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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/13523?offset=820</link>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/852/queensland-centre-for-medical-genomics-grimmond-lab</guid>
  <pubDate>Sun, 14 Jul 2013 11:58:34 -0500</pubDate>
  <link></link>
  <title><![CDATA[Queensland Centre for Medical Genomics, Grimmond Lab]]></title>
  <description><![CDATA[
<p>Queensland Centre for Medical Genomics</p>

<p>Research Area:<br />pancreatic cancer; ovarian cancer; prostate cancer; bowel cancer; brain cancer; endometrial cancer; breast cancer; personalised medicine; high-throughput genomics</p>

<p>Link @ http://www.imb.uq.edu.au/sean-grimmond</p>
]]></description>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/4725/complex-systems-from-physics-to-biology-october-15-16-2013-at-jnu-convention-center</guid>
  <pubDate>Mon, 23 Sep 2013 10:17:17 -0500</pubDate>
  <link></link>
  <title><![CDATA[Complex Systems: From Physics to Biology October 15-16 2013 at JNU Convention Center]]></title>
  <description><![CDATA[
<p>The symposium intents to focus on complex systems arising in a variety of settings in physics and biology. In particular, applications of the concepts of physics to biological sciences will be the major theme of this meeting.</p>

<p>Selected Topics:</p>

<p>    Cluster Dynamics<br />    Non-equilibrium Statistical Mechanics<br />    Forced Systems<br />    Hamiltonian Dynamics<br />    Synchronization &amp; Control<br />    Genomics &amp; Systems Biology<br />    Computational Neuroscience<br />    Econophysics</p>

<p>More @ http://www.jnu.ac.in/Conference/SCS2013/</p>
]]></description>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/863/rolland-lagan-lab</guid>
  <pubDate>Sun, 14 Jul 2013 12:57:57 -0500</pubDate>
  <link></link>
  <title><![CDATA[Rolland-Lagan lab]]></title>
  <description><![CDATA[
<p>The Rolland-Lagan lab at the University of Ottawa is specializing in computational and developmental biology. We use a combination of experimental work, microscopy, image analysis and computer simulations to explore developmental mechanisms in two and three dimensions. </p>

<p>Research Area</p>

<p>Developmental biology, Computational biology, Simulation modeling, Image data analysis</p>

