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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/28199?offset=1590</link>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/45296/luo-lab-symbiosis-genomics-evolution</guid>
  <pubDate>Wed, 09 Sep 2026 03:30:30 -0500</pubDate>
  <link></link>
  <title><![CDATA[Luo Lab | Symbiosis Genomics &amp; Evolution]]></title>
  <description><![CDATA[
<p>We study the evolutionary genomics of marine invertebrates to understand their origins and diversity. Our lab combines high-throughput sequencing and single-cell transcriptomics to explore a wide range of non-model systems. We are particularly interested in how evolutionary novelty arises, with a focus on animal development and photosymbiosis.</p>

<p>Research Directions</p>

<p>Stony corals: evolution of novelty and photosymbiosis</p>

<p>Symbiotic acoels: cell type evolution and photosymbiosis</p>

<p>Animal genomes: structural evolution and gene regulation</p>

<p>https://sgel.biodiv.tw/home</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/poll/view/19921/which-of-the-followings-are-the-best-place-to-study-bioinformatics</guid>
	<pubDate>Sun, 28 Dec 2014 00:20:30 -0600</pubDate>
	<link>https://bioinformaticsonline.com/poll/view/19921/which-of-the-followings-are-the-best-place-to-study-bioinformatics</link>
	<title><![CDATA[Which of the followings are the best place to study Bioinformatics ?]]></title>
	<description><![CDATA[<p>Bioinformatics is a major growth area and qualified Bioinformaticians are in high demand. An explosion in biological data has resulted from genome projects, next generation sequencing and other 'omics' techniques. Bioinformatics provides the tools to analyse and exploit such data sets.<br /><br />Can you please suggest me the best place to study bioinformatics ( Grad/PostGrad).</p>]]></description>
	<dc:creator>Reshma Khatun</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/8481/des-higgins-visualizing-multiple-sequence-alignments</guid>
	<pubDate>Wed, 26 Feb 2014 00:50:08 -0600</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/8481/des-higgins-visualizing-multiple-sequence-alignments</link>
	<title><![CDATA[Des Higgins: Visualizing Multiple Sequence Alignments]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/IQkOK3dsWs4" frameborder="0" allowfullscreen></iframe>Copyright Broad Institute, 2013. All rights reserved.
Des Higgins (http://www.bioinf.ucd.ie) gives a very entertaining introduction to the visualization of multiple sequence alignment, and to his widely-used Clustal tool. He highlights the emerging challenge of managing alignments with a very large number of sequences, and presents several approaches to this challenge, including faster algorithms and abstract views of clusters of alignments. This talk was presented at VIZBI 2011, an international conference series on visualizing biological data (http://www.vizbi.org) funded by NIH & EMBO.

For information about data visualization efforts at the Broad Institute, please visit:
http://www.broadinstitute.org/node/1363/]]></description>
	
