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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/28937?offset=300</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28141/csbb-v10</guid>
	<pubDate>Wed, 29 Jun 2016 07:33:05 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28141/csbb-v10</link>
	<title><![CDATA[CSBB-v1.0]]></title>
	<description><![CDATA[<p>CSBB is a command line based bioinformatics suite to analyze biological data acquired through varied avenues of biological experiments. CSBB is implemented in Perl, while it also leverages the use of R and python in background for specific modules. Major focus of CSBB is to allow users from biology and bioinformatics community, to get benefited by performing down-stream analysis tasks while eliminating the need to write programming code. CSBB is currently available on Linux, UNIX, MAC OS and Windows platforms.</p>
<p>Currently CSBB provides 13 modules focused on analytical tasks like performing upper-quantile normalization on expression data or convert genome wide gene expression to z-scores when comparing expression data from different platforms.</p>
<p>More at&nbsp;https://github.com/skygenomics/CSBB-v1.0</p><p>Address of the bookmark: <a href="https://github.com/skygenomics/CSBB-v1.0" rel="nofollow">https://github.com/skygenomics/CSBB-v1.0</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29272/decipher</guid>
	<pubDate>Fri, 30 Sep 2016 09:33:12 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29272/decipher</link>
	<title><![CDATA[DECIPHER]]></title>
	<description><![CDATA[<p>DECIPHER is a software toolset that can be used to maintain, analyze, and decipher large amounts of DNA sequence data. To install DECIPHER, see the <a href="http://DECIPHER.cee.wisc.edu/Download.html">Downloads</a> page.<br><br> To begin using DECIPHER read the "Getting Started DECIPHERing" tutorial. Refer to the PDF documents below for instructions on how to use DECIPHER for various tasks.</p><p>Address of the bookmark: <a href="http://decipher.cee.wisc.edu/Documentation.html" rel="nofollow">http://decipher.cee.wisc.edu/Documentation.html</a></p>]]></description>
	<dc:creator>Anjana</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31278/metapred2cs</guid>
	<pubDate>Fri, 03 Mar 2017 05:15:07 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31278/metapred2cs</link>
	<title><![CDATA[MetaPred2CS]]></title>
	<description><![CDATA[<p style="text-align: justify;"><strong>MetaPred2CS Web server&nbsp;</strong>is a meta-predictor based on&nbsp;<a href="http://www.ncbi.nlm.nih.gov/pubmed/17160063">Support Vector Machine (SVM)</a>&nbsp;that combines 6 individual sequence based protein-protein interaction prediction methods to predict&nbsp;<strong>prokaryotic two-component system&nbsp;</strong>protein-protein interactions (PPIs). The methods implemented in MetaPred2CS are 2 co-evolutionary methods:&nbsp;<a href="http://www.ncbi.nlm.nih.gov/pubmed/11933068">in-silico two hybrid (i2h)</a>&nbsp;and&nbsp;<a href="http://www.ncbi.nlm.nih.gov/pubmed/11707606">mirror tree (MT)</a>&nbsp;methods and 4 genomics context based methods:&nbsp;<a href="http://www.ncbi.nlm.nih.gov/pubmed/15947018">phylogenetic profiling (PP)</a>,&nbsp;<a href="http://www.ncbi.nlm.nih.gov/pubmed/10573422">gene fusion (GF)</a>,&nbsp;<a href="http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.0030043">gene neighbourhood (GN)</a>&nbsp;and and&nbsp;<a href="http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.0030043">gene operon methods (GO)</a>.</p>
<p>&nbsp;http://metapred2cs.ibers.aber.ac.uk/</p><p>Address of the bookmark: <a href="https://github.com/martinjvickers/MetaPred2CS" rel="nofollow">https://github.com/martinjvickers/MetaPred2CS</a></p>]]></description>
	<dc:creator>Manisha Mishra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30557/speedseq</guid>
	<pubDate>Fri, 20 Jan 2017 06:05:43 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30557/speedseq</link>
	<title><![CDATA[SpeedSeq]]></title>
	<description><![CDATA[<p>A flexible framework for rapid genome analysis and interpretation</p>
<p>C Chiang, R M Layer, G G Faust, M R Lindberg, D B Rose, E P Garrison, G T Marth, A R Quinlan, and I M Hall. SpeedSeq: ultra-fast personal genome analysis and interpretation. Nat Meth (2015). doi:10.1038/nmeth.3505.</p>
<p><a href="http://www.nature.com/nmeth/journal/vaop/ncurrent/full/nmeth.3505.html">http://www.nature.com/nmeth/journal/vaop/ncurrent/full/nmeth.3505.html</a></p><p>Address of the bookmark: <a href="https://github.com/hall-lab/speedseq" rel="nofollow">https://github.com/hall-lab/speedseq</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29658/bookmarks-biostatistics-materials-and-books</guid>
	<pubDate>Tue, 08 Nov 2016 07:42:42 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29658/bookmarks-biostatistics-materials-and-books</link>
	<title><![CDATA[Bookmarks Biostatistics materials and books]]></title>
	<description><![CDATA[<p>Biostatistics did not spring fully formed from the brow of R. A. Fisher, but evolved over many years. This process is continuing, although it may not be obvious from the outside. It has been ten years since the first edition of this book appeared (and rather longer since it was begun). Over this time, new areas of biostatistics have been developed and emphases and interpretations have changed</p>
<p>Please bookmarks your favourate biostatistics&nbsp;books in commend sectons ...</p><p>Address of the bookmark: <a href="http://www.cos.ufrj.br/~bioestatistica/livros/Introduction%20to%20Biostatistics.pdf" rel="nofollow">http://www.cos.ufrj.br/~bioestatistica/livros/Introduction%20to%20Biostatistics.pdf</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30901/ideoplot</guid>
	<pubDate>Mon, 13 Feb 2017 09:47:32 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30901/ideoplot</link>
	<title><![CDATA[Ideoplot]]></title>
	<description><![CDATA[<p>Simple ideogram plotting and annotation in R.</p>
<p>Basic usage:</p>
<p>Rscript Ideoplot.R --heatmap hm.bed --annotate annotations.bed --out ideogram.pdf<br> -or-<br> Rscript Ideoplot.R --annotate annotations.bed</p>
<pre>Options
  --ideobed, i      A bed file of reference contig lengths/chromosome names
  --heatmap, -h     Fill chromosomes with normalized heatmap
                   (described below)
  --annotate, -a    Add character annotations.
