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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/44279?offset=30</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44601/free-resources-to-learn-statistics</guid>
	<pubDate>Sat, 06 Jul 2024 10:30:50 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44601/free-resources-to-learn-statistics</link>
	<title><![CDATA[Free resources to learn statistics]]></title>
	<description><![CDATA[<p><span>Welcome to the course notes for&nbsp;</span><span>STAT 414: Introduction to Probability Theory</span><span>. These notes are designed and developed by Penn State's&nbsp;</span><a href="https://science.psu.edu/stat">Department of Statistics</a><span>&nbsp;and offered as open educational resources. These notes are free to use under Creative Commons license&nbsp;</span><a href="https://creativecommons.org/licenses/by-nc/4.0/">CC BY-NC 4.0</a><span>.</span></p>
<p>&nbsp;</p>
<p>A free online version of the second edition of the book based on Stat 110,&nbsp;<em>Introduction to Probability</em>&nbsp;by Joe Blitzstein and Jessica Hwang,&nbsp;is now available at&nbsp;<a href="http://probabilitybook.net/" title="http://probabilitybook.net">http://probabilitybook.net</a></p>
<p>Print copies are available via&nbsp;<a href="https://www.crcpress.com/Introduction-to-Probability-Second-Edition/Blitzstein-Hwang/p/book/9781138369917" title="">CRC Press</a>,&nbsp;<a href="https://amzn.to/2Ubh7D8" title="">Amazon</a>, and elsewhere.&nbsp;</p>
<p>Stat110x is also available as an&nbsp;edX course.&nbsp;Free signup at&nbsp;<a href="https://www.edx.org/course/introduction-to-probability-0" title="https://www.edx.org/course/introduction-to-probability-0">https://www.edx.org/course/introduction-to-probability-0</a></p>
<p>The edX course focuses on animations, interactive features, readings, and problem-solving, and&nbsp;is&nbsp;<strong>complementary</strong>&nbsp;to the Stat 110 lecture videos on YouTube, which are available at&nbsp;<a href="https://goo.gl/i7njSb" title="https://goo.gl/i7njSb">https://goo.gl/i7njSb</a></p>
<p>The Stat110x animations are available within the course and at&nbsp;<a href="https://goo.gl/g7pqTo" title="">https://goo.gl/g7pqTo</a></p>
<p><a href="https://projects.iq.harvard.edu/stat110/home">https://projects.iq.harvard.edu/stat110/home</a>&nbsp;</p><p>Address of the bookmark: <a href="https://online.stat.psu.edu/stat414/" rel="nofollow">https://online.stat.psu.edu/stat414/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/42811/bioinformatics-in-africa-part-4-morocco</guid>
	<pubDate>Sat, 06 Feb 2021 13:31:24 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/42811/bioinformatics-in-africa-part-4-morocco</link>
	<title><![CDATA[Bioinformatics in Africa: Part 4 - Morocco]]></title>
	<description><![CDATA[<p>Bioinformatics, in the UFR in Artificial Intelligence and Bioinformatics, deals with the management, the analysis, the modelling and the visualization of biological databases. Since the size of the databases is often exponential, the traditional algorithms are not very effective when seeking for a good computational solution.</p><p>To take care of this issue, many ways are opened to the researchers&nbsp;to&nbsp;improve&nbsp;the&nbsp;quality&nbsp;of&nbsp;the&nbsp;algorithms:</p><p>1. Usage of new information processing methods like artificial neuronal networks, genetic algorithms,&nbsp;etc. 2. Usage&nbsp;of&nbsp;Data&nbsp;mining&nbsp;&nbsp;to&nbsp;explore&nbsp;biochemical&nbsp;databases,<br />3. Usage of Machine learning on the biological examples to solve, for example, the problem of classification&nbsp;in&nbsp;Bioinformatics.</p><p>UFR&nbsp;offers&nbsp;in&nbsp;addition&nbsp;a&nbsp;doctoral&nbsp;training&nbsp;in&nbsp;Computer&nbsp;Science&nbsp;and&nbsp;Bioinformatics.</p><p>Doctoral&nbsp;module&nbsp;which&nbsp;includes:&nbsp;a&nbsp;Dipl&ocirc;me&nbsp;des&nbsp;Etudes&nbsp;Sup&eacute;rieures&nbsp;Approfondies&nbsp;(DESA)&nbsp; of&nbsp;two&nbsp;years;&nbsp;and&nbsp;a&nbsp;doctorate&nbsp;studies&nbsp;program&nbsp;with&nbsp;a&nbsp;national&nbsp;Ph.D.&nbsp;certification. Three&nbsp;specializations&nbsp;constitute&nbsp;the&nbsp;teaching&nbsp;trunk&nbsp;of&nbsp;the&nbsp;ENSAT:&nbsp;Computer&nbsp;engineering,&nbsp;Telecom&nbsp; engineering,&nbsp;and&nbsp;electronic&nbsp;systems&nbsp;engineering.</p><p>Research&nbsp;Interest&nbsp;and&nbsp;Activities:</p><p>The&nbsp;following&nbsp;are&nbsp;the&nbsp;present&nbsp;areas&nbsp;of&nbsp;research&nbsp;interest:</p><p>1. Machine&nbsp;Learning&nbsp;and&nbsp;Profile&nbsp;Gene&nbsp;Expression&nbsp;of&nbsp;Cancer<br />2. Predicting&nbsp;Protein&nbsp;structure <br />3. Hidden&nbsp;Markov&nbsp;Models&nbsp;(HMMs)&nbsp;and&nbsp;multiple&nbsp;alignments <br />4. Transformational&nbsp;Grammar&nbsp;for&nbsp;sequence&nbsp;modelling <br />5. Physical&nbsp;Mapping:&nbsp;STSs <br />6. Evolutionary&nbsp;Computation&nbsp;applied&nbsp;to&nbsp;Genomic&nbsp;and&nbsp;Proteomic <br />7. Predicate&nbsp;Logic&nbsp;and&nbsp;Protein&nbsp;Structure</p><p>Web&nbsp;site&nbsp;and&nbsp;links:</p><p>http://www.ensat.ac.ma/udiab http://www.pasteur.fr/pasteur/international/annonce_coursBioinfoannonce06_casa.pdf</p>]]></description>
