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<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/30242?offset=1100</link>
	<atom:link href="https://bioinformaticsonline.com/related/30242?offset=1100" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	
<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/21021/ra-bioinformatics-at-iiser</guid>
  <pubDate>Fri, 06 Feb 2015 04:05:49 -0600</pubDate>
  <link></link>
  <title><![CDATA[RA Bioinformatics at IISER]]></title>
  <description><![CDATA[
<p>Advertisement: Research Position in Computational Biology in the group of Shree P. Pandey Positions available in the area of NGS data analysis, bioinformatics, plant genomics Project Description: Projects involves high throughput analysis of data mostly generated by massively parallel sequencing (RNA-Seq and small-RNA-Seq), microarrays and related platforms.</p>

<p>We are looking for highly motivated and bright individuals interested in high-throughput cutting-edge data analyses methods in genomics (computational positions). Available positions:</p>

<p>Applications are invited from suitable candidates in both, the Max Planck India Partner Program and the CRP Wheat Program for openings at the levels:</p>

<p>Minimum qualification Salary scale (per month)</p>

<p>Project assistant Bachelor’s / Master’s Rs. 10000 / Rs. 14000</p>

<p>Project fellow (junior data analyst) Masters + research experience Rs. 16000</p>

<p>Research fellow (senior data analyst) Masters + adequate research experience/desirable skill sets Rs. 22000</p>

<p>Research Associated PhD (&lt;1yr) / &gt; 1 yr experience Rs. 28000 / Rs. 32000</p>

<p>Condition to satisfactory performance, availability of funds and requirements of the project, the positions could be available upto a period of ~2 years (or funding of the project).</p>

<p>Essential qualification: MSc/BTech/MTech/PhD (or other suitable qualification) in discipline related to bioinformatics, computational biology, computer application (or equivalent)/ ‘Advance PostGraduate Diploma in Bioinformatics’. Proficiency in one of the programming languages or statistics (proficient in R for example) is compulsory.</p>

<p>Desirable qualification:</p>

<p>1. Programming experiences in at least one low level language such as C/C++ and one scripting language such as Perl/Python/PHP and knowledge of SQL/MySQL.</p>

<p>2. Substantial experience in the linux or other unix environments.</p>

<p>Application process: Applications should contain CV along with brief description (maximum 1 page) of research conducted (highlighting skills and experience) till now. Applications should be sent by email to Shree P. Pandey, Department of Biological Sciences, IISER-Kolkata, Mohanpur Campus, West Bengal within 2 weeks (Feb 19th 2015). E-mail: sppiiserkol@gmail.com, sppandey@iiserkol.ac.in Brief description of the group: We are an interdisciplinary group focusing on small-RNA (miRNA, siRNA) mediated regulation of signaling and defense. Project equally involve bioinformatics and systems biology (specially microarrays and next-generation sequencing (NGS) data analysis and its use), along with plant molecular biology, genetic engineering, field biology, and analytical plant chemistry for understanding response of plants to biotic stresses. For more details visit: http://www.iiserkol.ac.in/~sppandey/</p>

<p>Advertisement:</p>

<p>www.iiserkol.ac.in/images/iiserk/advertisements/advertisement_7_spp_feb_2015.pdf</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33789/i-pv-interactive-protein-sequence-visualization</guid>
	<pubDate>Mon, 03 Jul 2017 07:52:51 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33789/i-pv-interactive-protein-sequence-visualization</link>
	<title><![CDATA[I-PV: Interactive Protein Sequence Visualization]]></title>
	<description><![CDATA[<p><span>I-PV is a interactive data visualization software designed for inspection of protein sequences and mutation information. It is mainly used for Genetics and Bioinformatics. So what exactly makes it standout?</span></p>
<p><span>http://i-pv.org/ipv_rec</span></p><p>Address of the bookmark: <a href="http://i-pv.org/" rel="nofollow">http://i-pv.org/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/21065/ra-bioinformatics-at-north-eastern-hill-university</guid>
  <pubDate>Sat, 07 Feb 2015 06:06:05 -0600</pubDate>
  <link></link>
  <title><![CDATA[RA Bioinformatics at North Eastern Hill University]]></title>
  <description><![CDATA[
<p>Bioinformatics Infrastructure Facility, Department of RDAP, NEHU vacancy of Research Associate</p>

