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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/28303?offset=1220</link>
	<atom:link href="https://bioinformaticsonline.com/related/28303?offset=1220" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/8987/the-dna-of-a-successful-bioinformatician-decoded</guid>
	<pubDate>Wed, 12 Mar 2014 13:41:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/8987/the-dna-of-a-successful-bioinformatician-decoded</link>
	<title><![CDATA[The DNA of a Successful Bioinformatician decoded !!!]]></title>
	<description><![CDATA[<p>Many blogs exist about successful bioinformatician, but this blog so far now is my personal view on characteristics of successful bioinformatician or computational biologist. &nbsp;Hmm &hellip; of course these views are subjective to my own personal experiences and therefore I don't claim that the view listed here is complete. As a human, I don&rsquo;t take them too serious. The success must not be the only target of your work. The target is to work on your own virtues; some of those virtues are the topic of this blog.</p><p><img src="http://bioinformaticsonline.com/mod/photo/genome_decode.png" alt="image" width="509" height="458" style="border: 0px; border: 0px;"><br /> <br /> <strong>1. Update new things continuously<br /></strong>As per my personal experience, it&rsquo;s not always easy to work as a bioinformatician! &nbsp;There are couple of reasons to say that; First computational part of biology make our life&rsquo;s a little harder compared to other professional categories. The fact - for instance - that the technology cycle in the bioinformatics world is very short, the actual knowledge becomes outdated in a few months or years. Therefore, we need to learn continuously - new things get important. Second, to stay on top of things we really need the strong will to be good at our job. That's probably the most important characteristic to bioinformatician. They are usually an excellent knowledge worker with great technical abilities, and have the will to be that over decades!<br /> <br /> <strong>2. Avoid the sentence </strong><strong>"I did not know what to do!"</strong><br /> In our computational biology lab, we generally face lots of technical problems. But as you know, it's impossible to know everything to do the computational biology jobs ( Yup.. because you need diverse and multidisciplinary knowledge to understand biological problems and resolve their respective solutions), therefore it's absolutely necessary that a bioinformatician finds its way through a new topic. How I typically do that is I use google and I talk to other experts in our laboratory or online biostar community to find out what they think. "I did not know what to do!" should not be an argument for us.<strong><br /><br /> <strong>3. To make oneself useful</strong></strong><br /> Several time it does happen, you finished our task earlier than expected; in such cases if you have some time left then: Take a coffee and play chess; reversi, etc. In my case I take a rest. Afterwards I think about what I could do that helps the team to achieve its targets, 'cause some of my team mates probably didn't finish! (at least if I didn't met them at coffee bar !!)</p><p><strong>4. Care for all</strong><br /> During my rigorous research duration; I attended several workshop organized by my University departments. I had a discussion with other research fellow, professors; I generally ask &hellip; what it really takes to make a team successful or to be a successful research leader. They always said: "Well, you need some caring people!" I think there is a lot truth in that statement. If we do not care about quality, timelines, good team culture, respectful communication (!!), clean code, if all this doesn&rsquo;t matter to us, then I believe the probability is higher that we fail in research and analysis. <br /> <br /> <strong>5. Be good with people</strong><br /> Because bioinformatician and computational biologist jobs typically involves to work in a (most wanted J cross-departmental!) team, therefore it's important that we're (more or less) good in dealing with other individuals. Everyone have their own strengths and weaknesses, just like us. It's important to treat all the research team mates with respect, regardless of their technical competence or contributions. Of course, sometimes people deserve a clear statement (!!!), but try to do these things one-on-one. Make sure nobody loses his face. Attend the meetings at the coffee bar; be good at table top soccer and go out once in a while to have a beer with your team. You know what I'm talking about.</p><p>At the end of a week I look back and I ask myself what I have produced. This could be paperwork, community days or (best!!) programming code. Always remember there is always a solution to a problem. Most of the times there are at least three solutions. So, don&rsquo;t just blame, suggest a solution.<br /> <br /> That's it. I am looking forward to your thoughts and comments!</p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33820/circular-visualization-in-r</guid>
