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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/27235?offset=520</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43848/r-shiny-in-life-sciences-%E2%80%93-top-7-dashboard-examples</guid>
	<pubDate>Fri, 01 Apr 2022 19:05:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43848/r-shiny-in-life-sciences-%E2%80%93-top-7-dashboard-examples</link>
	<title><![CDATA[R Shiny in Life Sciences – Top 7 Dashboard Examples]]></title>
	<description><![CDATA[<p><span>&nbsp;R Shiny is one of the easiest ways for developers to make production-ready dashboards when speed and functionality are crucial. Shiny is approachable with a lot of documentation available, and because of this, a lot of developers/researchers with non-coding backgrounds are able to produce some impressive results. The whole ecosystem is easy to get your head around and pretty much limitless with regard to what you can do.</span></p><p>Address of the bookmark: <a href="https://www.r-bloggers.com/2022/03/r-shiny-in-life-sciences-top-7-dashboard-examples/" rel="nofollow">https://www.r-bloggers.com/2022/03/r-shiny-in-life-sciences-top-7-dashboard-examples/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/13025/the-5-reasons-to-mistakes-at-bioinformatics-work</guid>
	<pubDate>Thu, 24 Jul 2014 02:51:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/13025/the-5-reasons-to-mistakes-at-bioinformatics-work</link>
	<title><![CDATA[The 5 reasons to mistakes at bioinformatics work !!!]]></title>
	<description><![CDATA[<p>When you're just starting out with biological programming, it's easy to run into complex problems that make you wonder how anyone has ever managed to write a program. There are some problems that trip up nearly every bioinformatician--everything from getting started understanding the biological problems to dealing with program design. Some random mistakes are so prominent that even experienced biological programmers do it. The 8 years in bioinformatics and my few random observations, most of them are snarky. These reasons will always take longer than expected and compel you to postpone your project deadline.</p><p><strong>1.Stupid for biologist:</strong> Biology is so complex that it will make bioinformatician feel stupid. There are no any universal fixed rules; it can surprise you any time. So be nice to biologists who ask questions and resolve your biological puzzles. Sometime you will have no idea what the hell you were doing either.<br /><br /><strong>2.Puzzling why:</strong> Do not hesitate to ask question. Especially. at the beginning of project you will have to ask a lot of questions. Instead of puzzling it out at end check out and clear your doubt even for a single error. It may can leads to wrong conclusion.<br /><br /><strong>3.Running marathon:</strong> The most of the biological software&rsquo;s documentation is always incomplete. In other word they are no more than 95 percent complete. Sometime a single problem can halt your entire project for months. Compilation and running the pipelines in tedious because almost all are interdependent and need proper configuration. I face the same kind of problem with Evolver :( &hellip; <br /><br /><strong>4.Folders missing:</strong> The pipelines generate lots of data, and we keep them in several folders for future use. But sometime we delete them by mistake and move to recovery&hellip;<br /><br /><strong>5.Digging deeper:</strong> Digging deeper is fruitful, but some time it can be catastrophic. You may get frustrated or direction less. So keep a biologist with you for rescue &hellip;. Sometime an expert computer programmer to handle your server. Remember, the server will always go down when you need it the most.<br /><br />The most common frustrating&nbsp; common line: Why do we do this again?</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44487/r-package-for-pca-analysis</guid>
	<pubDate>Sun, 24 Mar 2024 20:06:24 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44487/r-package-for-pca-analysis</link>
	<title><![CDATA[R Package for PCA Analysis]]></title>
	<description><![CDATA[<p><span>An R package for performing principal component analysis (PCA) of genomics data. The package performs PCA, generates the publication-ready plots, and identifies population-specific outlier individuals. The package can be accessed on GitHub:&nbsp;https://github.com/Devashish13/PopulationStructure</span></p><p>Address of the bookmark: <a href="https://rpubs.com/Devashish13/PCAGenomics" rel="nofollow">https://rpubs.com/Devashish13/PCAGenomics</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/13337/phd-opportunity-at-universite-de-liege-belgium</guid>
  <pubDate>Sat, 02 Aug 2014 01:12:43 -0500</pubDate>
  <link></link>
  <title><![CDATA[PhD opportunity at Université de Liège - Belgium]]></title>
  <description><![CDATA[
<p>PhD opportunity at Université de Liège - Belgium</p>

<p>The Bioinformatics and Systems Biology Unit of Université de Liège (Belgium) is looking for a highly motivated master student with programming skills for a PhD thesis project (4 years, fully funded) with the goal of designing computational tools that use literature, genomic and structural data in order to infer regulatory and metabolic networks.  </p>

