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<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/30242?offset=280</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37796/grsr-a-tool-for-deriving-genome-rearrangement-scenarios-from-multiple-unichromosomal-genome-sequences</guid>
	<pubDate>Fri, 28 Sep 2018 09:35:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37796/grsr-a-tool-for-deriving-genome-rearrangement-scenarios-from-multiple-unichromosomal-genome-sequences</link>
	<title><![CDATA[GRSR: a tool for deriving genome rearrangement scenarios from multiple unichromosomal genome sequences]]></title>
	<description><![CDATA[<p>GRSR is a Tool for Deriving Genome Rearrangement Scenarios for Multiple Uni-chromosomal Genomes. This tool will do the following steps:</p>
<ul>
<li>Step 1. Run mugsy to get multiple sequence alignment results.</li>
<li>Step 2 &amp; 3. Extraction of the Coordinates of Core Blocks, Construction of Synteny Blocks and Generating Signed Permutations.</li>
<li>Step 4. Generate pairwise genome rearrangement scenarios and find repeats at the breakpoints of each rearrangement events.</li>
<li></li>
<li></li>
</ul>
<p>https://github.com/DanwangJessica/GRSR</p><p>Address of the bookmark: <a href="https://github.com/DanwangJessica/GRSR" rel="nofollow">https://github.com/DanwangJessica/GRSR</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/8943/roth-lab</guid>
  <pubDate>Tue, 11 Mar 2014 17:43:45 -0500</pubDate>
  <link></link>
  <title><![CDATA[Roth Lab]]></title>
  <description><![CDATA[
<p>The Roth Lab seeks insight into biological systems through genome- and proteome-scale experimentation and analysis.</p>

<p>Current computational interests:</p>

<p>Systematic analysis of genetic epistasis to identify redundant or compensatory systems and to reveal order of action in genetic pathways.<br />Using knockout, knockdown, or overexpression, or other perturbation experiments in combinations of genes in S. cerevisiae, C. elegans or mouse.<br />Using genome-scale genotyping of natural polymorphisms in S. cerevisiae and human populations.<br />Alternative splicing and its relationship to protein interaction networks.<br />Integrating large-scale studies including phenotype, genetic epistasis, protein-protein and transcription-regulatory interactions and sequence patterns to quantitatively assign function to genes and guide experimentation.</p>

<p>More at http://llama.mshri.on.ca/index.html</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39624/cogent-a-tool-for-reconstructing-the-coding-genome-using-high-quality-full-length-transcriptome-sequences</guid>
	<pubDate>Tue, 18 Jun 2019 05:33:04 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39624/cogent-a-tool-for-reconstructing-the-coding-genome-using-high-quality-full-length-transcriptome-sequences</link>
	<title><![CDATA[Cogent: a tool for reconstructing the coding genome using high-quality full-length transcriptome sequences.]]></title>
	<description><![CDATA[<div id="yui_3_14_1_1_1560853173251_3865">Cogent is a tool that identifies gene&nbsp;families and reconstructs the coding genome using high-quality transcriptome data without a reference genome, and can be used to check&nbsp;assemblies&nbsp;for the presence of&nbsp;these known coding sequences.</div>
<div>&nbsp;</div>
<div>
<p>Cogent is a tool for reconstructing the coding genome using high-quality full-length transcriptome sequences. It is designed to be used on&nbsp;<a href="https://github.com/PacificBiosciences/cDNA_primer/wiki">Iso-Seq data</a>&nbsp;and in cases where there is no reference genome or the ref genome is highly incomplete.</p>
<p>See a&nbsp;<a href="https://www.dropbox.com/s/mn6hwhguh0pqceu/20160106_Cogent_developers_conference_slides_Cuttlefish.pdf?dl=0">recent presentation</a>&nbsp;on Cogent being applied to the Cuttlefish Iso-Seq data.</p>
