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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/10749?offset=400</link>
	<atom:link href="https://bioinformaticsonline.com/related/10749?offset=400" rel="self" type="application/rss+xml" />
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/14024/grapher</guid>
	<pubDate>Thu, 14 Aug 2014 14:02:17 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/14024/grapher</link>
	<title><![CDATA[GrapheR !!!]]></title>
	<description><![CDATA[<p>What a wonderful gem <em>GrapheR</em> is.... Oh yes it is. <em>GrapheR</em> is a GUI for base graphics in R by http://www.maximeherve.com/. The package provides a graphical user interface for creating base charts in R. It is ideal for beginners in R, as the user interface is very clear and the code is written along side into a text file, allowing users to recreate the charts directly in the console. <br /><br />Adding and changing legends? Messing around with the plotting window settings? It is much easier/quicker with this GUI than reading the help file and trying to understand the various parameters.<br />Here is a little example using the iris data set.<br /><br />library(GrapheR)<br />data(iris)<br />run.GrapheR()<br /><br />This will bring up a window that helps me to create the chart and tweak the various parameters.</p><p><img src="http://4.bp.blogspot.com/-NbnCM1dPh3E/U9aW9YxJ9oI/AAAAAAAABgo/gEPzPhOpf2Y/s1600/GrapheR.png" alt="image" width="878" height="868" style="border: 0px; border: 0px;"><br /><br />Finally, I find the underlying R code in a file created by <em>GrapheR</em>. For more details read also the <a href="http://cran.r-project.org/web/packages/GrapheR/index.html" target="_blank">package vignette</a>, which is available in <a href="http://cran.r-project.org/web/packages/GrapheR/vignettes/manual_en.pdf" target="_blank">English</a>, <a href="http://cran.r-project.org/web/packages/GrapheR/vignettes/manual_fr.pdf" target="_blank">French</a> and <a href="http://cran.r-project.org/web/packages/GrapheR/vignettes/manual_de.pdf" target="_blank">German</a>!</p>]]></description>
	<dc:creator>John Parker</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34515/metasim-a-sequencing-simulator-for-genomics-and-metagenomics</guid>
	<pubDate>Mon, 04 Dec 2017 07:18:20 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34515/metasim-a-sequencing-simulator-for-genomics-and-metagenomics</link>
	<title><![CDATA[MetaSim A Sequencing Simulator for Genomics and Metagenomics.]]></title>
	<description><![CDATA[<p><span>Our software can be used to&nbsp;</span><strong>generate collections of synthetic reads</strong><span>&nbsp;that reflect the diverse taxonomical composition of typical metagenome data sets. Based on a database of given genomes, the program allows the user to&nbsp;</span><strong>design a metagenome</strong><span>&nbsp;by specifying the number of genomes present at different levels of the NCBI taxonomy, and then to collect reads from the metagenome using a&nbsp;</span><strong>simulation of a number of different sequencing technologies</strong><span>. A population sampler optionally produces evolved sequences based on source genomes and a given evolutionary tree.&nbsp;</span></p><p>Address of the bookmark: <a href="http://ab.inf.uni-tuebingen.de/software/metasim/" rel="nofollow">http://ab.inf.uni-tuebingen.de/software/metasim/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/14186/pybedtools</guid>
	<pubDate>Wed, 20 Aug 2014 01:03:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/14186/pybedtools</link>
	<title><![CDATA[pybedtools]]></title>
	<description><![CDATA[<p>pybedtools is a Python wrapper for Aaron Quinlan's BEDtools programs (https://github.com/arq5x/bedtools), which are widely used for genomic interval manipulation or "genome algebra". pybedtools extends BEDTools by offering feature-level manipulations from with Python. See full online documentation, including installation instructions, at http://pythonhosted.org/pybedtools/.</p><p>More at http://pythonhosted.org/pybedtools/</p><p>A powerful toolset for genome arithmetic.http://code.google.com/p/bedtools/</p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/36647/bioinformatics-jobs-at-nibmg</guid>
  <pubDate>Wed, 16 May 2018 02:57:15 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics jobs at NIBMG]]></title>
  <description><![CDATA[
<p>NIBMG are looking for bright and motivated people in our big projects on cutting edge biomedical genomics research</p>