<p>Name of the Post: Research Associate<br />No. of the Post: 01 One<br />Age Limit: Max. 35 years<br />Salary: Rs. 22000/- per month plus HRA</p>

<p>Required Job Profile:<br />Candidate must possess M.Sc. in bioinformatics or biotechnology from recognized university or institute.<br />Desired Job Profile;<br />Candidate having Ph.D. or pursuing Ph.D. in the related subject or equivalent published work in reputed peer reviewed journals or advance PG dipoma in bioinformatics course.</p>

<p>How to apply:<br />Eligible and interested candidates should need to send the bio-data and bring all related documents in original and set of attested copies of the same in the time of interview.</p>

<p>Last date: 16.02.2015<br />Refer to http://www.nehu.ac.in/Advertisements/BIFTuraAdvt_221214.pdf</p>

<p>Summary <br />Employer Address:	Dr.B.K. Mishra Coordinator BIF, RDAP Department, North Eastern Hill University, Tura Campus, Tura, Meghalaya<br />Email:	drbkm1972@yahoo.co.in;birendramishra14@gmail.com<br />URL:	http://www.nehu.ac.in/Advertisements/BIFTuraAdvt_221214.pdf<br />Phone:	03651-223107<br />Required Skills:	not mentioned / required for this post<br />Required Experience:	not mentioned / required for this job post<br />Required Education:	M.Sc. in bioinformatics or biotechnology from recognized university or institute.<br />Job Location:	Tura, Meghalaya, India</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36109/sankeynetwork-with-networkd3</guid>
	<pubDate>Fri, 06 Apr 2018 12:07:55 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36109/sankeynetwork-with-networkd3</link>
	<title><![CDATA[sankeyNetwork with networkD3]]></title>
	<description><![CDATA[<p><span>You can also create&nbsp;</span><a href="http://en.wikipedia.org/wiki/Sankey_diagram">Sankey diagrams</a><span>&nbsp;with&nbsp;</span><code>sankeyNetwork</code><span>. Here is an example using downloaded JSON data:</span></p>
<p><span>https://en.wikipedia.org/wiki/Sankey_diagram</span></p><p>Address of the bookmark: <a href="https://christophergandrud.github.io/networkD3/#sankey" rel="nofollow">https://christophergandrud.github.io/networkD3/#sankey</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/21241/pacman</guid>
	<pubDate>Mon, 16 Feb 2015 12:15:17 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/21241/pacman</link>
	<title><![CDATA[Pacman]]></title>
	<description><![CDATA[<p><span>The pacman package is an R package management tool that combines the functionality of base library related functions into intuitively named functions. This package is ideally added to .Rprofile to increase workflow by reducing time recalling obscurely named functions, reducing code and integrating functionality of base functions to simultaneously perform multiple actions.<br /><br />Function names in the pacman package follow the format of p_xxx where &lsquo;xxx&rsquo; is the task the function performs. For instance the p_load function allows the user to load one or more packages as a more generic substitute for the library or require functions and if the package isn&rsquo;t available locally it will install it for you.<br /><br /></span></p><p><strong>Installation</strong></p><p><span>To download the development version of pacman:</span></p><p><span>Download the </span><a href="https://github.com/trinker/pacman/zipball/master">zip ball</a><span> or </span><a href="https://github.com/trinker/pacman/tarball/master">tar ball</a><span>, decompress and run </span><code>R CMD INSTALL</code><span> on it, or use th</span><span>e </span><strong>devtools</strong><span> package to install the development version:</span></p><pre title="">## Make sure your current packages are up to date
update.packages()
## devtools is required
devtools::install_github("trinker/pacman")
</pre><p>Note: Windows users need <a href="http://www.murdoch-sutherland.com/Rtools/">Rtools</a> and <a href="http://CRAN.R-project.org/package=devtools">devtools</a> to install this way.</p><p>More at https://github.com/trinker/pacman</p><p>&nbsp;</p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36907/higlass-a-tool-for-exploring-genomic-contact-matrices-and-tracks</guid>
	<pubDate>Mon, 11 Jun 2018 09:44:49 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36907/higlass-a-tool-for-exploring-genomic-contact-matrices-and-tracks</link>
	<title><![CDATA[HiGlass: a tool for exploring genomic contact matrices and tracks.]]></title>
	<description><![CDATA[HiGlass is a tool for exploring genomic contact matrices and tracks. Please take a look at the examples and documentation for a description of the ways that it can be configured to explore and compare contact matrices. To load private data, HiGlass can be run locally within a Docker container. The HiC data in the examples below is from Rao et al. (2014)

