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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/26573?offset=910</link>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/22780/ra-bioinformatics-at-institution-centre-for-human-genetics-bangalore</guid>
  <pubDate>Wed, 17 Jun 2015 19:14:37 -0500</pubDate>
  <link></link>
  <title><![CDATA[RA Bioinformatics at Institution: Centre for Human Genetics,  Bangalore]]></title>
  <description><![CDATA[
<p>Institution: Centre for Human Genetics, <br />Bangalore <br />Discipline: Molecular Genetics of Human Disease Biology </p>

<p>Minimum qualification: MSc in any branch of life sciences</p>

<p>Applications are invited for the position of a Research Assistant in the Centre for Human Genetics, Bangalore. </p>

<p>The project involves identification of mutations in MPS (mucopolysaccharidosis) patients, and study of their predicted effects to understand how the mutations lead to disease. </p>

<p>Techniques used will be genomic DNA isolation, PCR, DNA sequencing and sequence analysis. Computational tools would also be used to analyse and interpret data. </p>

<p>Candidates may be assigned work in the ongoing project or in new ones. </p>

<p>The candidate who is selected and joins would acquire hands-on experience in research and the capability to conduct insightful research. </p>

<p>Candidates applying for the position should have an MSc in any branch of life sciences. Those with research experience in cell and molecular biology, and high NET/ GATE score would be preferred. </p>

<p>The successful applicant is expected to stay for at least one and a half years. </p>