<p>Link @ http://mysite.science.uottawa.ca/arolland/index.html</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41872/autodock-vina-an-open-source-program-for-doing-molecular-docking</guid>
	<pubDate>Sat, 13 Jun 2020 07:55:56 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41872/autodock-vina-an-open-source-program-for-doing-molecular-docking</link>
	<title><![CDATA[AutoDock Vina: an open-source program for doing molecular docking.]]></title>
	<description><![CDATA[<p><span>AutoDock Vina is an open-source program for doing&nbsp;</span><a href="http://en.wikipedia.org/wiki/Docking_(molecular)">molecular docking</a><span>. It was designed and implemented by&nbsp;</span><a href="http://olegtrott.com/">Dr. Oleg Trott</a><span>&nbsp;in the Molecular Graphics Lab at The Scripps Research Institute.</span>&nbsp;It is especially effective for protein-ligand docking. AutoDock 4 is available under the GNU General Public License. AutoDock is one of the most cited docking software applications in the research community.</p>
<p><img src="http://vina.scripps.edu/img/accuracy.png" width="352" height="264" alt="image" style="border: 0px;"></p>
<p><a href="http://vina.scripps.edu/">http://vina.scripps.edu/</a></p><p>Address of the bookmark: <a href="http://vina.scripps.edu/" rel="nofollow">http://vina.scripps.edu/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/4209/enzyme-portal</guid>
	<pubDate>Tue, 03 Sep 2013 18:06:06 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/4209/enzyme-portal</link>
	<title><![CDATA[Enzyme Portal]]></title>
	<description><![CDATA[<p><span>Enzyme Portal-&nbsp;To look for information about the biology of a protein with enzymatic activity.</span></p>
<p><span>The enzyme portal integrates many resources, most of them hosted by EBI and also external ones such as BioPortal. Its main goal is to provide information about enzymes in a suitable format, with a usable interface designed for intended users. Instead of reinventing the wheel, it makes use of available and reliable resources to that end.</span></p>
<p><span><strong>Related Literature</strong>:</span></p>
<p><span><a href="http://nar.oxfordjournals.org/content/41/D1/D773.full">http://nar.oxfordjournals.org/content/41/D1/D773.full</a></span></p>
<p><span><a href="http://www.biomedcentral.com/1471-2105/14/103">http://www.biomedcentral.com/1471-2105/14/103</a></span></p><p>Address of the bookmark: <a href="http://www.ebi.ac.uk/enzymeportal/" rel="nofollow">http://www.ebi.ac.uk/enzymeportal/</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36026/mmseqs20-ultra-fast-and-sensitive-protein-search-and-clustering-suite</guid>
	<pubDate>Thu, 22 Mar 2018 10:40:51 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36026/mmseqs20-ultra-fast-and-sensitive-protein-search-and-clustering-suite</link>
	<title><![CDATA[MMseqs2.0: ultra fast and sensitive protein search and clustering suite]]></title>
	<description><![CDATA[<p>MMseqs2 (Many-against-Many sequence searching) is a software suite to search and cluster huge protein sequence sets. MMseqs2 is open source GPL-licensed software implemented in C++ for Linux, MacOS, and (as beta version, via cygwin) Windows. The software is designed to run on multiple cores and servers and exhibits very good scalability. MMseqs2 can run 10000 times faster than BLAST. At 100 times its speed it achieves almost the same sensitivity. It can perform profile searches with the same sensitivity as PSI-BLAST at over 400 times its speed.</p>
<p>The MMseqs2 user guide is available as&nbsp;<a href="https://github.com/soedinglab/mmseqs2/wiki">Github Wiki</a>&nbsp;or as&nbsp;<a href="https://mmseqs.com/latest/userguide.pdf">PDF file</a>&nbsp;(Thanks to&nbsp;<a href="https://github.com/jgm/pandoc">pandoc</a>!)</p>
<p>Please cite:&nbsp;<a href="https://www.nature.com/nbt/journal/vaop/ncurrent/full/nbt.3988.html">Steinegger M and Soeding J. MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets. Nature Biotechnology, doi: 10.1038/nbt.3988 (2017)</a>.</p><p>Address of the bookmark: <a href="https://github.com/soedinglab/MMseqs2" rel="nofollow">https://github.com/soedinglab/MMseqs2</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37965/kobas-a-web-server-for-geneprotein-functional-annotation-and-functional-gene-set-enrichment</guid>
	<pubDate>Fri, 19 Oct 2018 09:36:11 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37965/kobas-a-web-server-for-geneprotein-functional-annotation-and-functional-gene-set-enrichment</link>
	<title><![CDATA[KOBAS: a web server for gene/protein functional annotation and functional gene set enrichment]]></title>
	<description><![CDATA[<p><span>KOBAS 3.0 is a web server for gene/protein functional annotation (</span><a href="http://kobas.cbi.pku.edu.cn/annotate.php">Annotate</a><span>&nbsp;module) and functional gene set enrichment(Enrichment module). For Annotate module, it accepts gene list as input, including IDs or sequences, and generates annotations for each gene based on multiple databases about pathways, diseases, and Gene Ontology. For Enrichment module, it can accept either gene list or gene expression data as input, and generates enriched gene sets, corresponding name, p-value or a probability of enrichment and enrichment score based on results of multiple methods.</span></p><p>Address of the bookmark: <a href="http://kobas.cbi.pku.edu.cn/" rel="nofollow">http://kobas.cbi.pku.edu.cn/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/12111/internship-program-with-arraygen-technolgies</guid>
  <pubDate>Sun, 22 Jun 2014 23:18:31 -0500</pubDate>
  <link></link>
  <title><![CDATA[Internship program with ArrayGen Technolgies]]></title>
  <description><![CDATA[
<p>Internship Program for Bioinformatics / Biotechnology Professionals Currently we offer positions to outstanding students interested in Next Generation Sequencing (NGS) data analysis. Applications are accepted throughout the year. Accepted students will be listed on web with their schedules. Accepted students can attend our future workshops and trainings freely at the specified venue.</p>

<p>Interested candidates may email their resume along with a cover letter to careers@arraygen.com</p>

<p>Official website: http://www.arraygen.com/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42405/caretta-%E2%80%93-a-multiple-protein-structure-alignment-and-feature-extraction-suite</guid>
	<pubDate>Fri, 18 Dec 2020 02:09:44 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42405/caretta-%E2%80%93-a-multiple-protein-structure-alignment-and-feature-extraction-suite</link>
	<title><![CDATA[Caretta – A multiple protein structure alignment and feature extraction suite]]></title>
	<description><![CDATA[<h3>Caretta &ndash;&nbsp;a multiple protein structure alignment and feature extraction suite</h3>
<p><span>Caretta, a multiple structure alignment suite meant for homologous but sequentially divergent protein families which consistently returns accurate alignments with a higher coverage than current state-of-the-art tools. Caretta is available as a GUI and command-line application and additionally outputs an aligned structure feature matrix for a given set of input structures, which can readily be used in downstream steps for supervised or unsupervised machine learning.&nbsp;</span></p><p>Address of the bookmark: <a href="http://www.bioinformatics.nl/caretta/" rel="nofollow">http://www.bioinformatics.nl/caretta/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/4546/sowdhamini-lab</guid>
  <pubDate>Sun, 15 Sep 2013 09:19:12 -0500</pubDate>
  <link></link>
  <title><![CDATA[SOWDHAMINI Lab]]></title>
  <description><![CDATA[
<p>Genome sequencing projects have enormous potential for benefiting human endeavors. However, just as acquiring a language's vocabulary does not enable one to speak it, databases that list the amino acid composition of proteins do not directly tell us much about these proteins' higher-level structure and function. The most productive way to indirectly exploit these databases has been to start with the small number of proteins that are fully-characterised and to assume that other "similar" proteins will have a related structure and function. Proteins with very similar amino acid sequence are "no-brainers", but the real test, which our group largely focuses on, is to detect the "essential" similarity in proteins whose non-critical sections have experienced random rearrangements during evolution. In such cases functionally similar proteins may have less than 25% sequence overlap.</p>

<p>More @ http://www.ncbs.res.in/sowdhamini/groups_sowdhamini.htm</p>
]]></description>
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