	<pubDate>Wed, 05 Jul 2017 04:11:30 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33820/circular-visualization-in-r</link>
	<title><![CDATA[Circular Visualization in R]]></title>
	<description><![CDATA[<p>This is the documentation of the&nbsp;<a href="https://cran.r-project.org/package=circlize"><span>circlize</span></a>&nbsp;package. Examples in the book are generated under version 0.4.1.</p>
<p>If you use&nbsp;<span>circlize</span>&nbsp;in your publications, I would be appreciated if you can cite:</p>
<p>Gu, Z. (2014) circlize implements and enhances circular visualization in R. Bioinformatics. DOI:&nbsp;<a href="https://doi.org/10.1093/bioinformatics/btu393">10.1093/bioinformatics/btu393</a></p><p>Address of the bookmark: <a href="http://zuguang.de/circlize_book/book/" rel="nofollow">http://zuguang.de/circlize_book/book/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/9028/linux-for-bioinformatician</guid>
	<pubDate>Thu, 13 Mar 2014 16:59:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/9028/linux-for-bioinformatician</link>
	<title><![CDATA[Linux for bioinformatician !!!]]></title>
	<description><![CDATA[<p>Linux, free operating system for computers, provides several powerful admin tools and utilities which will help you to manage your systems effectively and handle huge amount of genomic/biological data with an ease. The field of bioinformatics relies heavily on Linux-based computers and software. Although most bioinformatics programs can be compiled to run. If you don&rsquo;t know what these no so user-friendly tools are and how to use them, you could be spending lot of time trying to perform even the basic admin tasks. The focus of this linux series is to help you understand system admin as well as basic tools, which will help you to become an effective bioinformatician and computational biologist.<br /><br /></p><p>For knowledge about Linux and their importance amongst bioinformatician plesae read this article "<a href="http://www.ualberta.ca/~stothard/downloads/linux_for_bioinformatics.pdf">An introduction to Linux for bioinformatics</a>" by Paul Stothard.</p><p>Linux cheat sheet at http://bioinformaticsonline.com/file/view/87/linux-cheat-sheet</p><p>Please browse for futher useful linux pages on right hand side ...</p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36216/crusview</guid>
	<pubDate>Thu, 12 Apr 2018 09:22:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36216/crusview</link>
	<title><![CDATA[CrusView]]></title>
	<description><![CDATA[<p><span>CrusView&nbsp;is a java based tool for karyotype/genome visualization and comparison of crucifer&nbsp;Species. It also integrates an binary version of KGBassembler and a&nbsp;post-modification step for its assembling result.</span></p><p>Address of the bookmark: <a href="http://www.cmbb.arizona.edu/?page_id=250" rel="nofollow">http://www.cmbb.arizona.edu/?page_id=250</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/9204/keep-your-important-ssh-session-running-when-you-disconnect-from-server</guid>
	<pubDate>Sat, 15 Mar 2014 21:39:17 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/9204/keep-your-important-ssh-session-running-when-you-disconnect-from-server</link>
	<title><![CDATA[Keep Your Important SSH Session Running when You Disconnect from Server !!!]]></title>
	<description><![CDATA[<p>As a Bioinformatician/ Computational biologist we swim in the ocean of genomic/proteomics data, and play with them with an ease. In our day to day simulation, analysis, comparative study we do need to run exhaustive programs, which might take more than a week. In such cases we do need to disconnect from sever in a way that our program/session should not get terminated. To do so there are lots of software, tools such as tmux ( <a href="http://tmux.sourceforge.net/">http://tmux.sourceforge.net/</a>, nohup (<a href="http://ss64.com/bash/nohup.html">http://ss64.com/bash/nohup.html</a>) , byobu (<a href="https://help.ubuntu.com/10.04/serverguide/byobu.html">https://help.ubuntu.com/10.04/serverguide/byobu.html</a>) and other commands (disown -a &amp;&amp; exit), but following are the ones I use the most.</p><p>Screen is like a window manager for your console. It will allow you to keep multiple terminal sessions running and easily switch between them. It also protects you from disconnection, because the screen session doesn&rsquo;t end when you get disconnected.