  --out, -o         PDF output name.
  --stripes, -s     Specify a file containing the layout of the
                    annotations (description below)
  --bars, -b        Add track annotations
  --reference, -f   Either hg19, or hg38
  --topdown, r      Flag, when set, flips the orientation (P arms
                    drawn on top).
</pre><p>Address of the bookmark: <a href="https://github.com/mchaisso/Ideoplot" rel="nofollow">https://github.com/mchaisso/Ideoplot</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31526/sequenceserver</guid>
	<pubDate>Fri, 10 Mar 2017 08:51:55 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31526/sequenceserver</link>
	<title><![CDATA[sequenceserver]]></title>
	<description><![CDATA[<p><span>SequenceServer lets you rapidly set up a BLAST+ server with an intuitive user interface for use locally or over the web.</span></p>
<p><span><span>More at&nbsp;</span><a href="http://sequenceserver.com/">http://sequenceserver.com</a><span>.</span></span></p><p>Address of the bookmark: <a href="https://github.com/wurmlab/sequenceserver" rel="nofollow">https://github.com/wurmlab/sequenceserver</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/35125/eugene-v-koonin-lab</guid>
  <pubDate>Tue, 09 Jan 2018 05:01:15 -0600</pubDate>
  <link></link>
  <title><![CDATA[Eugene V. Koonin Lab]]></title>
  <description><![CDATA[
<p>Interested in understanding the evolution of life. To obtain glimpses of such understanding, we employ existing and new methods of computational biology to perform research in several major areas.</p>

<p>https://www.ncbi.nlm.nih.gov/research/groups/koonin/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/37610/applied-statistics-for-bioinformatics-using-r</guid>
	<pubDate>Thu, 30 Aug 2018 03:45:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/file/view/37610/applied-statistics-for-bioinformatics-using-r</link>
	<title><![CDATA[Applied Statistics for Bioinformatics using R]]></title>
	<description><![CDATA[<p>The purpose of this book is to give an introduction into statistics in order to solve some problems of bioinformatics. Statistics provides procedures to explore and visualize data as well as to test biological hypotheses. The book intends to be introductory in explaining and programming elementary statistical concepts, thereby bridging the gap between high school levels and the specialized statistical literature</p>]]></description>
	<dc:creator>Neel</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/37610" length="1368378" type="application/pdf" />
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/40248/industrial-training-in-computer-aided-drug-designing-cadd</guid>
	<pubDate>Wed, 13 Nov 2019 05:00:44 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/40248/industrial-training-in-computer-aided-drug-designing-cadd</link>
	<title><![CDATA[Industrial Training in Computer Aided Drug Designing (CADD)]]></title>
	<description><![CDATA[<p>Learn More about&nbsp; Computer Aided Drug Designing (CADD)!!!</p><p>#rasalsi #rasa In our Industrial program you will get Knowledge on RNA Seq, CHIP Seq,</p><h2 style="text-align: center;"><strong>Batch Starts From 18<sup>th</sup> November 2019</strong></h2><p>#hurryup #registernow #enquirenow The primary goal of the industrial training program is to provide students with necessary skills making with employable. RASA LSI trains students with the enhanced skills required for them to excel in jobs in biotechnology, pharmaceuticals, BioIT and related industry sectors. At Rasa you will&nbsp; learn from industry leaders&nbsp;how to apply these skills in life science &amp; have a command over software developing process &nbsp;by using various methodologies. For Registration visit us on: https://www.rasalsi.com/index.php/front-page/industrial-training/</p>]]></description>
	<dc:creator>RASA Life Sciences</dc:creator>
</item>

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