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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/28200?offset=1400</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38443/genoplotr-plot-gene-and-genome-maps-project</guid>
	<pubDate>Wed, 12 Dec 2018 08:33:41 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38443/genoplotr-plot-gene-and-genome-maps-project</link>
	<title><![CDATA[genoPlotR - plot gene and genome maps project!]]></title>
	<description><![CDATA[<p>genoPlotR is a R package to produce reproducible, publication-grade graphics of gene and genome maps. It allows the user to read from usual format such as protein table files and blast results, as well as home-made tabular files.</p>
<h3>Features</h3>
<ul>
<li>Linear representation of several segments of DNA</li>
<li>Comparisons represented by areas between the segments (like Artemis, for example)</li>
<li>Reads from common formats: Genbank, EMBL, blast, Mauve, and from user-generated tab files</li>
<li>Plot several subsegments of the same segment on the same line, separated by a //</li>
<li>Automatic or manual placement of the segments on the plot</li>
<li>Add annotations to all the lines</li>
<li>Create smart, automatic annotations for genomes, based on gene names</li>
<li>Add a user-generated tree</li>
<li>Add a global scale or a scale to each line</li>
<li>Use user-defined graphical functions to represent genes</li>
<li></li>
</ul><p>Address of the bookmark: <a href="http://genoplotr.r-forge.r-project.org/" rel="nofollow">http://genoplotr.r-forge.r-project.org/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/7913/the-genome-factory</guid>
	<pubDate>Thu, 16 Jan 2014 02:09:31 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/7913/the-genome-factory</link>
	<title><![CDATA[The genome factory !!!]]></title>
	<description><![CDATA[<p>Illumina, Inc. announced Tuesday that its new HiSeq X Ten Sequencing System has broken the &ldquo;sound barrier&rdquo; of human genomics by enabling the $1,000 genome. &ldquo;This platform includes dramatic technology breakthroughs that enable researchers to undertake studies of unprecedented scale by providing the throughput to sequence tens of thousands of human whole genomes in a single year in a single lab,&rdquo; Illumina stated.</p><p>Initial customers for the HiSeq X Ten System, which will ship in Q1 2014, include Macrogen, based in Seoul, South Korea and its CLIA laboratory in Rockville, Maryland, the Broad Institute in Cambridge, Massachusetts, and the Garvan Institute of Medical Research in Sydney, Australia.</p><p>&ldquo;For the first time, it looks like it will be possible to deliver the $1,000 genome, which is tremendously exciting,&rdquo; said Eric Lander, founding director of the Broad Institute and a professor of biology at MIT. &ldquo;The HiSeq X Ten should give us the ability to analyze complete genomic information from huge sample populations. Over the next few years, we have an opportunity to learn as much about the genetics of human disease as we have learned in the history of medicine.&rdquo;</p><p>&ldquo;The HiSeq X Ten is an ideal platform for scientists and institutions focused on the discovery of genotypic variation to enable a deeper understanding of human biology and genetic disease,&rdquo; Illumina stated. &ldquo;It can sequence tens of thousands of samples annually with high-quality, high-coverage sequencing, delivering a comprehensive catalog of human variation within and outside coding regions.&rdquo;</p><p>HiSeq X Ten utilizes a number of advanced design features to generate massive throughput. Patterned flow cells, which contain billions of nanowells at fixed locations, combined with a new clustering chemistry deliver a significant increase in data density (6 billion clusters per run). Using state-of-the art optics and faster chemistry, HiSeq X Ten can process sequencing flow cells more quickly than ever before &mdash; generating a 10x increase in daily throughput when compared to current HiSeq 2500 performance.</p><p>The HiSeq X Ten is sold as a set of 10 or more ultra-high throughput sequencing systems, each generating up to 1.8 terabases (Tb) of sequencing data in less than three days or up to 600 gigabases (Gb) per day, per system, providing the throughput to sequence tens of thousands of high-quality, high-coverage genomes per year. Illumina says the $1,000 includes typical instrument depreciation, DNA extraction, library preparation, and estimated labor.</p>]]></description>
	<dc:creator>Madhvan Reddy</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/7999/senior-research-fellow-indian-agricultural-statistics-research-institute</guid>
  <pubDate>Thu, 23 Jan 2014 06:22:15 -0600</pubDate>
  <link></link>
  <title><![CDATA[Senior Research Fellow @ Indian Agricultural Statistics Research Institute]]></title>
  <description><![CDATA[
<p>Indian Agricultural Statistics Research Institute<br />Library Avenue, Pusa, New Delhi – 110012</p>

<p>Walk-in-Interview</p>

<p>Walk-in-interview will be held on February 11, 2014 at 10:00 A.M. at IASRI, New Delhi for a project “Whole Genome Sequencing and Development of Allied Genomics Resources in Two Commercially Important Fish-Labeo rohita and Clarias batrachus” funded by Department of Biotechnology, Ministry of Science and Technology, Government of India, New Delhi for the following posts. The appointment will be on contractual basis upto September, 2016 or till the termination of the project whichever is earlier and the incumbent shall not have any claim for regular appointment under ICAR.</p>

