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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/44734?offset=1170</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38304/lordfast-sensitive-and-fast-alignment-search-tool-for-long-noisy-read-sequencing-data</guid>
	<pubDate>Tue, 27 Nov 2018 04:43:57 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38304/lordfast-sensitive-and-fast-alignment-search-tool-for-long-noisy-read-sequencing-data</link>
	<title><![CDATA[lordFAST: sensitive and Fast Alignment Search Tool for LOng noisy Read sequencing Data]]></title>
	<description><![CDATA[<p><span>lordFAST is a sensitive tool for mapping long reads with high error rates. lordFAST is specially designed for aligning reads from PacBio sequencing technology but provides the user the ability to change alignment parameters depending on the reads and application.</span></p>
<p>lordFAST, a novel long-read mapper that is specifically designed to align reads generated by PacBio and potentially other SMS technologies to a reference. lordFAST not only has higher sensitivity than the available alternatives, it is also among the fastest and has a very low memory footprint.</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://github.com/vpc-ccg/lordfast" rel="nofollow">https://github.com/vpc-ccg/lordfast</a></p>]]></description>
	<dc:creator>BioJoker</dc:creator>
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  <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>
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<item>
	<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/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/44557/fundamentals-of-data-visualization-by-claus-o-wilke</guid>
	<pubDate>Sat, 08 Jun 2024 16:07:19 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44557/fundamentals-of-data-visualization-by-claus-o-wilke</link>
	<title><![CDATA[Fundamentals of Data Visualization by Claus O. Wilke]]></title>
	<description><![CDATA[<p><span><span>The book is meant as a guide to making visualizations that accurately reflect the data, tell a story, and look professional. It has grown out of my experience of working with students and postdocs in my laboratory on thousands of data visualizations. Over the years, I have noticed that the same issues arise over and over. I have attempted to collect my accumulated knowledge from these interactions in the form of this book.</span></span></p>
<p><span>The entire book is written in R Markdown, using RStudio as my text editor and the&nbsp;</span><span>bookdown</span><span>&nbsp;package to turn a collection of markdown documents into a coherent whole. The book&rsquo;s source code is hosted on GitHub, at&nbsp;</span><a href="https://github.com/clauswilke/dataviz">https://github.com/clauswilke/dataviz</a><span>.&nbsp;</span></p><p>Address of the bookmark: <a href="https://clauswilke.com/dataviz/" rel="nofollow">https://clauswilke.com/dataviz/</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
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<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>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34172/orthodotter-synteny-plots-oxford-grid</guid>
	<pubDate>Wed, 09 Aug 2017 07:16:16 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34172/orthodotter-synteny-plots-oxford-grid</link>
	<title><![CDATA[orthodotter: Synteny plots (oxford grid)]]></title>
	<description><![CDATA[<pre><code>orthodotter -h
--------------------------------------------------------------------------------
orthodotter - Plot orthologous genes on an oxford grid.
       -f &lt;file&gt;     : input file, containing orthologous genes, default is stdin
                       species chr-name start end species chr-name start end
       -toPlot &lt;arg&gt; : give the x and y sets and the color separated by double-dots,
                       for example set1:set2:red will plot set1 on x, set2 on y with
                       red points. Could give several -toPlot arguments.
                       To launch the clustering of dots, use extra-option 1=dist,min_nb_genes
                       where dist is the minimal distance (euclidian) between two points and min_nb_genes the minimal
                       number of genes in a cluster to be valid.
       -o &lt;file&gt;     : output file, default is stdout
       -x &lt;int&gt;      : resolution of x axis, default is 600
       -y &lt;int&gt;      : resolution on y axis, default is 600
       -r &lt;int&gt;      : radius of circle representing orthologous genes
       -format       : could be png, gif, jpg, pdf or ps. Default is png.
       -fg           : foreground color, default is black
       -bg           : background color, default is transparent
       -fSize &lt;int&gt;  : fontSize, default is 1
       -filter       : check chromosome names
       -h            : help
--------------------------------------------------------------------------------
orthodotter -f Vigne_Banane.ortho -toPlot Vigne:Banane:black:1=10,5 -x 1200 -y 1200 -bg white -o Vigne_vs_Banane.png &gt; Vigne_vs_Banane.clusters
--------------------------------------------------------------------------------</code></pre><p>Address of the bookmark: <a href="https://github.com/institut-de-genomique/orthodotter" rel="nofollow">https://github.com/institut-de-genomique/orthodotter</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/8466/srf-position-in-computational-systems-biology-computational-biology-group-iiit-delhi</guid>
  <pubDate>Sun, 23 Feb 2014 20:56:08 -0600</pubDate>
  <link></link>
  <title><![CDATA[SRF position in Computational Systems Biology Computational biology Group, IIIT-Delhi]]></title>
  <description><![CDATA[
<p>An opportunity to perform research in DST supported project that involves building of mathematical models to understand the functional relationship between circadian rhythms and memory formation under stressful condition.  In this project, mathematical model of circadian rhythms based on gene regulatory mechanisms will be unified with the mathematical model of calcium signal transduction pathway to understand and predict the formation of fear memory under stressful conditions. The research scholar will spend full time on this project to build new models and expected to contribute significantly to prepare the results for publication and presentation, and to contribute to grant proposals. </p>