<p>Applicants are invited to send their resume and a recommendation letter to Prof. Patrick Meyer (more details at   www.biosys.ulg.ac.be )</p>

<p>For more information : www.biosys.ulg.ac.be</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/44364/genbank-release-2570-is-now-available</guid>
	<pubDate>Wed, 23 Aug 2023 00:23:23 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/44364/genbank-release-2570-is-now-available</link>
	<title><![CDATA[GenBank release 257.0 is now available!]]></title>
	<description><![CDATA[<p><span>GenBank release 257.0 is now available! This release has 25.10 trillion bases and 3.69 billion records. Learn more:&nbsp;https://ncbiinsights.ncbi.nlm.nih.gov/2023/08/21/genbank-release-257/</span><a href="https://ow.ly/zHbV50PBE5o"><br /></a></p><p><a href="https://www.ncbi.nlm.nih.gov/genbank/?utm_source=ncbi_insights&amp;utm_medium=referral&amp;utm_campaign=genbank-release-20230821">GenBank</a>&nbsp;release 257.0 (8/15/2023) is now available on the&nbsp;<a href="https://ftp.ncbi.nlm.nih.gov/genbank/">NCBI FTP site</a>. This release has 25.10 trillion bases and 3.69 billion records.</p><p><strong>The current release has:</strong></p><ul>
<li>246,119,175 traditional records containing 2,112,058,517,945 base pairs of sequence data</li>
<li>2,631,493,489 WGS records containing 22,294,446,104,543 base pairs of sequence data</li>
<li>686,271,945 bulk-oriented TSA records containing 646,176,166,908 base pairs of sequence data</li>
<li>124,421,006 bulk-oriented TLS records containing 48,289,699,026 base pairs of sequence data</li>
</ul>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/13523/megadock-40</guid>
	<pubDate>Thu, 07 Aug 2014 18:08:54 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/13523/megadock-40</link>
	<title><![CDATA[MEGADOCK 4.0]]></title>
	<description><![CDATA[<p>An ultra&ndash;high-performance protein&ndash;protein docking software for heterogeneous supercomputers</p>
<p id="p-4"><strong>Summary:</strong> The application of protein&ndash;protein docking in large-scale interactome analysis is a major challenge in structural bioinformatics and requires huge computing resources. In this work, we present MEGADOCK 4.0, an FFT-based docking software that makes extensive use of recent heterogeneous supercomputers and shows powerful, scalable performance of over 97% strong scaling.</p>
<p id="p-5"><strong>Availability and Implementation:</strong> MEGADOCK 4.0 is written in C++ with OpenMPI and NVIDIA CUDA 5.0 (or later) and is freely available to all academic and non-profit users at: <a href="http://www.bi.cs.titech.ac.jp/megadock">http://www.bi.cs.titech.ac.jp/megadock</a>.</p>
<p id="p-6"><strong>Contact:</strong> <a href="mailto:akiyama@cs.titech.ac.jp">akiyama@cs.titech.ac.jp</a></p><p>Address of the bookmark: <a href="http://bioinformatics.oxfordjournals.org/content/early/2014/08/06/bioinformatics.btu532.short" rel="nofollow">http://bioinformatics.oxfordjournals.org/content/early/2014/08/06/bioinformatics.btu532.short</a></p>]]></description>
	<dc:creator>Suleman Khan</dc:creator>
</item>
<item>
	<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>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/14756/roderic-guigo-lab</guid>
  <pubDate>Mon, 01 Sep 2014 17:13:00 -0500</pubDate>
  <link></link>
  <title><![CDATA[Roderic Guigó Lab]]></title>
  <description><![CDATA[
<p>Research in our group focuses on the investigation of the signals involved in gene specification in genomic sequences (promoter elements, splice sites, translation initiation sites, etc…). We are interested both in the mechanism of their recognition and processing, and in their evolution. In addition, but related to this basic component of our research, our group is also involved in the development of software for gene prediction and annotation in genomic sequences. Our group also actively participates in the analysis of many eukaryotic genomes and it in involved in the NIH-funded ENCODE project. Furthermore we are members of two large cancer-studies consortia (chronic lymphocytic leukemia "CLL" and Breast Cancer -Hospital del Mar/CRG/Roche-).  <br /> <br />More at http://big.crg.cat/computational_biology_of_rna_processing</p>
]]></description>
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<item>
  <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>
</item>
<item>
	<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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