<p>Senior Research Fellow Two</p>

<p>Post-Graduation in Bioinformatics/ Agricultural Statistics/ Statistics/ Computer Science/ Computer Application/ Biotechnology or equivalent with 1st Division</p>

<p> Knowledge of Statistical Analysis /Bioinformatics tools/computer programming for computational genomics.</p>

<p>Emoluments for Research Associate: Consolidated Rs: 16000/- per month + 30% HRA (1st Two years) and Rs: 18000/- per month + 30% HRA (3rd Year)</p>

<p>Age Limit: Age should be not more than 35 years (5 years relaxation for SC/ST/women candidates and 3 years for OBC candidates as on date of interview).<br />Interested candidates are requested to appear for Walk-in-Interview on the date and time as specified above in Room No. 106, Training Cum Administrative Block of the Institute along with their application giving bio-data with attested copies of certificates, degrees, testimonials, etc. and one passport size photograph. Original certificates/ Degrees are needed to be produced at the time of interview. No T.A. /D.A. will be paid for appearing in the interview.</p>

<p>Advertisement: http://www.iasri.res.in/employment/2014/srf_cabin.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39956/alluvial-diagram</guid>
	<pubDate>Sat, 21 Sep 2019 07:31:08 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39956/alluvial-diagram</link>
	<title><![CDATA[alluvial diagram]]></title>
	<description><![CDATA[<p><span style="color: #000000; font-size: 14px; font-style: normal; font-weight: 400; text-align: start; background-color: #ffffff; float: none;">Alluvial diagram is a variant of a Parallel Coordinates Plot (PCP) but for categorical variables. Variables are assigned to vertical axes that are parallel. Values are represented with blocks on each axis. Observations are represented with<span>&nbsp;</span></span><em style="color: #000000; font-size: 14px; font-weight: 400; text-align: start; background-color: #ffffff;">alluvia</em><span style="color: #000000; font-size: 14px; font-style: normal; font-weight: 400; text-align: start; background-color: #ffffff; float: none;"><span>&nbsp;</span>(sing. &ldquo;alluvium&rdquo;) spanning across all the axes.</span></p><p>Address of the bookmark: <a href="https://cran.r-project.org/web/packages/alluvial/vignettes/alluvial.html" rel="nofollow">https://cran.r-project.org/web/packages/alluvial/vignettes/alluvial.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/8108/jrf-institute-of-cytology-preventive-oncology</guid>
  <pubDate>Sat, 01 Feb 2014 13:47:29 -0600</pubDate>
  <link></link>
  <title><![CDATA[JRF @ Institute of Cytology &amp; Preventive Oncology]]></title>
  <description><![CDATA[
<p>Institute of Cytology &amp; Preventive Oncology (ICPO) which was initially established as Cytology Research Centre ( CRC ) by the Indian Council of Medical Research (ICMR) in 1979, came into the existence in 1989 when CRC was elevated to the level of Institute. ICPO was instituted with the main aim of promoting research in the field of cancers that are most prevalent in India with an emphasis on their early detection and prevention.</p>

<p>Candidates having the below mentioned qualifications may appear for Walk in Interview at ICPO on 5th Feb 2014 between 10.00 AM and 12.00 PM under the NIF project entitled "Prediction of drug tragets of chemical constituents present within non-codified medicinal plants" under Dr Subhash M.Agarwal, Scientist C</p>

<p>    Position : JRF<br />    No of Post : One<br />    Pay : Rs 12000/- + 30% HRA </p>

<p>    Desired Profile : M.Sc in Bioinformatics with good academic record. Candidate with experience in database development and scripting would be preferred<br />    Age Limit : Below 28 years<br />    Period : 2 months</p>

<p>Interested candidates may send their applications with bio-data by email (smagarwal@gmail.com) or post addressed to Dr Subhash M Agarwal, Scientist C, Bioinformatics Division, Institute of Cytology and Preventive Oncology (ICPO) I-7, Sector 39, Noida-201301 so as to reach latest by 04.02.14</p>

<p>Deadline : 04.02.14</p>

<p>http://icmr.nic.in/icmrnews/icpo_jrf.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40721/efs-an-ensemble-feature-selection-tool-implemented-as-r-package-and-web-application</guid>
	<pubDate>Tue, 28 Jan 2020 05:12:23 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40721/efs-an-ensemble-feature-selection-tool-implemented-as-r-package-and-web-application</link>
	<title><![CDATA[EFS: an ensemble feature selection tool implemented as R-package and web-application]]></title>
	<description><![CDATA[<p><span>The software EFS (Ensemble Feature Selection) makes use of multiple feature selection methods and combines their normalized outputs to a quantitative ensemble importance. Currently, eight different feature selection methods have been integrated in EFS, which can be used separately or combined in an ensemble.</span></p>
<p><a href="https://biodatamining.biomedcentral.com/articles/10.1186/s13040-017-0142-8">https://biodatamining.biomedcentral.com/articles/10.1186/s13040-017-0142-8</a></p><p>Address of the bookmark: <a href="http://efs.heiderlab.de/" rel="nofollow">http://efs.heiderlab.de/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/8385/peng-lab</guid>
  <pubDate>Tue, 18 Feb 2014 13:53:46 -0600</pubDate>
  <link></link>
  <title><![CDATA[Peng Lab]]></title>
  <description><![CDATA[
<p>Peng Lab at Janelia Farm Research Campus, Howard Hughes Medical Institute focuses on data mining for bioinformatics and computational molecular biology, particularly, bioimage data mining and informatics. These bioimages include cellular and molecular images and related medical images. </p>

