classification and alignment.</li>
</ul>
</li>
<li>
<p><span>Ribosomal Database Project (RDP)</span>:</p>
<ul>
<li>RDP (<a target="_new">http://rdp.cme.msu.edu/</a>) is a curated database that offers 16S rRNA sequences.</li>
<li>It provides tools for sequence analysis and classification.</li>
<li>You can download sequences and taxonomy information from their website.</li>
</ul>
</li>
<li>
<p><span>QIIME (Quantitative Insights Into Microbial Ecology)</span>:</p>
<ul>
<li>QIIME (<a href="https://qiime2.org/" target="_new">https://qiime2.org/</a>) is a widely used bioinformatics platform for microbiome analysis.</li>
<li>It provides tools for analyzing microbial communities, including processing 16S rRNA sequences.</li>
<li>QIIME often includes its own preprocessed 16S rRNA databases that can be used for analysis within the platform.</li>
</ul>
</li>
</ol><p>Before downloading any database, make sure to read the terms of use and citation requirements, as some databases may have specific usage policies. Additionally, consider the compatibility of the database with your analysis pipeline and software tools.</p><p>&nbsp;</p><p>NCBI 16s RNA database location&nbsp;ftp://ftp.ncbi.nih.gov/blast/db/16SMicrobial.tar.gz</p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>

<item>
  <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>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/view/119</guid>
	<pubDate>Wed, 10 Jul 2013 14:35:34 -0500</pubDate>
	<link>https://bioinformaticsonline.com/view/119</link>
	<title><![CDATA[Which are the best statistical programming languages to study for a bioinformatician?]]></title>
	<description><![CDATA[<p><span>In Bio-informatics based&nbsp;genome sequencing and predicting metabolic pathways&nbsp;research jobs&nbsp;I used Matlab, SAS, SPSS, R and several Bioconductor packages. Matlab had a lot of powerful tools and was easy to use, whereas SPSS is for non-programmers and R need programming skills. I am wondering what other people think is best? or there might not be one specific language but a few that lend themselves best to Bio-informatics work that is math heavy and deals with a large amount of data.</span></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/857/smyth-lab</guid>
  <pubDate>Sun, 14 Jul 2013 12:26:18 -0500</pubDate>
  <link></link>
  <title><![CDATA[Smyth Lab]]></title>
  <description><![CDATA[
<p>Statistical functional genomics in experimental medicine<br />The genome projects and the accelerated development of high-throughput genomic technologies such as microarrays have revolutionised biology. Making the most of this revolution requires the marriage of researchers from mathematical and biological backgrounds.</p>

<p>Research Area:<br />Linear models for microarray data<br />Digital gene expression technologies<br />Detection of molecular pathways<br />Bioinformatics resources for medical research</p>

<p>Link @ http://www.wehi.edu.au/faculty_members/professor_gordon_smyth/</p>
]]></description>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/1215/livestock-functional-genomics-summer-school-lfg-2013</guid>
  <pubDate>Fri, 02 Aug 2013 09:57:37 -0500</pubDate>
  <link></link>
  <title><![CDATA[Livestock Functional Genomics Summer School (LFG 2013)]]></title>
  <description><![CDATA[
<p>*Livestock Functional Genomics Summer School - Call for applications*</p>

<p>1st Livestock Functional Genomics Summer School (LFG 2013).</p>

<p>This School was designed for graduate students and early-stage researchers with interest in livestock genomics, who are engaged in projects that require knowledge in the field of computational biology.</p>

<p>Sixty selected participants will spend 13 days receiving theoretical and practical training in genomic data handling from internationally renowned experts.</p>

<p>After the course, the participant should understand the basis and the context of livestock big molecular data, and be able to manipulate high density genotypes, whole genome sequences and transcriptome data.</p>

<p>The Summer School will be held in Araçatuba-SP Brazil, from the 13th to the 21st of September 2013.</p>

<p>All accepted participants will have *expenses fully covered (air ticket, hotel and meals)*, including a free pass to the 5th International Symposium on Animal Functional Genomics http://www.isafg2013.org.br </p>

<p>Applicants will be selected based on their résumés. Application date is due by August 10th.  Results will be announced in August 12th.  </p>

<p>Please consult website: http://www.sciencesatellite.org.br/sschool</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/3918/the-human-genome-project-video-3d-animation-introduction-low</guid>
	<pubDate>Sat, 24 Aug 2013 19:01:19 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/3918/the-human-genome-project-video-3d-animation-introduction-low</link>
	<title><![CDATA[The Human Genome Project Video   3D Animation Introduction Low)]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/YxoQFSBwyms" frameborder="0" allowfullscreen></iframe>]]></description>
	
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