<p>Please apply with CV to Sudha Srinivasan (sudha@ibab.ac.in), stating where you saw this ad.</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/33869/import-r-data</guid>
	<pubDate>Wed, 12 Jul 2017 08:30:46 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/33869/import-r-data</link>
	<title><![CDATA[Import R Data]]></title>
	<description><![CDATA[<p>It is often necessary to import sample textbook data into R before you start working on your homework.</p><div id="node-69"><div><p><strong>Excel File</strong></p><p>Quite frequently, the sample data is in&nbsp;<span>Excel&nbsp;</span>format, and needs to be imported into R prior to use. For this, we can use the function&nbsp;<span>read.xls&nbsp;</span>from the&nbsp;<span>gdata&nbsp;</span>package. It reads from an Excel spreadsheet and returns a&nbsp;<a href="http://www.r-tutor.com/r-introduction/data-frame">data frame</a>. The following shows how to load an Excel spreadsheet named&nbsp;<span>"mydata.xls"</span>. This method requires Perl runtime to be present in the system.</p><blockquote><div id="listing-68"><span><a></a></span>&gt;&nbsp;library(gdata)&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;#&nbsp;load&nbsp;gdata&nbsp;package&nbsp;<br /><span><a></a></span>&gt;&nbsp;help(read.xls)&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;#&nbsp;documentation&nbsp;<br /><span><a></a></span>&gt;&nbsp;mydata&nbsp;=&nbsp;read.xls("mydata.xls")&nbsp;&nbsp;#&nbsp;read&nbsp;from&nbsp;first&nbsp;sheet</div></blockquote><p>Alternatively, we can use the function&nbsp;<span>loadWorkbook&nbsp;</span>from the&nbsp;<span>XLConnect&nbsp;</span>package to read the entire workbook, and then load the worksheets with&nbsp;<span>readWorksheet</span>. The&nbsp;<span>XLConnect&nbsp;</span>package requires Java to be pre-installed.</p><blockquote><div id="listing-69"><span><a></a></span>&gt;&nbsp;library(XLConnect)&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;#&nbsp;load&nbsp;XLConnect&nbsp;package&nbsp;<br /><span><a></a></span>&gt;&nbsp;wk&nbsp;=&nbsp;loadWorkbook("mydata.xls")&nbsp;<br /><span><a></a></span>&gt;&nbsp;df&nbsp;=&nbsp;readWorksheet(wk,&nbsp;sheet="Sheet1")</div></blockquote><p>&nbsp;</p><h4><a></a>Minitab File</h4><p>If the data file is in&nbsp;<span>Minitab Portable Worksheet&nbsp;</span>format, it can be opened with the function&nbsp;<span>read.mtp&nbsp;</span>from the&nbsp;<span>foreign&nbsp;</span>package. It returns a&nbsp;<a href="http://www.r-tutor.com/r-introduction/list">list</a>&nbsp;of components in the Minitab worksheet.</p><blockquote><div id="listing-70"><span><a></a></span>&gt;&nbsp;library(foreign)&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;#&nbsp;load&nbsp;the&nbsp;foreign&nbsp;package&nbsp;<br /><span><a></a></span>&gt;&nbsp;help(read.mtp)&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;#&nbsp;documentation&nbsp;<br /><span><a></a></span>&gt;&nbsp;mydata&nbsp;=&nbsp;read.mtp("mydata.mtp")&nbsp;&nbsp;#&nbsp;read&nbsp;from&nbsp;.mtp&nbsp;file</div></blockquote><p>&nbsp;</p><h4><a></a>SPSS File</h4><p>For the data files in&nbsp;<span>SPSS&nbsp;</span>format, it can be opened with the function&nbsp;<span>read.spss&nbsp;</span>also from the&nbsp;<span>foreign&nbsp;</span>package. There is a&nbsp;<span>"to.data.frame"&nbsp;</span>option for choosing whether a data frame is to be returned. By default, it returns a list of components instead.</p><blockquote><div id="listing-71"><span><a></a></span>&gt;&nbsp;library(foreign)&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;#&nbsp;load&nbsp;the&nbsp;foreign&nbsp;package&nbsp;<br /><span><a></a></span>&gt;&nbsp;help(read.spss)&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;#&nbsp;documentation&nbsp;<br /><span><a></a></span>&gt;&nbsp;mydata&nbsp;=&nbsp;read.spss("myfile",&nbsp;to.data.frame=TRUE)</div></blockquote><p>&nbsp;</p><h4><a></a>Table File</h4><p>A data table can resides in a text file. The cells inside the table are separated by blank characters. Here is an example of a table with 4 rows and 3 columns.</p><blockquote><div id="listing-72"><span><a></a></span>100&nbsp;&nbsp;&nbsp;a1&nbsp;&nbsp;&nbsp;b1&nbsp;<br /><span><a></a></span>200&nbsp;&nbsp;&nbsp;a2&nbsp;&nbsp;&nbsp;b2&nbsp;<br /><span><a></a></span>300&nbsp;&nbsp;&nbsp;a3&nbsp;&nbsp;&nbsp;b3&nbsp;<br /><span><a></a></span>400&nbsp;&nbsp;&nbsp;a4&nbsp;&nbsp;&nbsp;b4</div></blockquote><p>Now copy and paste the table above in a file named&nbsp;<span>"mydata.txt"&nbsp;</span>with a text editor. Then load the data into the workspace with the function&nbsp;<span>read.table</span>.</p><blockquote><div id="listing-73"><span><a></a></span>&gt;&nbsp;mydata&nbsp;=&nbsp;read.table("mydata.txt")&nbsp;&nbsp;#&nbsp;read&nbsp;text&nbsp;file&nbsp;<br /><span><a></a></span>&gt;&nbsp;mydata&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;#&nbsp;print&nbsp;data&nbsp;frame&nbsp;<br /><span><a></a></span>&nbsp;&nbsp;&nbsp;V1&nbsp;V2&nbsp;V3&nbsp;<br /><span><a></a></span>1&nbsp;100&nbsp;a1&nbsp;b1&nbsp;<br /><span><a></a></span>2&nbsp;200&nbsp;a2&nbsp;b2&nbsp;<br /><span><a></a></span>3&nbsp;300&nbsp;a3&nbsp;b3&nbsp;<br /><span><a></a></span>4&nbsp;400&nbsp;a4&nbsp;b4</div></blockquote><p>For further detail of the function&nbsp;<span>read.table</span>, please consult the R documentation.</p><blockquote><div id="listing-74"><span><a></a></span>&gt;&nbsp;help(read.table)</div></blockquote><p>&nbsp;</p><h4><a></a>CSV File</h4><p>The sample data can also be in&nbsp;<span>comma separated values&nbsp;</span>(CSV) format. Each cell inside such data file is separated by a special character, which usually is a comma, although other characters can be used as well.</p><p>The first row of the data file should contain the column names instead of the actual data. Here is a sample of the expected format.</p><blockquote><div id="listing-75"><span><a></a></span>Col1,Col2,Col3&nbsp;<br /><span><a></a></span>100,a1,b1&nbsp;<br /><span><a></a></span>200,a2,b2&nbsp;<br /><span><a></a></span>300,a3,b3</div></blockquote><p>After we copy and paste the data above in a file named&nbsp;<span>"mydata.csv"&nbsp;</span>with a text editor, we can read the data with the function&nbsp;<span>read.csv</span>.</p><blockquote><div id="listing-76"><span><a></a></span>&gt;&nbsp;mydata&nbsp;=&nbsp;read.csv("mydata.csv")&nbsp;&nbsp;#&nbsp;read&nbsp;csv&nbsp;file&nbsp;<br /><span><a></a></span>&gt;&nbsp;mydata&nbsp;<br /><span><a></a></span>&nbsp;&nbsp;Col1&nbsp;Col2&nbsp;Col3&nbsp;<br /><span><a></a></span>1&nbsp;&nbsp;100&nbsp;&nbsp;&nbsp;a1&nbsp;&nbsp;&nbsp;b1&nbsp;<br /><span><a></a></span>2&nbsp;&nbsp;200&nbsp;&nbsp;&nbsp;a2&nbsp;&nbsp;&nbsp;b2&nbsp;<br /><span><a></a></span>3&nbsp;&nbsp;300&nbsp;&nbsp;&nbsp;a3&nbsp;&nbsp;&nbsp;b3</div></blockquote><p>In various European locales, as the comma character serves as the decimal point, the function&nbsp;<span>read.csv2&nbsp;</span>should be used instead. For further detail of the&nbsp;<span>read.csv&nbsp;</span>and&nbsp;<span>read.csv2&nbsp;</span>functions, please consult the R documentation.</p><blockquote><div id="listing-77"><span><a></a></span>&gt;&nbsp;help(read.csv)</div></blockquote><p>&nbsp;</p><h4><a></a>Working Directory</h4><p>Finally, the code samples above assume the data files are located in the R&nbsp;<span>working</span>&nbsp;<span>directory</span>, which can be found with the function&nbsp;<span>getwd</span>.</p><blockquote><div id="listing-78"><span><a></a></span>&gt;&nbsp;getwd()&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;#&nbsp;get&nbsp;current&nbsp;working&nbsp;directory</div></blockquote><p>You can select a different working directory with the function&nbsp;<span>setwd()</span>, and thus avoid entering the full path of the data files.</p><blockquote><div id="listing-79"><span><a></a></span>&gt;&nbsp;setwd("")&nbsp;&nbsp;&nbsp;#&nbsp;set&nbsp;working&nbsp;directory</div></blockquote><p>Note that the forward slash should be used as the path separator even on Windows platform.</p><blockquote><div id="listing-80"><span><a></a></span>&gt;&nbsp;setwd("C:/MyDoc")</div></blockquote></div></div>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34504/minion-gc-an-r-script-to-do-some-qc-on-minion-data</guid>