<p>* Analysis of Gene Expression Pattern Images: high-performance image analysis and mining for different model organisms, such as fruitfly, C. elegans, and mouse;<br />* Feature/Model Learning: developing algorithms and software</p>

<p>Location :Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, USA.</p>

<p>http://research.janelia.org/peng/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41272/rainbowr-reliable-association-inference-by-optimizing-weights-with-r-r-package-for-snp-set-gwas-and-multi-kernel-mixed-model</guid>
	<pubDate>Fri, 28 Feb 2020 23:27:37 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41272/rainbowr-reliable-association-inference-by-optimizing-weights-with-r-r-package-for-snp-set-gwas-and-multi-kernel-mixed-model</link>
	<title><![CDATA[RAINBOWR: Reliable Association INference By Optimizing Weights with R (R package for SNP-set GWAS and multi-kernel mixed model)]]></title>
	<description><![CDATA[<p><code>RAINBOWR</code>(Reliable Association INference By Optimizing Weights with R) is a package to perform several types of <code>GWAS</code> as follows.</p>
<ul>
<li>Single-SNP GWAS with <code>RGWAS.normal</code> function</li>
<li>SNP-set (or gene set) GWAS with <code>RGWAS.multisnp</code> function (which tests multiple SNPs at the same time)</li>
<li>Check epistatic (SNP-set x SNP-set interaction) effects with <code>RGWAS.epistasis</code> (very slow and less reliable)</li>
</ul>
<p>https://github.com/KosukeHamazaki/RAINBOWR</p>
<p>https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1007663</p>
<p>https://cran.r-project.org/web/packages/RAINBOWR/index.html</p><p>Address of the bookmark: <a href="https://github.com/KosukeHamazaki/RAINBOWR" rel="nofollow">https://github.com/KosukeHamazaki/RAINBOWR</a></p>]]></description>
	<dc:creator>Surabhi Chaudhary</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/8442/assistant-professor-king-saud-university-riyadh</guid>
  <pubDate>Fri, 21 Feb 2014 05:57:18 -0600</pubDate>
  <link></link>
  <title><![CDATA[Assistant Professor @ King Saud University Riyadh]]></title>
  <description><![CDATA[
<p>Qualifications: Candidates must have a Ph.D. and a strong background in Molecular and Cellular Biology, protein expression, FACS, or computational biology, and ability to work collaboratively.</p>

<p>This position will have a significant focus on providing analytical support for next generation sequencing data analysis – Exome-sequencing, Targetted sequencing as well as high-throughput genotyping on Illumina platform.</p>

<p>Job location:</p>

<p>Genome Research Chair<br />King Saud University, Riyadh-11451<br />KSA</p>

<p>Interested candidate may forward their CV to grcksu@gmail.com</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42299/platypus-%E2%80%93-r-package-for-object-detection-and-image-segmentation</guid>
	<pubDate>Mon, 09 Nov 2020 02:56:25 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42299/platypus-%E2%80%93-r-package-for-object-detection-and-image-segmentation</link>
	<title><![CDATA[Platypus – R package for object detection and image segmentation.]]></title>
	<description><![CDATA[<p><a href="https://github.com/maju116/platypus" target="_blank">platypus</a>&nbsp;is an R package for object detection and semantic segmentation. Currently using&nbsp;</p>
<div>platypus&nbsp;you can perform:</div>
<ul>
<li>multi-class semantic segmentation using&nbsp;U-Net&nbsp;architecture</li>
<li>multi-class object detection using&nbsp;YOLOv3&nbsp;architecture</li>
</ul>
<p>You can install the latest version of&nbsp;platypus&nbsp;with&nbsp;remotes&nbsp;package:</p>
<div>
<div>
<div>
<div>remotes::install_github("maju116/platypus")</div>
</div>
</div>
</div>
<p>Note that in order to install&nbsp;platypus&nbsp;you need to install&nbsp;keras&nbsp;and&nbsp;tensorflow&nbsp;packages and&nbsp;Tensorflow&nbsp;version&nbsp;&gt;= 2.0.0&nbsp;(&nbsp;Tensorflow 1.x&nbsp;will not be supported!)</p><p>Address of the bookmark: <a href="https://github.com/maju116/platypus" rel="nofollow">https://github.com/maju116/platypus</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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