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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/30971?offset=130</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30625/pandaseq</guid>
	<pubDate>Mon, 23 Jan 2017 04:54:32 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30625/pandaseq</link>
	<title><![CDATA[PANDASEQ]]></title>
	<description><![CDATA[<p>PANDASEQ assembles paired-end Illumina reads into sequences, trying to correct for errors and uncalled bases. The assembler reads two files in FASTQ format with quality information. If amplification primers were used (e.g., to isolate a variable region of the 16S gene, or the constant regions around zinc finger binding residues), they can be removed from the sequence during assembly. The final sequence will correct any uncalled bases in the overlapping region using the complementary strand. When mismatches occur in the overlapping region, the base with the better quality score is chosen.<br>The algorithm is as follows:<br><br>1.Find the positions where the forward and reverse primers match best above the threshold and discard the ends of the sequence, including the primer.<br>2.Pick and overlap to maximise the probability of the forward and reverse reads having come from a single piece of DNA.<br>3.Identify the masking of the end of the read with the quality score B or # as done by CASAVA and adjust the probabilities in this region.<br>4.Construct an assembled sequence between the primers and calculate the quality.<br>5.Check for various constraints, including quality, length, uncalled bases, and user-supplied modules.</p>
<p>http://neufeldserver.uwaterloo.ca/~apmasell/pandaseq_man1.html</p><p>Address of the bookmark: <a href="http://neufeldserver.uwaterloo.ca/~apmasell/pandaseq_man1.html" rel="nofollow">http://neufeldserver.uwaterloo.ca/~apmasell/pandaseq_man1.html</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/32713/salzberg-lab</guid>
  <pubDate>Mon, 15 May 2017 05:14:01 -0500</pubDate>
  <link></link>
  <title><![CDATA[Salzberg lab]]></title>
  <description><![CDATA[
<p>We are a computational biology lab that develops novel methods for analysis of DNA and RNA sequences. Our research includes software for aligning and assembling RNA-seq data, whole-genome assembly, and microbiome analysis. We work closely with biomedical scientists to apply these methods to current problems arising in a broad spectrum of biological and medical research areas. We’re also part of the Center for Computational Biology, a group of 20+ faculty members and their labs at Johns Hopkins working on computational, statistical, and mathematical methods that can turn massive genomic data sets into biologically and clinically useful information.</p>

<p>https://salzberg-lab.org/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36954/mscaffolder-a-comparative-genome-scaffolding-tool</guid>
	<pubDate>Fri, 15 Jun 2018 04:48:01 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36954/mscaffolder-a-comparative-genome-scaffolding-tool</link>
	<title><![CDATA[mScaffolder: A comparative genome scaffolding tool]]></title>
	<description><![CDATA[<p>A comparative genome scaffolding tool based on MUMmer</p>
<p>mScaffolder scaffolds a genome using an existing high quality genome as the reference. It aligns the two genomes using nucmer utility from MUMmer and then orders and orients the contigs of the candidate genome guided by their alignments to the reference genome. Please send your questions and comments to&nbsp;<a href="mailto:mchakrab@uci.edu">mchakrab@uci.edu</a>.</p>
<p><span>Citation</span><span>&nbsp;</span><a href="https://www.nature.com/articles/s41588-017-0010-y">https://www.nature.com/articles/s41588-017-0010-y</a></p><p>Address of the bookmark: <a href="https://github.com/mahulchak/mscaffolder" rel="nofollow">https://github.com/mahulchak/mscaffolder</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40465/airlift-a-methodology-and-tool-for-comprehensively-moving-mappings-and-annotations-from-one-genome-to-another-similar-genome</guid>
	<pubDate>Mon, 23 Dec 2019 10:20:13 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40465/airlift-a-methodology-and-tool-for-comprehensively-moving-mappings-and-annotations-from-one-genome-to-another-similar-genome</link>
	<title><![CDATA[AirLift, a methodology and tool for comprehensively moving mappings and annotations from one genome to another similar genome]]></title>
