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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/31300?offset=110</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30168/gene-synteny-database</guid>
	<pubDate>Fri, 16 Dec 2016 11:09:39 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30168/gene-synteny-database</link>
	<title><![CDATA[Gene Synteny Database]]></title>
	<description><![CDATA[<p>Comparative genomics remains a pivotal strategy to study the evolution of gene organization, and this primacy is reinforced by the growing number of full genome sequences available in public repositories. Despite this growth, bioinformatic tools available to visualize and compare genomes and to infer evolutionary events remain restricted to two or three genomes at a time, thus limiting the breadth and the nature of the question that can be investigated. Here we present Genomicus, a new synteny browser that can represent and compare unlimited numbers of genomes in a broad phylogenetic view. In addition, Genomicus includes reconstructed ancestral gene organization, thus greatly facilitating the interpretation of the data.</p>
<p><strong>Availability:</strong>&nbsp;Genomicus is freely available for online use at&nbsp;<a href="http://www.dyogen.ens.fr/genomicus" target="pmc_ext">http://www.dyogen.ens.fr/genomicus</a>&nbsp;while data can be downloaded at&nbsp;<a href="ftp://ftp.biologie.ens.fr/pub/dyogen/genomicus" target="pmc_ext">ftp://ftp.biologie.ens.fr/pub/dyogen/genomicus</a></p>
<p><strong>Contact:</strong>&nbsp;<a href="mailto:dev@null">rf.sne.eigoloib@crh</a></p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2853686/" rel="nofollow">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2853686/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31064/cgaln</guid>
	<pubDate>Wed, 22 Feb 2017 05:14:15 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31064/cgaln</link>
	<title><![CDATA[Cgaln]]></title>
	<description><![CDATA[<p>Cgaln (Coarse grained alignment) is a program designed to align a pair of whole genomic sequences of not only bacteria but also entire chromosomes of vertebrates on a nominal desktop computer. Cgaln performs an alignment job in two steps, at the block level and then at the nucleotide level. The former "coarse-grained" alignment can explore genomic rearrangements and reduce the regions to be analyzed in the next step. The latter is devoted to detailed alignment within the limited regions found in the first stage. The output of Cgaln is 'glocal' in the sense that rearrangements are taken into consideration while each alignable region is extended as long as possible. Thus, Cgaln is not only fast and memory-efficient, but also can filter noisy outputs without missing the most important homologous segment pairs.</p>
<p>http://www.iam.u-tokyo.ac.jp/chromosomeinformatics/rnakato/cgaln/</p><p>Address of the bookmark: <a href="http://www.iam.u-tokyo.ac.jp/chromosomeinformatics/rnakato/cgaln/" rel="nofollow">http://www.iam.u-tokyo.ac.jp/chromosomeinformatics/rnakato/cgaln/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30355/meme-suite</guid>
	<pubDate>Fri, 23 Dec 2016 08:49:55 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30355/meme-suite</link>
	<title><![CDATA[MEME suite]]></title>
	<description><![CDATA[<p>Motif based sequence analysis suits&nbsp;</p>
<p>The MEME Suite allows the biologist to discover novel motifs in collections of unaligned nucleotide or protein sequences, and to perform a wide variety of other motif-based analyses.</p>
<p>The MEME Suite supports motif-based analysis of DNA, RNA and protein sequences. It provides motif discovery algorithms using both probabilistic (MEME) and discrete models (MEME), which have complementary strengths. It also allows discovery of motifs with arbitrary insertions and deletions (GLAM2). In addition to motif discovery, the MEME Suite provides tools for scanning sequences for matches to motifs (FIMO, MAST and GLAM2Scan), scanning for clusters of motifs (MCAST), comparing motifs to known motifs (Tomtom), finding preferred spacings between motifs (SpaMo), predicting the biological roles of motifs (GOMo), measuring the positional enrichment of sequences for known motifs (CentriMo), and analyzing ChIP-seq and other large datasets (MEME-ChIP).</p>
<p>The MEME Suite is comprised of a collection of tools that work together, as shown below. Not all the tools are available as webservices, so to get the full power of the MEME Suite you will need to&nbsp;<a href="http://meme-suite.org/doc/download.html">download</a>&nbsp;and&nbsp;<a href="http://meme-suite.org/doc/install.html">install</a>&nbsp;a local copy of the software. To see what has changed recently you can peruse the&nbsp;<a href="http://meme-suite.org/doc/release-notes.html">release notes</a>.</p>
<p>http://meme-suite.org/</p><p>Address of the bookmark: <a href="http://meme-suite.org/" rel="nofollow">http://meme-suite.org/</a></p>]]></description>
	<dc:creator>Bulbul</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30833/dnasp-v5-a-software-for-comprehensive-analysis-of-dna-polymorphism-data</guid>
	<pubDate>Mon, 06 Feb 2017 04:45:37 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30833/dnasp-v5-a-software-for-comprehensive-analysis-of-dna-polymorphism-data</link>
	<title><![CDATA[DnaSP v5: a software for comprehensive analysis of DNA polymorphism data]]></title>
	<description><![CDATA[<p><span>DnaSP is a software package for a comprehensive analysis of DNA polymorphism data. Version 5 implements a number of new features and analytical methods allowing extensive DNA polymorphism analyses on large datasets. Among other features, the newly implemented methods allow for: (i) analyses on multiple data files; (ii) haplotype phasing; (iii) analyses on insertion/deletion polymorphism data; (iv) visualizing sliding window results integrated with available genome annotations in the UCSC browser.</span></p><p>Address of the bookmark: <a href="http://www.ub.edu/dnasp/" rel="nofollow">http://www.ub.edu/dnasp/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31018/j-circos</guid>