<br /><br />You&rsquo;ll need to make sure that screen is installed on the server you are connecting to. If that server is Ubuntu or Debian, just use this command:<br /><br />sudo apt-get install screen<br /><br />Now you can start a new screen session by just typing screen at the command line. You&rsquo;ll be shown some information about screen. Hit enter, and you&rsquo;ll be at a normal prompt.<br /><br /><strong>To disconnect (but leave the session running)</strong><br /><br />Hit Ctrl + A and then Ctrl + D in immediate succession. You will see the message [detached]<br /><br /><strong>To reconnect to an already running session</strong><br /><br />screen -r<br /><br /><strong>To reconnect to an existing session, or create a new one if none exists</strong><br /><br />screen -D -r<br /><br /><strong>To create a new window inside of a running screen session</strong><br /><br />Hit Ctrl + A and then C in immediate succession. You will see a new prompt.<br /><br /><strong>To switch from one screen window to another</strong><br /><br />Hit Ctrl + A and then Ctrl + A in immediate succession.<br /><br /><strong>To list open screen windows</strong><br /><br />Hit Ctrl + A and then W in immediate succession</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38577/genoviz-visualization-software-for-genomics</guid>
	<pubDate>Wed, 02 Jan 2019 04:07:57 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38577/genoviz-visualization-software-for-genomics</link>
	<title><![CDATA[GenoViz: Visualization software for genomics]]></title>
	<description><![CDATA[<p><span>GenoViz provides software applications and re-usable components for data visualization and data sharing in genomics. Our flagship product is Integrated Genome Browser (IGB).</span><br><br><span>For more information about IGB, visit&nbsp;</span><a href="http://bioviz.org/" target="_blank">http://bioviz.org<span></span></a><span>.</span><br><br><span>Source code for the project was hosted here for many years. In 2014, we moved to a new git repository at&nbsp;</span><a href="http://www.bitbucket.org/lorainelab/integrated-genome-browser" target="_blank">http://www.bitbucket.org/lorainelab/integrated-genome-browser<span></span></a><span>. We are still using SourceForge to distribute new releases of IGB as compiled code (igb.zip) you can use to run IGB on your computer.&nbsp;</span><br><br><span>If you have questions, feel free to get in touch. Contact project head Ann Loraine (</span><a href="mailto:aloraine@uncc.edu" target="_blank">aloraine@uncc.edu<span></span></a><span>) or lead developer David Norris (</span><a href="mailto:dcnorris@uncc.edu" target="_blank">dcnorris@uncc.edu<span></span></a><span>&gt;).</span></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/genoviz/" rel="nofollow">https://sourceforge.net/projects/genoviz/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/9242/check-the-size-of-a-directory-free-disk-space</guid>
	<pubDate>Mon, 17 Mar 2014 02:35:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/9242/check-the-size-of-a-directory-free-disk-space</link>
	<title><![CDATA[Check the Size of a directory &amp; Free disk space.]]></title>
	<description><![CDATA[<p>The amount of databases we bioinformatician deal are just HUGE &hellip; In such cases, we always need to check our server for free spaces etc. I planned this article to explains 2 simple commands that most bioinformatician want to know when they start using Linux / BioLinux. First: Size of a directory (du) and and second: free disk space that exists on your machine (df).</p><p><br /><strong>'du' &ndash; Check the size of a directory</strong></p><p><br />$ du<br />This command ( du) gives you a list of directories that exist in the current working directory along with their sizes in kilobytes (default). The last line of the output gives you the total size of the current directory including its subdirectories. <br /><br />$ du /home/jin1<br />The above command would give you the directory size of the directory /home/david<br /><br />$ du -h<br />The same &ldquo;du&rdquo;command with some flag gives you a better output than the default one. The option '-h' stands for human readable format. Therefore, in order to print the sizes of the files / directories in your desire notation use this time suffixed with a 'k' if its kilobytes and 'M' if its Megabytes and 'G' if its Gigabytes.<br /><br />$ du -ah<br />If you are interested in checking everything present in a folder use above mentioned command. It gives us not only the directories but also all the files that are present in the current directory. The &ldquo;-a&rdquo; flag displays the filenames along with the directory names in the output. <br /><br />$ du -c<br />This gives you a grand total as the last line of the output. So if your directory occupies 30MB the last 2 lines of the output would be 30M.