	<description><![CDATA[<p>We propose AirLift, a methodology and tool for comprehensively moving mappings and annotations from one genome to another similar genome while maintaining the accuracy of a full mapper.</p><p>Address of the bookmark: <a href="https://github.com/CMU-SAFARI/AirLift" rel="nofollow">https://github.com/CMU-SAFARI/AirLift</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/13226/you-and-your-friend-have-similar-dna</guid>
	<pubDate>Sun, 27 Jul 2014 20:44:05 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/13226/you-and-your-friend-have-similar-dna</link>
	<title><![CDATA[You and your friend have similar DNA !!!]]></title>
	<description><![CDATA[<p>New research out of Massachusetts claims that people often choose friends that are similar to them in genetics and they are more accurate than you might suppose. A study published on PNAS&nbsp;http://www.pnas.org/content/111/Supplement_3/10796.full found that people are apt to pick friends who are genetically similar to themselves - so much so that friends tend to be as alike at the genetic level as a person's fourth cousin.</p><div style="text-align: center;"><img src="http://i.kinja-img.com/gawker-media/image/upload/s--CwLwHa43--/18fbmlokxcmqcjpg.jpg" alt="image" width="300" height="271" style="border: 0px; border: 0px;"></div><p>Scientists with a long-running Framingham Heart Study looked at 1,932 people (examination of about 1.5 million markers of genetic variations), comparing unrelated friends to unrelated strangers. They found that friends shared about 1% of their genes &mdash; a percentage much higher than those shared with strangers.This new findings made it clear that people have more DNA in common with those who are selected as friends than with strangers in the same population.&nbsp;</p><p>The genes that lined up the most were olfactory genes, which deal with smell. The ones that lined up the least were immune system genes. The researchers weren't sure why that happened :/. Olfactory genes might be a straightforward explanation: People who like the same smells tend to be drawn to similar environments, where they meet others with the same tendencies.</p><p>Reference:</p><p>http://www.pnas.org/content/111/Supplement_3/10796.full</p><p>Image : http://i.kinja-img.com</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26414/advanced-bash-scripting-guide</guid>
	<pubDate>Thu, 18 Feb 2016 04:50:51 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26414/advanced-bash-scripting-guide</link>
	<title><![CDATA[Advanced Bash-Scripting Guide]]></title>
	<description><![CDATA[<p>This tutorial assumes no previous knowledge of scripting or programming, yet progresses rapidly toward an intermediate/advanced level of instruction <em>. . . all the while sneaking in little nuggets of <span>UNIX</span>&reg; wisdom and lore</em>. It serves as a textbook, a manual for self-study, and as a reference and source of knowledge on shell scripting techniques. The exercises and heavily-commented examples invite active reader participation, under the premise that <tt><strong>the only way to really learn scripting is to write scripts</strong></tt>.</p>
<p>This book is suitable for classroom use as a general introduction to programming concepts.</p>
<p>More at http://tldp.org/LDP/abs/html/</p><p>Address of the bookmark: <a href="http://tldp.org/LDP/abs/html/" rel="nofollow">http://tldp.org/LDP/abs/html/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28290/bioinformatics-tools-and-software</guid>
	<pubDate>Tue, 05 Jul 2016 10:02:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28290/bioinformatics-tools-and-software</link>
	<title><![CDATA[Bioinformatics tools and software]]></title>
	<description><![CDATA[<p><a href="http://drive5.com/usearch">USEARCH &gt;</a><br><span>Extreme high-throughput sequence analysis. Orders of magnitude faster than BLAST.</span>&nbsp;<a href="http://drive5.com/muscle">MUSCLE &gt;</a><br><span>Multiple sequence alignment. Faster and more accurate than CLUSTALW.</span></p>