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/20007/roche-has-acquired-bina-technologies</guid>
	<pubDate>Tue, 30 Dec 2014 09:42:16 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/20007/roche-has-acquired-bina-technologies</link>
	<title><![CDATA[Roche has acquired Bina Technologies !!!]]></title>
	<description><![CDATA[<p>Bina Technologies is a privately held company that provides a big data platform for centralized management and processing of next generation sequencing (NGS) data for the academic and translational research markets.&nbsp; Bina will be integrated into the Roche Sequencing Unit, and will continue to focus on development of their innovative genomic analysis solution.<br /><br />Roche has acquired Bina Technologies, a privately-owned biotech company based in California. The biotech&rsquo;s first product was the Bina Box, a platform for secondary genomic analysis, sequence alignment, and variant calling, but since 2012, it has developed other products and platforms. <br /><br />It is our shared vision with Roche that informatics and data sciences are critical elements of an end-to-end genomics solution. Fast, easy-to-use, scalable, and robust informatics solutions make a big difference in the quality and impact of the work of scientists and researchers. We believe in the future of data-driven, personalized medicine. We are passionate about accelerating that future together with Roche.<br /><br />Financial details of the deal were not disclosed. For Roche, the move is yet another in a string of acquisitions. Last week (December 18), Roche paid $489 million for antibody maker Dutalys. And earlier this month, Roche bought prenatal testing company Ariosa Diagnostics.</p><p>Reference</p><p>http://blog.bina.com/news/bina-technologies-acquired-by-roche?&amp;__hssc=109677338.1.1419953400266&amp;__hstc=109677338.b8350f2729889b08f1325906d5236cd3.1419953400266.1419953400266.1419953400266.1&amp;hsCtaTracking=96cac941-9372-4bbf-bacb-3ca6f1ff8cfd|3fce0f18-835b-4086-9345-388880861732</p><p>http://www.the-scientist.com/?articles.view/articleNo/41750/title/Roche-Buys-Bioinformatics-Firm/</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<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>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/20331/type-hinting</guid>
	<pubDate>Fri, 09 Jan 2015 22:26:13 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/20331/type-hinting</link>
	<title><![CDATA[Type Hinting]]></title>
	<description><![CDATA[<p>Python creator Guido van Rossum&rsquo;s proposal for static type-checking annotations is inching closer to reality, and the feature has taken on a new name: type hinting.</p><p><img src="http://sdtimes.com/wp-content/uploads/2015/01/0107.sdt-python-typehinting.png" alt="image" width="619" height="219" style="border: 0px; border: 0px;"></p><p>Back in August, van Rossum published a proposal on the Python mailing list recommending type-checking annotations as a valuable feature for the next version of Python to improve the performance of editors and IDEs, linter capabilities, standard notation, and refactoring. Van Rossum&rsquo;s <a href="http://lwn.net/Articles/627558/">latest proposal</a>, posted late last month, outlined plans to publish a Python Enhancement Proposal (PEP) in early January to put the feature now known as type hinting on track for inclusion in Python 3.5, slated for release this September.</p><p>Reference</p><p>https://quip.com/r69HA9GhGa7J</p>]]></description>
	<dc:creator>Pranjali Yadav</dc:creator>
</item>
<item>
	<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/20363/postdoctoral-researcher-in-cancer-systems-biology</guid>
  <pubDate>Mon, 12 Jan 2015 01:44:11 -0600</pubDate>
  <link></link>
  <title><![CDATA[Postdoctoral Researcher in Cancer Systems Biology]]></title>
  <description><![CDATA[
<p>Postdoctoral Researcher in Cancer Systems Biology<br />Department of Oncology, Old Road Campus Research Building, Roosevelt Drive, Oxford<br />Grade 7: £30,434 - £37,394 with a discretionary range to £40,847 p.a.<br />Applications are invited for a Postdoctoral Researcher in Cancer Systems Biology to join a rapidly developing Bioinformatics Research Core group headed by Dr Anastasia Samsonova. The purpose of the role is to develop and deliver integrative approaches to dissect the complexity of cancer as a genomic disease. The research will focus on development and application of effective strategies for mining and integration of complex human *omics datasets and clinical/phenotypic data in cancer studies.</p>

<p>The role sits at the critical interface between genetics and cancer systems biology, and would suit a candidate who is interested in developing a career at the confluence of Statistics/Data Mining/Machine Learning and Biology. Ideally, you will have experience in development of analytical approaches to high-throughput and multivariate data mining and integration gained through a PhD (or equivalent) in a quantitative subject (eg mathematics, statistics, physics, engineering or computer science).</p>

<p>Experience of statistics and/or machine learning techniques is highly desirable as is evidence of prior experience of developing bioinformatics software and/or analysing complex *omics data sets. You will be able to work as part of a team and independently and deliver results to the required standard and schedule. You should be able to organise and prioritise your own work, as well as have excellent communication skills, both written and oral. The post will involve interactions with collaborators from such diverse fields as applied mathematics, statistics, computer science and medicine.</p>

<p>This is a full-time post, fixed-term until 31 March 2017. For informal enquiries, contact Dr Anastasia Samsonova (bioinformatics@oncology.ox.ac.uk).</p>

<p>All applicants must complete a short application form and upload a CV and supporting statement.</p>

<p>The closing date for applications is 12.00 noon on 26 January 2015.</p>

<p>More at https://www.recruit.ox.ac.uk/pls/hrisliverecruit/erq_jobspec_version_4.display_form</p>
]]></description>
</item>
<item>
	<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>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/20439/interactive-market-intelligence</guid>
	<pubDate>Mon, 19 Jan 2015 08:20:38 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/20439/interactive-market-intelligence</link>
	<title><![CDATA[Interactive Market Intelligence]]></title>
	<description><![CDATA[<p>BioInformatics LLC, a premier research and advisory firm serving the life science industry, has launched groundbreaking, dynamic-data presentation platform, Interactive Market Intelligence&mdash; the only cloud-based market research analytics tool for the life science tools industry.<br /><br />Superior to traditional PDF and PowerPoint reports, Interactive Market Intelligence allows end-users to filter, create and export literally thousands of views of data &mdash; all easily obtainable from a set of core metrics that include market, brand, customer and workflow analytics in well-defined segments of the life science market.<br /><br />The Market for Real-Time PCR is the first in a series of topics to be explored using the Interactive Market Intelligence platform. The primary research analysis is based on a survey of 900+ international scientists performing qPCR in their laboratories.<br /><br />Key data findings from "The Market for Real-Time PCR": Global market for qPCR in 2015 is estimated to be $3.6B; The average growth in qPCR throughput is expected to be at 9.8% in 2015; 22% of respondents are highly likely to switch primary suppliers of qPCR products; 50% of respondents use pre-designed primer/probe sets.</p>]]></description>
	<dc:creator>Pranjali Yadav</dc:creator>
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