<br /><br />$ du -s<br />Use this command to displays a summary of the directory size. It is the simplest way to know the total size of the current directory.<br /><br />$ du -S<br />This would display the size of the current directory excluding the size of the subdirectories that exist within that directory. So it basically shows you the total size of all the files that exist in the current directory.<br /><br />$ du --exculde=mp3<br />Several times it required to exclude some directory in our size calculation. In such cases the above command would display the size of the current directory along with all its subdirectories, but it would exclude all the files having the given pattern present in their filenames.</p><p><br /><strong>'df' - finding the disk free space / disk usage</strong><br /><br />$ df<br />Hmmm &hellip; now &ldquo;df&rdquo; command is really useful, and I guess you are going to use it over time. Typing the above command, outputs a table consisting of 6 columns. All the columns are very easy to understand. Remember that the 'Size', 'Used' and 'Avail' columns use kilobytes as the unit. The 'Use%' column shows the usage as a percentage which is also very useful.<br /><br />$ df -h<br />Displays the same output as the previous command but the '-h' indicates human readable format. Hence instead of kilobytes as the unit the output would have 'M' for Megabytes and 'G' for Gigabytes.<br /><br />Example: Linux installed on /dev/hda1<br />$ df -h | grep /dev/hda1</p><p><br />All right, this is not the only option to check the sizes and free spaces but there are a few more options that can be used with 'du' and 'df' . I will discuss it later.<br /><br /></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39917/chromomap-an-r-package-for-interactive-visualization-and-annotation-of-chromosomes</guid>
	<pubDate>Sat, 07 Sep 2019 10:45:31 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39917/chromomap-an-r-package-for-interactive-visualization-and-annotation-of-chromosomes</link>
	<title><![CDATA[chromoMap-An R package for Interactive Visualization and Annotation of Chromosomes]]></title>
	<description><![CDATA[<p><code>chromoMap</code>&nbsp;provides interactive, configurable and elegant graphics visualization of chromosomes or chromosomal regions allowing users to map chromosome elements (like genes,SNPs etc.) on the chromosome plot.Each chromosome is composed of loci(representing a specific range determined based on chromosome length) that, on hover, shows details about the annotations in that locus range. The plots can be saved as HTML documents that can be shared easily. In addition, you can include them in R Markdown or in R Shiny applications.</p>
<p>Some of the prominent features of the package are:</p>
<ul>
<li>visualizing polyploidy simultaneously on the same plot.</li>
<li>annotating groups of elements as distinct colors.</li>
<li>creating chromosome heatmaps.</li>
<li>adjusting chromosome range or visualizing chromosome regions such as genes</li>
<li>adding labels to the plot</li>
<li>adding hyperlinks to each element</li>
</ul><p>Address of the bookmark: <a href="https://cran.r-project.org/web/packages/chromoMap/vignettes/chromoMap.html" rel="nofollow">https://cran.r-project.org/web/packages/chromoMap/vignettes/chromoMap.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/9441/jrf-at-gautam-buddha-university</guid>
  <pubDate>Thu, 27 Mar 2014 03:53:57 -0500</pubDate>
  <link></link>
  <title><![CDATA[JRF at Gautam Buddha University]]></title>
  <description><![CDATA[
<p>Gautam Buddha University (GBU) Noida invites applications for the follow posts<br />2014 March Advertisement from Gautam Buddha University (GBU)<br />Junior Research Fellow (JRF)<br />No. of Positions:  01<br />Educational Qualifications:<br />Master degree in any discipline of Life Science with NET qualified or valid GATE score. Desirable Qualification: Preference will be given to candidates having research experience in Bioinformatics<br />Experience:</p>

<p>(details of experience required)<br />Pay Scale:<br />INR Rs.12000/-P.M. + HRA<br />Category:<br />Science and Research Jobs<br />How To Apply:<br />The interested candidates should report for the Interview on 31st<br />March, 2014 at 10:00 am in the Conference Room of Dean, School of Biotechnology, First floor, Gautam Buddha University, Greater<br />Noida. Interested candidates may also send their resume to undersigned by post-mail/e-mail shaktis@gbu.ac.in or shaktisahi@gmail.com. No TA and DA will be paid for appearing for the interview<br />Download Official Notification:</p>

<p>http://www.gbu.ac.in/Recruitment/JRF_advertisement_DSTProject_Shakti_24March14.pdf</p>
]]></description>
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<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>
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