<p>&nbsp;<a href="http://drive5.com/uparse">UPARSE &gt;</a><br><span>OTU clustering for 16S and other marker genes. Highly accurate OTU sequences and improved diversity measures.</span>&nbsp;<a href="http://drive5.com/uchime">UCHIME &gt;</a><br><span>Chimeric sequence detection.</span>&nbsp;<a href="http://drive5.com/piler">PILER &gt;</a><br><span>De novo genome repeat finder.</span>&nbsp;<a href="http://drive5.com/pilercr">PILER-CR &gt;</a><br><span>Detection of CRISPR repeats in bacterial genomes.</span>&nbsp;<a href="http://drive5.com/qscore">QSCORE &gt;</a><br><span>Compare two multiple alignments for benchmarking.</span>&nbsp;<a href="http://drive5.com/pals">PALS &gt;</a><br><span>Whole-genome alignment.</span>&nbsp;<a href="http://drive5.com/muscle/prefab.htm">PREFAB &gt;</a><br><span>Protein Reference Alignment Database.</span>&nbsp;<a href="http://drive5.com/bench">MSA benchmark collection &gt;</a><br><span>Selected multiple alignment benchmarks in a standardized FASTA format.</span></p><p>Address of the bookmark: <a href="http://drive5.com/software.html" rel="nofollow">http://drive5.com/software.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28554/megan6</guid>
	<pubDate>Mon, 25 Jul 2016 05:45:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28554/megan6</link>
	<title><![CDATA[MEGAN6]]></title>
	<description><![CDATA[<p>Microbiome analysis using a single application</p>
<p>MEGAN6 is a comprehensive toolbox for interactively analyzing microbiome data. All the interactive tools you need in one application.</p>
<ul>
<li>Taxonomic analysis using the NCBI taxonomy or a customized taxonomy such as SILVA</li>
<li>Functional analysis using InterPro2GO, SEED, eggNOG or KEGG</li>
<li>Bar charts, word clouds, Voronoi tree maps and many other charts</li>
<li>PCoA, clustering and networks</li>
<li>Supports metadata</li>
<li>MEGAN parses many different types of input</li>
</ul>
<p>Why use MEGAN6?</p>
<div>&nbsp;The software is:</div>
<div><ol>
<li>Easy to use. MEGAN6 is a single application and all features are available through menus, toolbars and graphics. No scripting skills required.</li>
<li>Powerful. MEGAN6 allows you to work with hundreds of samples containing&nbsp;hundreds of millions of sequencing reads. Blast-like analysis can be performed using DIAMOND.</li>
<li>Comprehensive. MEGAN6 offers a large range of analysis tools, and is under active development.</li>
</ol></div><p>Address of the bookmark: <a href="https://ab.inf.uni-tuebingen.de/software/megan6" rel="nofollow">https://ab.inf.uni-tuebingen.de/software/megan6</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27070/venn-diagrams-on-r-studio</guid>
	<pubDate>Mon, 25 Apr 2016 16:22:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27070/venn-diagrams-on-r-studio</link>
	<title><![CDATA[Venn Diagrams on R Studio]]></title>
	<description><![CDATA[<h3>First step: Install &amp; load &ldquo;VennDiagram&rdquo; package.</h3>
<pre><code><span># install.packages('VennDiagram')</span>
<span>library</span><span>(</span><span>VennDiagram</span><span>)</span>
</code></pre>
<h3>Second step: Load data</h3>
<p>Add filepath if &ldquo;catdoge.csv&rdquo; is not in working-directory.</p>
<pre><code><span>d</span> <span>&lt;-</span> <span>read.csv</span><span>(</span><span>"catdoge.csv"</span><span>)</span></code><br><br></pre><p>Address of the bookmark: <a href="http://rstudio-pubs-static.s3.amazonaws.com/13301_6641d73cfac741a59c0a851feb99e98b.html" rel="nofollow">http://rstudio-pubs-static.s3.amazonaws.com/13301_6641d73cfac741a59c0a851feb99e98b.html</a></p>]]></description>
	<dc:creator>Jitendra Prajapati</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/29652/bioistats-ppt</guid>
	<pubDate>Tue, 08 Nov 2016 07:09:01 -0600</pubDate>
	<link>https://bioinformaticsonline.com/file/view/29652/bioistats-ppt</link>
	<title><![CDATA[Bioistats PPT]]></title>
	<description><![CDATA[<p>Basics concepts of&nbsp;Probability: The Study of Randomness</p><p>Biostatistics is the application of statistics to a wide range of topics in biology. The science of biostatistics encompasses the design of biological experiments, especially in medicine, pharmacy, agriculture and fishery; the collection, summarization, and analysis of data from those experiments; and the interpretation of, and inference from, the results. A major branch of this is medical biostatistics, which is exclusively concerned with medicine and health.</p>]]></description>
	<dc:creator>Jit</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/29652" length="1663809" type="application/pdf" />
</item>

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