<p>Required Qualifications: Masters in physics/chemistry/mathematics (or) MTech in bioengineering, chemical (or) Masters in any traditional field of science with outstanding performance throughout the program. Candidate should have cleared GATE/UGC-CSIR examinations. Applicant should have done basic mathematics courses like calculus, differential equations, numerical analysis etc in their degree program and have obtained good grades in those courses. Knowledge of MATLAB and C or at least one traditional programming language is absolutely necessary. Strong inclination to understand biological concepts is a must for this research work as this project is about modeling biological systems.     </p>

<p>Salary: A fixed salary of Rs 18000 PM including HRA will be paid. </p>

<p>Last date for application: This advertisement is open until suitable candidate is found for the project. </p>

<p>Preferred Qualifications:  - Expertise in dynamical systems theory, bifurcation theory, numerical simulations, parameter estimation. </p>

<p>Independence and high motivation for carrying out interdisciplinary research. - Excellent communication skills and ability to work independently. - Good working habits. </p>

<p>Interested candidates should submit both curriculum vitae and statement of interest in PDF format to sriramk@iiitd.ac.in and should clearly mention in the subject "Application for SRF".</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44288/upset-plots</guid>
	<pubDate>Fri, 24 Mar 2023 22:30:23 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44288/upset-plots</link>
	<title><![CDATA[Upset plots !]]></title>
	<description><![CDATA[<p>Upset plots are a type of visualization used to analyze the intersection of sets or categories. They are particularly useful for displaying data with multiple categories and analyzing their overlaps.</p>
<p>In an upset plot, each row represents a category or set, and each column represents a data point. The length of the bar for each category indicates the number of data points that belong to that category. The plot also shows the intersections between categories, represented by overlapping bars.</p>
<p>Upset plots are useful for visualizing complex data with multiple categories and intersections, and can help identify patterns and relationships between categories. They are often used in fields such as bioinformatics, where they can be used to analyze gene expression data or to compare the results of different experimental conditions.</p>
<p>https://jokergoo.github.io/ComplexHeatmap-reference/book/upset-plot.html#example-with-the-genomic-regions</p><p>Address of the bookmark: <a href="https://jokergoo.github.io/ComplexHeatmap-reference/book/upset-plot.html#example-with-the-genomic-regions" rel="nofollow">https://jokergoo.github.io/ComplexHeatmap-reference/book/upset-plot.html#example-with-the-genomic-regions</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/12868/landry-lab</guid>
  <pubDate>Thu, 17 Jul 2014 14:33:57 -0500</pubDate>
  <link></link>
  <title><![CDATA[Landry Lab]]></title>
  <description><![CDATA[
<p>EVOLUTIONARY AND INTEGRATIVE CELL BIOLOGY</p>

<p>Our research is at the crossroad between cell biology, ecological genomics, systems biology, molecular evolution and population genetics. We study the architecture and evolution of protein and signalling networks.</p>

<p>More at http://landrylab.ibis.ulaval.ca/</p>
]]></description>
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