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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/33651?offset=90</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38012/cosine-non-seeding-method-for-mapping-long-noisy-sequences</guid>
	<pubDate>Fri, 26 Oct 2018 00:41:59 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38012/cosine-non-seeding-method-for-mapping-long-noisy-sequences</link>
	<title><![CDATA[COSINE: non-seeding method for mapping long noisy sequences]]></title>
	<description><![CDATA[<p><span>Third generation sequencing (TGS) are highly promising technologies but the long and noisy reads from TGS are difficult to align using existing algorithms. Here, we present COSINE, a conceptually new method designed specifically for aligning long reads contaminated by a high level of errors.</span></p><p>Address of the bookmark: <a href="https://github.com/SUwonglab/COSINE" rel="nofollow">https://github.com/SUwonglab/COSINE</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/42206/pollard-lab</guid>
  <pubDate>Fri, 25 Sep 2020 20:20:50 -0500</pubDate>
  <link></link>
  <title><![CDATA[Pollard Lab]]></title>
  <description><![CDATA[
<p>We are a bioinformatics research lab focused on developing novel methods and using them to study genome evolution, organization, and regulation. Our mission is to decode biomedical knowledge that is missed without rigorous statistical approaches.</p>

<p>http://docpollard.org/</p>

<p>Tools</p>

<p>http://docpollard.org/resources/software/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44906/winpca</guid>
	<pubDate>Tue, 23 Sep 2025 03:58:13 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44906/winpca</link>
	<title><![CDATA[WinPCA]]></title>
	<description><![CDATA[<p><span>A package for windowed principal component analysis. WinPCA performs principal component analyses (PCA) in sliding windows along chromosomes. Both hard-called genotypes (input: VCF or TSV) or genotype likelihoods (input: VCF, TSV or BEAGLE) encoding&nbsp;</span><span>biallellic SNPs</span><span>&nbsp;are accepted. WinPCA uses&nbsp;</span><a href="https://scikit-allel.readthedocs.io/en/stable/stats/decomposition.html?highlight=pca">scikit-allel</a><span>&nbsp;to perfom PCAs on genotype data and&nbsp;</span><a href="https://github.com/Rosemeis/pcangsd">PCAngsd</a><span>&nbsp;methods for genotype likelihood (GL, PL) data.</span></p><p>Address of the bookmark: <a href="https://github.com/MoritzBlumer/winpca" rel="nofollow">https://github.com/MoritzBlumer/winpca</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34940/jpred4-a-protein-secondary-structure-prediction-server</guid>
	<pubDate>Fri, 29 Dec 2017 16:14:28 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34940/jpred4-a-protein-secondary-structure-prediction-server</link>
	<title><![CDATA[JPred4: A Protein Secondary Structure Prediction Server]]></title>
	<description><![CDATA[<p><span>JPred4 (</span><a href="http://www.compbio.dundee.ac.uk/jpred4" target="">http://www.compbio.dundee.ac.uk/jpred4</a><span>) is the latest version of the popular JPred protein secondary structure prediction server which provides predictions by the JNet algorithm, one of the most accurate methods for secondary structure prediction.</span></p><p>Address of the bookmark: <a href="http://www.compbio.dundee.ac.uk/jpred4/" rel="nofollow">http://www.compbio.dundee.ac.uk/jpred4/</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33901/rnacon-web-server-for-the-prediction-and-classification-of-non-coding-rnas</guid>
	<pubDate>Mon, 17 Jul 2017 04:55:11 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33901/rnacon-web-server-for-the-prediction-and-classification-of-non-coding-rnas</link>
	<title><![CDATA[RNAcon: web-server for the prediction and classification of non-coding RNAs]]></title>
	<description><![CDATA[<p style="text-align: justify;">RNAcon is a web-server for the prediction and classification of non-coding RNAs. It uses SVM-based model for the discrimination between coding and ncRNAs and RandomForest-based prediction model for the classification of ncRNAs into different classes. The structural information based graph properties were used for the development of prediction model.</p>
<p style="text-align: justify;">The&nbsp;<a href="http://crdd.osdd.net/raghava/rnacon/RNAcon_v1.0.tar.gz">standalone version (Linux-based command-line) of RNAcon</a>&nbsp;is freely available for the global scientific community.</p>
<p style="text-align: justify;">Reference:&nbsp;<a href="http://www.biomedcentral.com/1471-2164/15/127/abstract">Panwar, B.; Arora, A. and Raghava, G.P.S. (2014) Prediction and classification of ncRNAs using structural information</a>BMC Genomics 2014, 15:127</p><p>Address of the bookmark: <a href="http://crdd.osdd.net/raghava/rnacon/" rel="nofollow">http://crdd.osdd.net/raghava/rnacon/</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44892/grannot</guid>
	<pubDate>Sun, 31 Aug 2025 06:21:50 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44892/grannot</link>
	<title><![CDATA[GrAnnoT]]></title>
	<description><![CDATA[<p>GrAnnoT is an annotation transfer tool for pangenome graphs. It can transfer linear genome annotations to a pangenome graph containing the genome, and also transfer the pangenome graph's annotations on the genomes it contains. It also outputs complementary information such as the alignments of the transfered genes, or a presence-absence matrix.</p><p>Address of the bookmark: <a href="https://forge.ird.fr/diade/dynadiv/grannot" rel="nofollow">https://forge.ird.fr/diade/dynadiv/grannot</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
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