<p><a href="https://www.dropbox.com/s/kz0gi7qg0w82k9a/20161026_Cogent_manuscript_forGitHub.pdf?dl=0">Cogent preliminary draft paper (updated 2016Dec version)</a>,&nbsp;<a href="https://www.dropbox.com/s/37412o8glvnfhf9/20161026_Cogent_ManuscriptPlusSupplement_forGitHub.pdf?dl=0">Supplementary</a></p>
<p>Please see&nbsp;<a href="https://github.com/Magdoll/Cogent/wiki">wiki</a>&nbsp;for details on usage.</p>
</div><p>Address of the bookmark: <a href="https://github.com/Magdoll/Cogent" rel="nofollow">https://github.com/Magdoll/Cogent</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/10741/managing-and-analyzing-next-generation-sequence-data</guid>
	<pubDate>Sat, 10 May 2014 06:28:06 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/10741/managing-and-analyzing-next-generation-sequence-data</link>
	<title><![CDATA[Managing and Analyzing Next-Generation Sequence Data]]></title>
	<description><![CDATA[<p>Centralized Bioinformatics Core Facilities provide shared resources for the computational and IT requirements of the investigators in their department or institution. As such, they must be able to effectively react to new types of experimental technology. Recently faced with an unprecedented flood of data generated by the next generation of DNA sequencers, these groups found it necessary to respond quickly and efficiently to the informatics and infrastructure demands. Centralized Facilities newly facing this challenge need to anticipate time and design considerations of necessary components, including infrastructure upgrades, staffing, and tools for data analyses and management ...</p>
<p>More at http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1000369</p><p>Address of the bookmark: <a href="http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1000369" rel="nofollow">http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1000369</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43711/vcf-compare</guid>
	<pubDate>Wed, 19 Jan 2022 10:30:14 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43711/vcf-compare</link>
	<title><![CDATA[VCF Compare !]]></title>
	<description><![CDATA[<h2><span>compare two&nbsp;<strong>BWA</strong>&nbsp;mapping methods with the online hg18-mapped data</span></h2>
<p>We first operate a rapid inspection of the different BAM files using&nbsp;<strong>samtools flagstat</strong>. Illumina provided chr21 read mapping obtained with their&nbsp;<strong>GA IIx</strong>&nbsp;deep sequencing platform &lt;<a href="ftp://webdata:webdata@ussd-ftp.illumina.com/Data/SequencingRuns/NA18507_GAIIx_100_chr21.bam" target="_blank">ftp://webdata:webdata@ussd-ftp.illumina.com/Data/SequencingRuns/NA18507_GAIIx_100_chr21.bam</a>&gt;, aligned to the b36/hg18 reference genome)</p><p>Address of the bookmark: <a href="https://wiki.bits.vib.be/index.php/NGS_Exercise.6#compare_aln_.26_mem_results_with_vcf-compare" rel="nofollow">https://wiki.bits.vib.be/index.php/NGS_Exercise.6#compare_aln_.26_mem_results_with_vcf-compare</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/12206/bioinformatics-algorithms-tutorials</guid>
	<pubDate>Tue, 24 Jun 2014 00:10:45 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/12206/bioinformatics-algorithms-tutorials</link>
	<title><![CDATA[Bioinformatics algorithms tutorials]]></title>
	<description><![CDATA[<p>Useful bioinformatics tutorial, such as</p>
<p>De Bruijn Graphs for NGS Assembly<br>Algorithms for PacBio Reads<br>Software and Hardware Concepts for Bioinformatics<br>Finding us in Homolog.us (Search Algorithms)<br>NGS Genome and RNAseq Assembly - a Hands on Primer<br>Introduction to PERL, Python, R and C/C++ for Bioinformatics</p><p>Address of the bookmark: <a href="http://www.homolog.us/Tutorials/" rel="nofollow">http://www.homolog.us/Tutorials/</a></p>]]></description>
	<dc:creator>John Parker</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36012/gmol-an-interactive-tool-for-3d-genome-structure-visualization</guid>