	<pubDate>Sun, 03 Dec 2017 15:19:18 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34504/minion-gc-an-r-script-to-do-some-qc-on-minion-data</link>
	<title><![CDATA[MinION_GC: An R script to do some QC on MinION data]]></title>
	<description><![CDATA[<p><span>Other tools focus on getting data out of the fastq or fast5 files, which is slow and computationally intensive. The benefit of this approach is that it works on a single, small, .txt summary file. So it's a lot quicker than most other things out there: it takes about a minute to analyse a 4GB flowcell on my laptop.</span></p>
<p>https://github.com/roblanf/minion_qc</p><p>Address of the bookmark: <a href="https://github.com/roblanf/minion_qc" rel="nofollow">https://github.com/roblanf/minion_qc</a></p>]]></description>
	<dc:creator>Radha Agarkar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/36418/r-350-has-been-released</guid>
	<pubDate>Thu, 26 Apr 2018 11:31:58 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/36418/r-350-has-been-released</link>
	<title><![CDATA[R 3.5.0 has been Released!]]></title>
	<description><![CDATA[<ul>
<li>The latest version of R is a major release! It comes with a ton of new features, including performance and speed improvements</li>
<li>All R packages will now be byte-compiled, hence boosting packages installed from GitHub</li>
<li>You may need to re-install all previously installed R packages; old scripts however will continue to work normally</li>
</ul><p>More at&nbsp;<a href="https://cran.r-project.org/doc/manuals/r-release/NEWS.html">https://cran.r-project.org/doc/manuals/r-release/NEWS.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/22995/bioinformatics-phd-postdoc-job-rejection</guid>
	<pubDate>Thu, 02 Jul 2015 08:52:46 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/22995/bioinformatics-phd-postdoc-job-rejection</link>
	<title><![CDATA[Bioinformatics PhD / PostDoc / Job Rejection]]></title>
	<description><![CDATA[<div><p>While your PhD or PostDoc application, it is more common that you got rejected by many professors. Don't disappoint reply it calmly.</p><p><img src="http://bioinformaticsonline.com/mod/photo/rejected1.png" alt="image" style="border: 0px; border: 0px;"></p><p>In grad school, I shared a house with three Bioinformatics PhD students. One, when he applied to a particular professor, received a letter that said, essentially, "If you are applying because you want to enrich yourself, great. If you are applying because you want a job, you should know that you won't get one." I am trying to tell you this is because if you, with a good background in Bioinformatics, are passing up opportunities, you must be a strong candidate in many areas. Enrich yourself.<br /><br /> So, my suggestion is take a deep breath, forgot about all. Don&rsquo;t take it personally. It's been usual processes while hunting for a good lab and professor. Take is positive, I am not sure why they reject, but don't worry perhaps the lab don't deserve you. Always remember there are billions of reasons not to hire someone for projects, especially in a research sector.<br /><br /> My suggestion, please do not whine about how you were a great research candidate for the post, and you just can't understand why they were so stupid as to have rejected you! This feeling will not win you any points in research, community. Especially, when in todays socially connected era everyone is linked. Remember, a nice E-mail saying, "I really wished to working with you on this project and I hope we cross paths again," is all you need to send to the professor. Send a thank you note to the professor. Thank them for the time they spend to judge you. In the future, If you and the professor (of your dream) are attending a bioinformatics conference, invite him/her to lunch (please remember to pay the bill). In today evolving scientific ere, always remember to build your solid network in order to get a job of interest. Join all possible networking sites like LinkedIn, ResearchGate, Acamedia, FB for the same reason. You as a researcher always build a bridge with student/researcher/colleague/professor who have the research potential to lead in research and hire you. Just because you didn't get this project, doesn't mean there isn't another that will open up in couple of month.<br /><br /> Mostly, jobs that are hard to get are hard to get. Only you can decide if the continued sacrifices are worth the expected payout. If it is, keep on plowing. Build relationships. Attend conferences.</p><p>Image ref @ JaSonYa</p></div>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37732/making-2d-hilbert-curve</guid>
	<pubDate>Mon, 17 Sep 2018 05:43:35 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37732/making-2d-hilbert-curve</link>
	<title><![CDATA[Making 2D Hilbert Curve]]></title>
	<description><![CDATA[<p><a href="https://en.wikipedia.org/wiki/Hilbert_curve">Hilbert curve</a>&nbsp;is a type of space-filling curves that folds one dimensional axis into a two dimensional space, but still keeps the locality. It has advantages to visualize data with long axis in following two aspects:</p>
<ol>
<li>greatly improve resolution of the visualization fron n to&nbsp;<span><span><span><span><span><span><span>&radic;</span></span><span><span><span><span>n</span></span></span></span></span></span></span></span><span>n</span></span>;</li>
<li>easy to visualize clusters because generally data points in the axis will also be close in the 2D space.</li>
</ol>
<p>This package aims to provide an easy and flexible way to visualize data through Hilbert curve. The implementation and example figures are based on following sources:</p>
<ul>
<li><a href="http://mkweb.bcgsc.ca/hilbert/">http://mkweb.bcgsc.ca/hilbert/</a></li>
<li><a href="http://corte.si/posts/code/hilbert/portrait/index.html">http://corte.si/posts/code/hilbert/portrait/index.html</a></li>
<li><a href="http://bioconductor.org/packages/devel/bioc/html/HilbertVis.html">http://bioconductor.org/packages/devel/bioc/html/HilbertVis.html</a></li>
</ul><p>Address of the bookmark: <a href="https://bioconductor.org/packages/devel/bioc/vignettes/HilbertCurve/inst/doc/HilbertCurve.html" rel="nofollow">https://bioconductor.org/packages/devel/bioc/vignettes/HilbertCurve/inst/doc/HilbertCurve.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/23209/bisr-jaipur</guid>
  <pubDate>Tue, 07 Jul 2015 23:12:26 -0500</pubDate>
  <link></link>
  <title><![CDATA[BISR Jaipur]]></title>
  <description><![CDATA[
<p>The Bioinformatics Centre at BISR has created an infrastructure for providing facilities to the users working in the field of Biological Sciences. The users of Rajasthan, Jaipur in particular, are using facilities available at the Bioinformatics Centre extensively. The centre has leased line Internet connection as well latest Bioinformatics software for sequence and structure analysis. The centre provides the following services:</p>