	<pubDate>Fri, 17 Feb 2017 09:06:54 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31018/j-circos</link>
	<title><![CDATA[J-Circos]]></title>
	<description><![CDATA[<p>Circos plot tool (J-Circos) that is an interactive visualization tool that can plot Circos figures, as well as being able to dynamically add data to the figure, and providing information for specific data points using mouse hover display and zoom in/out functions. J-Circos uses the Java computer language to enable it to be used on most operating systems (Windows, MacOS, Linux). Users can input data into J-Circos using flat data formats, as well as from the GUI. J-Circos will enable biologists to better study more complex chromosomal interactions and fusion transcripts that are otherwise difficult to visualize from next-generation sequencing data.</p><p>Address of the bookmark: <a href="http://www.australianprostatecentre.org/research/software/jcircos" rel="nofollow">http://www.australianprostatecentre.org/research/software/jcircos</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31209/dial</guid>
	<pubDate>Wed, 01 Mar 2017 08:42:28 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31209/dial</link>
	<title><![CDATA[DIAL]]></title>
	<description><![CDATA[<p>A computational pipeline for identifying single-base substitutions between two closely related genomes without the help of a reference genome. DIAL works even when the depth of coverage is insufficient for de novo assembly, and it can be extended to determine small insertions/deletions. Our main motivation is to use this tool to survey the genetic diversity of endangered species as the identified sequence differences can be used to design genotyping arrays to assist in the species' management.</p>
<p>http://www.bx.psu.edu/~ratan/</p><p>Address of the bookmark: <a href="http://www.bx.psu.edu/miller_lab/" rel="nofollow">http://www.bx.psu.edu/miller_lab/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32048/json</guid>
	<pubDate>Tue, 04 Apr 2017 08:02:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32048/json</link>
	<title><![CDATA[JSON]]></title>
	<description><![CDATA[<p><strong>JSON</strong>&nbsp;(JavaScript Object Notation) is a lightweight data-interchange format. It is easy for humans to read and write. It is easy for machines to parse and generate. It is based on a subset of the&nbsp;<a href="http://javascript.crockford.com/">JavaScript Programming Language</a>,&nbsp;<a href="http://www.ecma-international.org/publications/files/ecma-st/ECMA-262.pdf">Standard ECMA-262 3rd Edition - December 1999</a>. JSON is a text format that is completely language independent but uses conventions that are familiar to programmers of the C-family of languages, including C, C++, C#, Java, JavaScript, Perl, Python, and many others. These properties make JSON an ideal data-interchange language.</p>
<p>JSON is built on two structures:</p>
<ul>
<li>A collection of name/value pairs. In various languages, this is realized as an&nbsp;<em>object</em>, record, struct, dictionary, hash table, keyed list, or associative array.</li>
<li>An ordered list of values. In most languages, this is realized as an&nbsp;<em>array</em>, vector, list, or sequence.</li>
</ul>
<p>These are universal data structures. Virtually all modern programming languages support them in one form or another. It makes sense that a data format that is interchangeable with programming languages also be based on these structures.</p><p>Address of the bookmark: <a href="http://json.org/" rel="nofollow">http://json.org/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32465/tetra-nucleotide-analysis</guid>
	<pubDate>Thu, 04 May 2017 05:07:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32465/tetra-nucleotide-analysis</link>
	<title><![CDATA[Tetra-Nucleotide Analysis]]></title>
	<description><![CDATA[<p>A tetra-nucleotide is a fragment of DNA sequence with 4 bases (e.g. AGTC or TTGG). Pride&nbsp;<em>et al.</em>&nbsp;(2003) showed that the frequency of tetra-nucleotides in bacterial genomes contain useful, albeit weak, phylogenetic signals. Even though tetra-nucleotide analysis (TNA) utilizes the information of whole genome, it is evident that it cannot replace other alignment-based phylogenetic methods such as&nbsp;<a href="https://chunlab.wordpress.com/orthoani/">OrthoANI</a>&nbsp;or&nbsp;16S rRNA phylogeny. However, TNA can be useful for&nbsp;phylogenetic characterization when whole genome or 16S rRNA gene information is not available. For example, a partial genomic fragment obtained from a metagenome can be identified by TNA (Teeling&nbsp;<em>et al.</em>, 2004). TNA is also fast enough that it can be&nbsp;used&nbsp;as a search engine against a large genome database.</p><p>Address of the bookmark: <a href="https://chunlab.wordpress.com/tetra-nucleotide-analysis/" rel="nofollow">https://chunlab.wordpress.com/tetra-nucleotide-analysis/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37257/asar-advanced-metagenomic-sequence-analysis-in-r</guid>
	<pubDate>Mon, 09 Jul 2018 05:20:50 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37257/asar-advanced-metagenomic-sequence-analysis-in-r</link>
	<title><![CDATA[ASAR: Advanced metagenomic Sequence Analysis in R]]></title>
	<description><![CDATA[<p><span>An interactive data analysis tool for selection, aggregation and visualization of metagenomic data is presented. Functional analysis with a SEED hierarchy and pathway diagram based on KEGG orthology based upon MG-RAST annotation results is available.</span></p>
<p><span><span>To read the manual, please click the link&nbsp;</span><a href="https://askarbek-orakov.github.io/ASAR/">https://askarbek-orakov.github.io/ASAR/</a></span></p><p>Address of the bookmark: <a href="https://github.com/Askarbek-orakov/ASAR" rel="nofollow">https://github.com/Askarbek-orakov/ASAR</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<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>
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