<p>http://www.nibmg.ac.in/academic/SyMeC-ICGC/SyMeC%20&amp;%20ICGC_May%202018.pdf</p>

<p>http://www.nibmg.ac.in/academic/plp/15_05_2018/AdvertisementMay2018.pdf</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/38815/research-opening-ibab-bengaluru</guid>
  <pubDate>Mon, 28 Jan 2019 17:45:54 -0600</pubDate>
  <link></link>
  <title><![CDATA[Research opening @ IBAB, Bengaluru]]></title>
  <description><![CDATA[
<p>Applications are invited for the position of Project Assistant in Bio-IT centre at IBAB, Electronic city, Bengaluru. The successful candidate will work in the next-generation sequencing (NGS) facility to perform nucleic acid isolations, quality and quantity analyses, NGS library preparations, and maintenance of sequencing related instruments and other related lab equipment. In addition, the candidate is expected to assist in various administrative matters including procurement, maintaining inventory of laboratory consumables etc. The person will have opportunity to get expertise in entire pipeline of NGS. After sufficient training, the person will act as a demonstrator in the workshops conducted by Bio-IT centre.<br />Essential Qualifications, Experiences, and Skills:</p>

<p>1. MSc. or B. Tech. or equivalent degree in Biotechnology or related life sciences discipline.<br />2. Strong aptitude for laboratory work and should be detail-oriented person.<br />3. Hands-on experience in basic molecular biology techniques.<br />4. Prior experience in working in a research laboratory or industry.<br />5. Basic IT skills that include familiarity with Microsoft Office packages.<br />6. Ability to carry out basic maintenance of general lab equipments and laboratory resources.<br />7. Ability to maintain accurate records of laboratory work.<br />8. Willingness to learn, and should be a team player.<br />Desirable Experience and Skills:<br />1. Familiarity with NGS technology.<br />2. Experience in preparation of NGS libraries.<br />3. Familiarity with Sanger sequencing technology (capillary electrophoresis based)</p>

<p>Remuneration: Remuneration will commensurate with expertise and experience.</p>

<p>How to Apply: Interested applicants fulfilling the criteria may send their detailed CV and a cover letter that explains their suitability for this position, in a single PDF, to Dr. Sreekanth Reddy at careers_bioit@ibab.ac.in. Last date for submission of application is 23rd February 2019. Please mention the position applying for in the subject line of the email.</p>

<p>About IBAB: The Bio-IT Centre at IBAB has state-of-art sequencing facility with the HiSeq 2500 and accessories such as Qubit, Covaris, Agilent 2200 TapeStation, Stratagene Mx 3000 for next generation sequencing, 3500 Dx Genetic Analyzer for capillary electrophoresis based sequencing, and HiScan for microarray imaging. The facility is fully operational and providing services to the scientific community. The Institute of Bioinformatics and Applied Biotechnology (IBAB) is a unique institute engaged in education, research and entrepreneur support programs and is based at Electronic City, Bangalore. IBAB’s mission is to catalyze the growth of the biotechnology and bioinformatics industries in India. To know more please visit: http://www.ibab.ac.in/index.php/bioit/</p>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/14904/bioinformatics-jrfsrf-position-at-iari</guid>
  <pubDate>Thu, 04 Sep 2014 04:14:01 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics JRF/SRF position at IARI]]></title>
  <description><![CDATA[
<p>DIVISION OF NEMATOLOGY<br />INDIAN AGRICULTURAL RESEARCH INSTITUTE<br />NEW DELHI 110012<br />Applications are invited for the posts of one Junior<br />Research Fellow and one RA in the DBT funded project entitled “ Plant parasitic nematode genome informatics - insilico resource development”. The project is for a period of three years. </p>

<p>Essential qualifications for JRF<br />: M. Sc. in Bioinformatics with experience in Proteomics, genomics and structural biology. Knowledge of programming language, pearl and database – HTML, CSS,php and Java script.<br />Essential qualifications for Research Associate:<br />MSc/MTech in Bioinformatics with three years experience or Ph.D in Bioinformatics with experience in proteomics, genomics and structural biology. Knowledge of programming language, perl and database<br />– HTML, CSS, Java script. NGS sequence assembly and analysis and algorithm designing.<br />Age limit : 35 years maximum (5 year relaxation for SC/ST and women candidates)<br />Emoluments:<br />JRF: 16,000 + 30% HRA<br />.<br />Res Assoc: Rs22,000 + 30% HRA<br />The post is purely temporary in nature and is co-terminus with the project. The appointment would be initially for one year and may be extended further upon satisfactory performance.<br />Interested candidates<br />should send the duly filled application forms (format in the following page ) so as to reach on or before 20.9.2014 along with all the relevant documents.</p>