<p>    Bioinformatics supports to researchers<br />    Customized training in Bioinformatics for researchers and faculty members<br />    Support in Installing, implementing and maintaining software on computer.<br />    Create awareness for taking preventive measure against data security<br />    Organize workshops on thrust ares of Bioinformatics<br />    Research Training to students of Biotechnology and Bioinformatics </p>

<p>More at http://bioinfo.bisr.res.in/index.php</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38420/regioner-an-r-package-for-the-management-and-comparison-of-genomic-regions</guid>
	<pubDate>Tue, 11 Dec 2018 08:43:51 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38420/regioner-an-r-package-for-the-management-and-comparison-of-genomic-regions</link>
	<title><![CDATA[regioneR: an R package for the management and comparison of genomic regions]]></title>
	<description><![CDATA[<p><span>Regioner is an R package for the management and comparison of genomic regions. It offers a set of function for basic manipulation of region sets extending the functionality of GenomicRanges and a powerful and customizable permutation test framework. With it, it's possible to study the association of a set of regions with other sets of regions, functions defined over the genome or essentially any user defined function.</span></p>
<p><span>http://gattaca.imppc.org/regioner/</span></p><p>Address of the bookmark: <a href="http://gattaca.imppc.org/regioner/" rel="nofollow">http://gattaca.imppc.org/regioner/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/23278/research-associate-project-fellow-biological-sciences-at-igib</guid>
  <pubDate>Sun, 12 Jul 2015 07:57:27 -0500</pubDate>
  <link></link>
  <title><![CDATA[Research Associate, Project Fellow (Biological Sciences) at IGIB]]></title>
  <description><![CDATA[
<p>Research Associate, Project Fellow (Biological Sciences)<br />Institute of Genomics &amp; Integrative Biology (IGIB) - New Delhi, Delhi<br />Pay Scale: Rs. 22,000/- + 30 % HRA per month<br />Educational Requirements: PhD in any branch of Biological Sciences with specialization in Bioinformatics with at least one research paper in Science Citation Indexed (SCI) journal<br />Desired Skills: Knowledge of molecular dynamics simulations<br />Details will be available at: http://www.igib.res.in/sites/default/files/24July2015.pdf</p>