http://higlass.io/<p>Address of the bookmark: <a href="http://higlass.io/" rel="nofollow">http://higlass.io/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/21435/ra-walk-in-interview-nbfgr-lucknow</guid>
  <pubDate>Tue, 24 Feb 2015 08:23:48 -0600</pubDate>
  <link></link>
  <title><![CDATA[RA WALK-IN-INTERVIEW @ NBFGR, Lucknow]]></title>
  <description><![CDATA[
<p>F.No. 1(122)/2015-Admn. (CABin Project)<br />Research Associate/Young Professional/SRF Zoology job vacancies in National Bureau of Fish Genetic Resources (NBFGR)<br />Post Name: Research Associate (Computer Science/ Applications)                <br />Qualification: Ph.D. In Computer Science/Computer Applications or equivalent. Or Post-Graduation in Computer Science/ Computer Applications with 1st Division or 60% marks or equivalent overall grade point average with at least two years of research experience. Desirable: 1. Expertise and experience of working/ handling High Performance Computing (H PC) and genomic resource data. 2. Expertise on database management, data mining technologies/ softwares/tools. 3. Published Research papers	<br />No.of Post: 1<br />Pay Scale: Consolidated Rs.24,000/- p.m. + HRA (as admissible) for Ph.D. holders and consolidated `23,000/- + HRA (as admissible) for Master degree holder.	<br />Age:40 years</p>

<p>Young Professional II (Computer Science/Applications)	<br />Master degree in Computer Science/Computer Applications/B.Tech (Computer Science) or equivalent. <br />Desirable: 1. Knowledge of Statistical and Computational Genomics/ Proteomics/ Bioinformatics/Data mining tools. 2. Experience in handling HPC, programming languages and database management packages.	<br />A consolidated salary of Rs.25,000/- per month.	<br />21 to 45 year</p>

<p>Young Professional II (Biotechnology/ Bioinformatics)	<br />Master degree in Bioinformatics/ Biotechnology/ B. Tech(Biotech) or equivalent. Desirable: 1. Knowledge of Computational Genomics/Proteomics/Bioinformatics. 2. Expertise in NGS data analysis and knowledge of allied software and tools.	<br />A consolidated salary of Rs.25,000/- per month.	</p>

<p>Senior Research Fellow	<br />1. Bachelors degree with Zoology, Fisheries and 2. Master's degree in Fishery science/ Zoology with Fisheries/ Biotechnology/ Life Sciences with specialization in Fisheries/ Molecular Biology. 3. 1 st Division or 60% marks or equivalent overall grade point average. <br />Desirable: Work experience in Fisheries, molecular research techniques, bioinformatics and Computer skills. NET qualified <br />Note: The project involves extensive exploration tours and sampling from water bodies all over India	<br />Rs.16,000/- p.m. for 1st &amp; 2nd year and `18,000/- p.m. for 3rd and subsequent years +HRA (as per rules)	35 years for male and 40 years for female candidate</p>