<p>More at http://www.iari.res.in/files/JRF_RA-03092014-20140903-135319.pdf</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/42324/comparative-genomics-data-set-including-240-mammals-released</guid>
	<pubDate>Thu, 19 Nov 2020 06:45:39 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/42324/comparative-genomics-data-set-including-240-mammals-released</link>
	<title><![CDATA[Comparative Genomics Data Set Including 240 Mammals Released !]]></title>
	<description><![CDATA[<p>The genome of 130 mammals was sequenced by a large international consortium and the data was analyzed together with 110 existing genomes to allow scientists to identify the important positions in the DNA. This report, published in Nature today will help advance research on human disease mutations and inform how best to protect endangered species.</p><p>In addition to the knowledge of the human genome, all these genomes, widely sampled across mammals, can be used to research how particular organisms respond to different conditions. Some otters, for example, have a thick, water-resistant shell, and some rodents, but not all, have adapted to hibernation. These animal traits will help us to understand human traits, such as metabolic diseases.</p><p><img src="https://media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41586-020-2876-6/MediaObjects/41586_2020_2876_Fig1_HTML.png?as=webp" alt="image" style="border: 0px; border: 0px;"></p><p>With climate change and more animal ecosystems being threatened by human activity, the protection of endangered species is becoming increasingly important. Scientists have historically researched several people in various populations of a species to understand the genetic variation that occurs in that species. This is important for understanding how particular species can be protected. In this study, animals on the Red List of Endangered Species of the International Union for Conservation of Nature had fewer differences in their genomes, which is consistent with their endangered status.</p><p>Ref @&nbsp;A comparative genomics multitool for scientific discovery and conservation&nbsp;https://www.nature.com/articles/s41586-020-2876-6</p><p>&nbsp;Data at&nbsp;http://zoonomiaproject.org/</p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/poll/view/15000/which-mathstatistics-programming-languageapplication-do-you-most-frequently-use-in-bioinformatics</guid>
	<pubDate>Thu, 04 Sep 2014 17:46:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/poll/view/15000/which-mathstatistics-programming-languageapplication-do-you-most-frequently-use-in-bioinformatics</link>
	<title><![CDATA[Which math/statistics programming language/application do you most frequently use in bioinformatics?]]></title>
	<description><![CDATA[<p>I'm doing a bit more statistical analysis on some bioinformatics things lately, and I'm curious if there are any programming languages that are particularly good for this NGS computation. What suggestions do you guys have? Are there any languages that have exceptionally good libraries?</p>]]></description>
	<dc:creator>John Parker</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43362/machine-learning-for-genomics</guid>
	<pubDate>Thu, 09 Sep 2021 11:26:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43362/machine-learning-for-genomics</link>
	<title><![CDATA[Machine Learning for Genomics]]></title>
	<description><![CDATA[<h3>Module 1: Statistics for genomics (2-8 August 2021)</h3>
<ul>
<li>A simple intro to statistical distributions</li>
<li>hypothesis testing</li>
<li>linear models.</li>
</ul>
<p>reading:&nbsp;<a href="http://compgenomr.github.io/book/stats.html">http://compgenomr.github.io/book/stats.html</a></p>
<p>slides:&nbsp;<a href="https://github.com/BIMSBbioinfo/compgen2021/tree/main/week1/compgen2021_stats.pdf">https://github.com/BIMSBbioinfo/compgen2021/tree/main/week1/compgen2021_stats.pdf</a></p>
<p>exercises+code:&nbsp;<a href="https://github.com/BIMSBbioinfo/compgen2021/tree/main/week1/">https://github.com/BIMSBbioinfo/compgen2021/tree/main/week1/</a></p>
<h3><a href="https://github.com/BIMSBbioinfo/compgen2021#module-2-unsupervised-learning-for-genomics-9-15-august-2021"></a>Module 2: Unsupervised learning for genomics (9-15 August 2021)</h3>
<ul>
<li>Understanding basic intuition behind machine learning approaches.</li>
<li>Using unsupervised learning to cluster and visualise data points</li>
<li>Dimension reduction techniques for visualisation and as input to clustering methods</li>
</ul>
<p>reading:&nbsp;<a href="http://compgenomr.github.io/book/unsupervisedLearning.html">http://compgenomr.github.io/book/unsupervisedLearning.html</a></p>
<p>slides:&nbsp;<a href="https://github.com/BIMSBbioinfo/compgen2021/tree/main/week2/compgen2021_unsupervisedLearning.pdf">https://github.com/BIMSBbioinfo/compgen2021/tree/main/week2/compgen2021_unsupervisedLearning.pdf</a></p>
<p>exercises+code:&nbsp;<a href="https://github.com/BIMSBbioinfo/compgen2021/tree/main/week2/">https://github.com/BIMSBbioinfo/compgen2021/tree/main/week2/</a></p>
<h3><a href="https://github.com/BIMSBbioinfo/compgen2021#module-3-supervised-learning-for-genomics-16-22-august-2021"></a>Module 3: Supervised learning for genomics (16-22 August 2021)</h3>
<ul>
<li>Understanding and using supervised learning methods for predictive purposes</li>
<li>How to measure prediction performance</li>
<li>Understand and use cross-validation and related concepts</li>
</ul>
<p>reading:&nbsp;<a href="http://compgenomr.github.io/book/supervisedLearning.html">http://compgenomr.github.io/book/supervisedLearning.html</a></p>
<p>slides:&nbsp;<a href="https://github.com/BIMSBbioinfo/compgen2021/tree/main/week3/compgen2021_supervisedLearning.pdf">https://github.com/BIMSBbioinfo/compgen2021/tree/main/week3/compgen2021_supervisedLearning.pdf</a></p>
<p>exercises+code:&nbsp;<a href="https://github.com/BIMSBbioinfo/compgen2021/tree/main/week3/">https://github.com/BIMSBbioinfo/compgen2021/tree/main/week3/</a></p>
<p>https://github.com/BIMSBbioinfo/compgen2021</p><p>Address of the bookmark: <a href="https://github.com/BIMSBbioinfo/compgen2021" rel="nofollow">https://github.com/BIMSBbioinfo/compgen2021</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/17186/urdip-pune-bioinformatics-srfpa-openings</guid>
  <pubDate>Sat, 20 Sep 2014 20:48:50 -0500</pubDate>
  <link></link>
  <title><![CDATA[URDIP Pune Bioinformatics SRF/PA Openings]]></title>
  <description><![CDATA[
<p>CSIR UNIT FOR RESEARCH AND DEVELOPMENT OF INFORMATION PRODUCTS<br />NCL Campus, S.No.113,114, Pashan, Pune 411 008</p>