<p>Project Fellow (Biological Sciences) Pay Scale: Rs. 16,000/- + 30 % HRA per month<br />Educational Requirements: M.Sc./B.Tech in life sciences/Biological sciences with at least 55 % marks<br />Experience Requirements: Research experience.<br />Details will be available at: http://www.igib.res.in/sites/default/files/24July2015.pdf</p>

<p>No of Post: 01<br />How To Apply: 1. Please fill up the proforma by clicking on the following link HR Online Form. 2. Candidate cannot apply for more than two posts. Last date of receiving application is 12-07-2015. No application would be entertained with “result awaited” status or after due date. List of shortlisted candidates will be put up on CSIR-IGIB website. No TA/DA will be paid to the candidates to attend the interview. The engagement shall be as per guidelines of CSIR/Funding agency. Candidates will have an option to give reply in Hindi. Note: The shortlisted candidates, have to report at 09:00 AM at Mall Road Campus, Delhi – 110007 on the day of interview along with any Photo ID card, (without photo ID card interview will not be conducted). 3 copies of updated signed C. V. (clearly mentioning Date of Birth and Highest Qualification with percentage), Dissertation (if any), PhD thesis (if any) and original certificates/Self attested photocopies for verification.<br />Detail of Interview: 24 July, 2015 at 10:30 AM<br />Age Limit: 28 Years</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39244/chromomap-an-r-package-for-interactive-visualization-and-annotation-of-chromosomes</guid>
	<pubDate>Fri, 12 Apr 2019 05:30:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39244/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>Provides interactive, configurable and elegant graphics visualization of the chromosomes or chromosome regions of any living organism allowing users to map chromosome elements (like genes, SNPs etc.) on the chromosome plot. It introduces a special plot viz. the "chromosome heatmap" that, in addition to mapping elements, can visualize the data associated with chromosome elements (like gene expression) in the form of heat colors which can be highly advantageous in the scientific interpretations and research work. The package provide multiple features like visualizing multiple sets, chromosome heat-maps, group annotations, adding hyperlinks, and labelling. The plots can be saved as HTML documents that can be customized and shared easily. In addition, you can include them in R Markdown or in R 'Shiny' applications.</p><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>Neel</dc:creator>
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