<p>How to apply</p>

<p>A walk-in-interview will be held on 04th March, 2015 at 10:00 hrs at National Bureau of Fish Genetic Resources, Lucknow. Eligible and desirous candidates fulfilling all the requirements may appear for the interview with duly filled in application giving full details of academic records and experience(s) along with attested photocopy as well as original copy of the relevant documents and a passport size photograph on the attached proforma.</p>

<p>http://www.nbfgr.res.in/</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38745/osprey-network-visualization-system</guid>
	<pubDate>Sun, 20 Jan 2019 05:34:24 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38745/osprey-network-visualization-system</link>
	<title><![CDATA[Osprey: Network Visualization System]]></title>
	<description><![CDATA[<p>Osprey is a software platform for the visualization of complex biological interaction networks. Osprey builds data-rich graphical representations from&nbsp;<a href="http://geneontology.org/" title="GENE ONTOLOGY CONSORTIUM">Gene Ontology (GO)</a>&nbsp;annotated interaction data maintained by the&nbsp;<a href="https://thebiogrid.org/" title="The BioGRID">BioGRID</a>.</p>
<p>Osprey is developed by the&nbsp;<a href="http://www.tyerslab.com/">TyersLab</a>&nbsp;and is a part of the&nbsp;<a href="https://thebiogrid.org/" title="The BioGRID">BioGRID</a>&nbsp;family of software. It utilizes both&nbsp;<a href="https://www.mysql.com/" title="MySQL Database">MySQL</a>&nbsp;and&nbsp;<a href="http://openjdk.java.net/" title="OpenJDK">Java</a>&nbsp;to operate and is compatible with&nbsp;<a href="https://www.microsoft.com/en-us/windows/" title="Microsoft Windows">Windows</a>,&nbsp;<a href="http://www.ubuntu.com/">Linux</a>, and&nbsp;<a href="http://www.apple.com/" title="Apple">Apple</a>&nbsp;operating systems.</p>
<p>These works were published in&nbsp;<strong>Breitkreutz, BJ., Stark, C., Tyers M. "Osprey: A Network Visualization System." Genome Biology 2003 4(3):R22</strong>&nbsp;<a href="http://genomebiology.com/2003/4/3/R22" title="Genome Biology">[Genome Biology]</a>&nbsp;<a href="http://genomebiology.com/content/pdf/gb-2003-4-3-r22.pdf" title="Osprey PDF">[PDF]</a>&nbsp;<a href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;list_uids=12620107&amp;dopt=Abstract" title="Pubmed">[PubMed]</a>&nbsp;and supported by the&nbsp;<a href="http://www.nih.gov/" title="NIH">National Institutes of Health</a>,&nbsp;<a href="http://www.cihr-irsc.gc.ca/" title="CIHR">Canadian Institutes of Health Research</a>, and&nbsp;<a href="http://www.genomecanada.ca/en/" title="Genome Canada">Genome Canada</a>.</p><p>Address of the bookmark: <a href="https://osprey.thebiogrid.org/" rel="nofollow">https://osprey.thebiogrid.org/</a></p>]]></description>
	<dc:creator>BioJoker</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/21443/a-guide-for-complete-r-beginners-getting-data-into-r</guid>
	<pubDate>Tue, 24 Feb 2015 20:15:08 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/21443/a-guide-for-complete-r-beginners-getting-data-into-r</link>
	<title><![CDATA[A guide for complete R beginners :- Getting data into R]]></title>
	<description><![CDATA[<p>For a beginner this can be is the hardest part, it is also the most important to get right.</p><p>It is possible to create a vector by typing data directly into R using the combine function &lsquo;c&rsquo;</p><blockquote><p><strong>x </strong></p></blockquote><p>same as</p><blockquote><p><strong>x </strong></p></blockquote><p>creates the vector x with the numbers between 1 and 5.