	<pubDate>Wed, 21 Mar 2018 12:25:20 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36012/gmol-an-interactive-tool-for-3d-genome-structure-visualization</link>
	<title><![CDATA[GMOL: An Interactive Tool for 3D Genome Structure Visualization]]></title>
	<description><![CDATA[<p><span>GMOL was developed based upon our multi-scale approach that allows a user to scale between six separate levels within the genome. With GMOL, a user can choose any unit at any scale and scale it up or down to visualize its structure and retrieve corresponding genome sequences.</span></p><p>Address of the bookmark: <a href="https://www.nature.com/articles/srep20802" rel="nofollow">https://www.nature.com/articles/srep20802</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/bookmarks/view/17924/software-developed-in-pevsner-lab</guid>
	<pubDate>Mon, 06 Oct 2014 12:41:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/17924/software-developed-in-pevsner-lab</link>
	<title><![CDATA[Software developed in pevsner lab]]></title>
	<description><![CDATA[<div>
<div id="block-system-main">
<div>
<div id="node-7">
<div>
<div>
<div>
<div>
<p><a href="http://pevsnerlab.kennedykrieger.org/dragon.htm">DRAGON</a>: Database Referencing of Array Genes Online</p>
<p><a href="http://pevsnerlab.kennedykrieger.org/php/node/96">SNOMAD</a>: Standardization and Normalization of Microarray Data</p>
<p><a href="http://pevsnerlab.kennedykrieger.org/php/node/70">SNPduo</a>: SNP Analysis Between Two Individuals</p>
<p><a href="http://pevsnerlab.kennedykrieger.org/php/node/71">SNPtrio</a>: Analyzing and Visualizing and Inheritance Patterns in Trios</p>
<p><a href="http://pevsnerlab.kennedykrieger.org/php/node/64">SNPscan</a>: Data Analysis and Visualization of SNP Data</p>
<p><a href="http://pevsnerlab.kennedykrieger.org/php/node/64">pediSNP</a>: Analyze SNP Data From a Pedigree of Two Generations</p>
<p><a href="http://pevsnerlab.kennedykrieger.org/php/node/73">kcoeff</a>: Calculate Cotterman Coefficients of SNP Genotype Data</p>
<p><a href="http://pevsnerlab.kennedykrieger.org/php/node/113">triPOD:</a> Detects chromosomal abnormalities in parent-child trio-based microarray data</p>
</div>
</div>
</div>
</div>
</div>
</div>
</div>
</div><p>Address of the bookmark: <a href="http://pevsnerlab.kennedykrieger.org/php/?q=software" rel="nofollow">http://pevsnerlab.kennedykrieger.org/php/?q=software</a></p>]]></description>
	<dc:creator>Robert M Willioms</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/35395/comprehensive-list-of-visualization-tools-for-biological-pathways</guid>
	<pubDate>Tue, 30 Jan 2018 06:01:31 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/35395/comprehensive-list-of-visualization-tools-for-biological-pathways</link>
	<title><![CDATA[Comprehensive list of visualization tools for biological pathways]]></title>
	<description><![CDATA[<p>The study of biological pathways is a key to understand the different processes inside a cell: proteins exert their function not in isolation but in a tightly controlled network of interactions and reactions. Activation of a pathway typically leads to a change of state in the cell. Pathways come in different flavors, depending on their functions in the cell &ndash; the three main types are metabolic pathways, gene regulatory pathways, and signaling pathways. These biological pathways and networks are not only an appropriate approach to visualize molecular reactions. They have also become one leading method in -omics data analysis and visualization.