<p>ADVERTISEMENT NO. - URDIP/ 5/2014</p>

<p>Learning opportunity for young Science and Engineering professionals to make a career in Information Science Industry CSIR has set up a Unit for Research and Development of Information Products (CSIR-URDIP) at Pune to work in the area of Scientific Informatics (ChemBioinformatics/Patent Informatics/Phytoinformatics/Toxinformatics) and related<br />software development projects.</p>

<p>Applications are invited from CSIR - UGC NET Qualified Candidates for consideration as Project Fellow (PF) and/or Senior Project Fellow (SPF) based on the experience to work on existing and new projects at CSIRURDIP.</p>

<p>Project Fellow</p>

<p>    Remuneration - (Rs. 16,000.00 + 20% HRA)</p>

<p>    M. Sc. In Biochemistry/Microbiology/Bioinformatics [Post-code A02] only with minimum of 55% marks</p>

<p>Senior Project Fellow</p>

<p>    Remuneration - (Rs. 18,000.00 + 20% HRA)</p>

<p>    M. Sc. in Biochemistry/Microbiology/Bioinformatics [Post-code A05] only with minimum of 55% marks plus two years research or relevant informatics experience</p>

<p>Please visit www.urdip.res.in/career.htm to apply online by 30th September, 2014.</p>

<p>Successful candidates who have appeared for NET exam in 2012 and 2013 are only eligible to apply.</p>

<p>Advertisement: http://115.112.95.114/urhr/download/Advt5_2014.pdf</p>
]]></description>
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