</p><p>You can see what is in an object at any time by typing its name;</p><blockquote><p><strong>x</strong></p></blockquote><p>will produce the output<strong> &lsquo;[1] 1 2 3 4 5&prime;</strong></p><p>Note that names need to be quoted</p><blockquote><p><strong>daysofweek </strong><strong>&larr; c(&lsquo;Monday&rsquo;, &lsquo;Tuesday&rsquo;, &lsquo;Wednesday&rsquo;, &lsquo;Thursday&rsquo;, &lsquo;Friday&rsquo;);</strong></p></blockquote><p>Usually however you want to input from a file. We have touched on the &lsquo;read.table&rsquo; function already.</p><blockquote><p><strong>mydata </strong></p></blockquote><p>Now <strong>mydata</strong> is a data frame with multiple vectors</p><p>each vector can be identified by the default syntax</p><p>#if any of these are typed it will print to screen</p><blockquote><p><strong>mydata$V1 mydata$V2 mydata$V3 </strong></p></blockquote><p>By default the function assumes certain things from the file</p><ul>
<li>The file is a plain text file (there are function to read excel files: <em>not covered here</em>)</li>
<li>columns are separated by any number of tabs or spaces</li>
<li>there is the same number of data points in each column</li>
<li>there is no header row (labels for the columns)</li>
<li>there is no column with names for the rows** [I&rsquo;ll explain].</li>
</ul><p><span style="text-decoration: underline;">If any of these are false, we need to tell that to the function</span></p><p>If it has a header column</p><blockquote><p><strong>mydata <em>header=T also works</em></strong></p></blockquote><p>Note that there is a comma between different parts of the functions arguments</p><p>If there is one less column in the header row, then R assumes that the 1<sup>st</sup> column of data after the header are the row names</p><p>Now the vectors (columns) are identified by their name</p><p>#if any of these are typed it will print to screen</p><blockquote><p><strong>mydata$A mydata$B mydata$C </strong></p></blockquote><p># Summary about the whole data frame</p><blockquote><p><strong>summary(mydata)</strong></p></blockquote><p># Summary information of column A</p><blockquote><p><strong>summary(mydata$A) </strong></p></blockquote><p>We can shortcut having to type the data frame each time by attaching it</p><blockquote><p><strong>attach(mydata)</strong></p></blockquote><p># summary of column B as &lsquo;mydata&rsquo; is attached</p><blockquote><p><strong>summary(B)</strong></p></blockquote><p><span style="text-decoration: underline;">Two other important options for </span><em><span style="text-decoration: underline;">read.table</span></em></p><p>If is is separated only by tabs and has a header</p><blockquote><p><strong>mydata </strong></p></blockquote><p>Really useful if you have spaces in the contents of some columns, so R does not mess up reading the columns . However if the columns or of an uneven length it will tell you.</p><p>If you know that the file has uneven columns</p><blockquote><p><strong>mydata </strong></p></blockquote><p>This causes R to fill empty spaces in a columns with &lsquo;NA&rsquo; .</p><p>The last two examples will still work with our file and give the same result as with only headers=T</p><p><span style="text-decoration: underline;">Graphs</span></p><p>to get an idea of what R is capable of type</p><blockquote><p><strong>demo(graphics)</strong></p></blockquote><p>steps through the examples, and the code is printed to the screen</p><p>We will work with simpler examples that have immediate use to biologists.</p><p>Remember to get more information about the options to a function type &lsquo;?function&rsquo;</p><p><span style="text-decoration: underline;">Histogram of A</span><span style="text-decoration: underline;"></span></p><blockquote><p><strong>hist(mydata$A)</strong></p></blockquote><p>If there was more data we could increase the number of vertical columns with the option, breaks=50 (or another relevant number).