</p><p><img src="https://photos-1.dropbox.com/t/2/AABemz29qAuSTqSzr5mEsQE7JIMxZlU1CBy0E5n0yUVYbA/12/85115969/png/32x32/1/_/1/2/pathway.png/EOfXoUIYrJ8CIAcoBw/01qsT2eykyPvSH-rNpy3cqioDzZPc4i-xULG3BEZvCk?preserve_transparency=1&amp;size=1280x960&amp;size_mode=3" width="800" height="533" alt="image" style="border: 0px;"></p><p>Following are the comprehensive list of visualization tools for biological pathways:</p><p>BiNA</p><p>Drawings of metabolic networks supporting hiding of cofactors and drawing of chemical structures</p><p>http://bina.unipax.info/</p><p>BioTapestry</p><p>Interactive tool for building, visualizing and sharing gene regulatory network models over the web</p><p>http://www.biotapestry.org/</p><p>Caleydo</p><p>Visual analysis framework targeted at biomolecular data. Visualization of interdependencies between multiple datasets</p><p>http://www.caleydo.org/</p><p>CellDesigner</p><p>A modeling tool for biochemical networks</p><p>http://www.celldesigner.org/</p><p>Edinburgh Pathway Editor</p><p>Edit and draw pathway diagrams</p><p>http://epe.sourceforge.net/SourceForge/EPE.html</p><p>GenMAPP</p><p>Visualization of gene expression and other genomic data on maps representing biological pathways and groupings of genes</p><p>http://www.genmapp.org/</p><p>Ingenuity IPA</p><p>Data integration platform and manually annotated pathways</p><p>http://tinyurl.com/IngenuityPath</p><p>JDesigner</p><p>Graphical modeling environment for biochemical reaction networks</p><p>http://jdesigner.sourceforge.net/Site/JDesigner.html</p><p>KaPPA View</p><p>Plant pathways</p><p>http://kpv.kazusa.or.jp/</p><p>KEGG Atlas</p><p>Interactive Kyoto Encyclopedia of Genes and Genomes pathways</p><p>http://www.genome.jp/kegg/</p><p>Omix&nbsp;</p><p>Visualizing multi-omics data in metabolic networks</p><p>https://www.omix-visualization.com</p><p>PathVisio&nbsp;</p><p>Biological pathway analysis software that allows drawing, editing and analysis of biological pathways</p><p>http://www.pathvisio.org/</p><p>VitaPad&nbsp;</p><p>Application to visualize biological pathways and map experimental data to them</p><p>http://tinyurl.com/vitapad/</p><p>Web tools for pathways</p><p>ArrayXPath&nbsp;</p><p>Mapping and visualizing microarray gene-expression data and integrated biological pathway resources using SVG</p><p>http://tinyurl.com/ArrayXPath/</p><p>GEPAT&nbsp;</p><p>Integrated analysis of transcriptome data in genomic, proteomic and metabolic contexts</p><p>http://gepat.sourceforge.net/</p><p>iPath&nbsp;</p><p>Web-based tool for the visualization, analysis and customization of pathway maps</p><p>http://pathways.embl.de/</p><p>Kegg-Based Viewer&nbsp;</p><p>KEGG-based pathway visualization tool for complex high-throughput data</p><p>http://www.g-language.org/data/marray/</p><p>MapMan&nbsp;</p><p>User-driven tool that displays large datasets onto diagrams of metabolic pathways or other processes</p><p>http://mapman.gabipd.org/web/guest/mapman</p><p>MetPA&nbsp;</p><p>Analysis and visualization of metabolomic data within the biological context of metabolic pathways</p><p>http://metpa.metabolomics.ca</p><p>Omics Viewer&nbsp;</p><p>Data mapping on BioCyc pathways (collection of 5500 pathway/genome databases)</p><p>http://www.biocyc.org/</p><p>Pathway Explorer</p><p>Interactive Java drawing tool for the construction of biological pathway diagrams in a visual way and the annotation of the components and interactions between them</p><p>http://genome.tugraz.at/pathwayexplorer/pathwayexplorer_description.shtml</p><p>Pathway projector&nbsp;</p><p>Zoomable pathway browser using KEGG atlas and Google Maps API</p><p>http://www.g-language.org/PathwayProjector/</p><p>PATIKA&nbsp;</p><p>Integrated environment composed of a central database and a visual editor, built around an extensive ontology and an integration framework</p><p>http://www.cs.bilkent.edu.tr/~patikaweb/</p><p>Reactome SkyPainter&nbsp;</p><p>Visualization of over-represented pathways and reactions from gene lists</p><p>http://www.reactome.org/skypainter-2</p><p>WikiPathways</p><p>Wiki-based, open, public platform dedicated to the curation of biological pathways by and for the scientific community</p><p>http://www.wikipathways.org/</p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>

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