</p><blockquote><p><strong>boxplot(mydata)</strong></p></blockquote><p>We can get rid of the need to type the data frame each time by using the <strong>attach</strong> function</p><p># if not already done so</p><blockquote><p><strong>attach(mydata) </strong></p><p><strong>boxplot(mydata$A, mydata$B, name=c(&ldquo;Value A&rdquo;, &ldquo;Value B&rdquo;) , ylab=&ldquo;Count of Something&rdquo;)</strong></p></blockquote><p>same as</p><blockquote><p><strong>boxplot(A, B, name=c(&ldquo;Value A&rdquo;, &ldquo;Value B&rdquo;) , ylab=&ldquo;Count of Something&rdquo;)</strong></p></blockquote><p><span style="text-decoration: underline;">Scatter plot</span></p><p># if not already done so</p><blockquote><p><strong>attach(mydata) </strong></p><p><strong>plot(A,B) # or plot(mydata$A, mydata$B)</strong></p></blockquote><p><strong><span style="text-decoration: underline;">SAVING an image</span></strong></p><p>Windows users (Rgui) RIGHT click on image and select which you want.</p><p><span style="text-decoration: underline;">These instructions work for everyone.</span></p><p>You need to create a new device of the type of file you need, then send the data to that device</p><p>to save as a png file (easy to load into the likes of powerpoint, also great for web applications.</p><blockquote><p><strong>png(&lsquo;filename&rsquo;) </strong></p><p><strong>boxplot(A, B, name=c(&ldquo;Value A&rdquo;, &ldquo;Value B&rdquo;) , ylab=&ldquo;Count of Something&rdquo;)</strong></p></blockquote><p>or to save as a pdf</p><blockquote><p><strong>pdf(&lsquo;filename&rsquo;) </strong></p><p><strong>boxplot(A, B, name=c(&ldquo;Value A&rdquo;, &ldquo;Value B&rdquo;) , ylab=&ldquo;Count of Something&rdquo;)</strong></p></blockquote><p><span style="text-decoration: underline;">Note</span></p><ul>
<li>Nothing will appear on screen, the output is going to the file</li>
<li>Also it may not be saved immediately but will once the device (or R) is turned quit.</li>
</ul><p>To quit R type</p><p><strong>q() # </strong>If you save your session, next time you start R, you will have your data preloaded.</p><p>Or if you want to remain in R</p><blockquote><pre><strong>dev.off() #</strong>turns of the png (or pdf etc) device, thus forces the data to save</pre></blockquote>]]></description>
	<dc:creator>Archana Malhotra</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41209/juicebox-visualization-and-analysis-software-for-hi-c-data</guid>
	<pubDate>Fri, 21 Feb 2020 00:33:38 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41209/juicebox-visualization-and-analysis-software-for-hi-c-data</link>
	<title><![CDATA[Juicebox: Visualization and analysis software for Hi-C data]]></title>
	<description><![CDATA[<p>Juicebox is visualization software for Hi-C data. This distribution includes the source code for Juicebox,&nbsp;<a href="https://github.com/theaidenlab/juicer/wiki/Download">Juicer Tools</a>, and&nbsp;<a href="https://aidenlab.org/assembly/">Assembly Tools</a>.&nbsp;<a href="https://github.com/theaidenlab/juicebox/wiki/Download">Download Juicebox here</a>, or use&nbsp;<a href="https://aidenlab.org/juicebox">Juicebox on the web</a>. Detailed documentation is available&nbsp;<a href="https://github.com/theaidenlab/juicebox/wiki">on the wiki</a>. Instructions below pertain primarily to usage of command line tools and the Juicebox jar files.</p>
<p>Juicebox can now be used to visualize and interactively (re)assemble genomes. Check out the Juicebox Assembly Tools Module website&nbsp;<a href="https://aidenlab.org/assembly">https://aidenlab.org/assembly</a>&nbsp;for more details on how to use Juicebox for assembly.</p>
<p>GUI at&nbsp;<a href="https://aidenlab.org/juicebox/">https://aidenlab.org/juicebox/</a></p><p>Address of the bookmark: <a href="https://github.com/aidenlab/Juicebox" rel="nofollow">https://github.com/aidenlab/Juicebox</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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