	<dc:creator>BioStar</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/17176/arvados</guid>
	<pubDate>Sat, 20 Sep 2014 16:54:21 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/17176/arvados</link>
	<title><![CDATA[Arvados]]></title>
	<description><![CDATA[<p>Arvados is a free and open&nbsp;source bioinformatics&nbsp;platform for genomic and&nbsp;biomedical data. User can&nbsp;Store | Organize | Compute | Share the data for free.&nbsp;</p>
<p><img src="https://arvados.org/images/dax.png" width="400" height="535" alt="image" style="border: 0px;"></p><p>Address of the bookmark: <a href="https://arvados.org/" rel="nofollow">https://arvados.org/</a></p>]]></description>
	<dc:creator>Martin Jones</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/21703/coding-ground</guid>
	<pubDate>Tue, 17 Mar 2015 00:47:20 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/21703/coding-ground</link>
	<title><![CDATA[Coding Ground]]></title>
	<description><![CDATA[<p>Online coding group for most of the programming languages.</p>
<p>Code in almost all popular languages using Coding Ground.&nbsp;Edit, compile, execute and share your projects, 100% cloud.</p>
<p>http://www.tutorialspoint.com/codingground.htm</p><p>Address of the bookmark: <a href="http://www.tutorialspoint.com/codingground.htm" rel="nofollow">http://www.tutorialspoint.com/codingground.htm</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26539/scikit-learn</guid>
	<pubDate>Mon, 29 Feb 2016 17:39:24 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26539/scikit-learn</link>
	<title><![CDATA[scikit-learn]]></title>
	<description><![CDATA[<p>Machine Learning in Python</p>
<p>Simple and efficient tools for data mining and data analysis<br> Accessible to everybody, and reusable in various contexts<br> Built on NumPy, SciPy, and matplotlib<br> Open source, commercially usable - BSD license</p>
<p>More at&nbsp;http://scikit-learn.org/stable/index.html</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="http://scikit-learn.org/stable/auto_examples/index.html" rel="nofollow">http://scikit-learn.org/stable/auto_examples/index.html</a></p>]]></description>
	<dc:creator>Jitendra Prajapati</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27094/smash-an-alignment-free-method-to-find-and-visualise-rearrangements-between-pairs-of-dna-sequences</guid>
	<pubDate>Tue, 26 Apr 2016 12:18:49 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27094/smash-an-alignment-free-method-to-find-and-visualise-rearrangements-between-pairs-of-dna-sequences</link>
	<title><![CDATA[Smash: An alignment-free method to find and visualise rearrangements between pairs of DNA sequences]]></title>
	<description><![CDATA[<p><strong>Smash is a completely alignment-free method/tool to find and visualise genomic rearrangements</strong><span>. The detection is based on&nbsp;</span><strong>conditional exclusive compression</strong><span>, namely using a FCM (Markov model), of high context order (typically 20). For visualisation, Smash outputs a&nbsp;</span><strong>SVG image</strong><span>, with an&nbsp;</span><strong>ideogram</strong><span>output architecture, where the patterns are represented with several&nbsp;</span><strong>HSV values</strong><span>&nbsp;(only value varies). The method can perform both in small- and large-scale. Nevertheless is more directed to large-scale since that the main aim of the research is to&nbsp;</span><strong>know where the large-scale [chromosomal by chromosome] of several primates was equal/different, having at a glance a map of the entire genomes</strong><span>.</span></p><p>Address of the bookmark: <a href="http://bioinformatics.ua.pt/software/smash/" rel="nofollow">http://bioinformatics.ua.pt/software/smash/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/28564/dbt-%E2%80%93-bioinformatics-industrial-training-programme-biitp-2016-%E2%80%93-17</guid>
	<pubDate>Wed, 27 Jul 2016 04:09:59 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/28564/dbt-%E2%80%93-bioinformatics-industrial-training-programme-biitp-2016-%E2%80%93-17</link>
	<title><![CDATA[DBT – Bioinformatics Industrial Training Programme (BIITP) 2016 – 17]]></title>
	<description><![CDATA[<p>BIITP is a programme of Department of Biotechnology (DBT), Ministry of Science and Technology, Government of India, managed by Biotech Consortium India Limited (BCIL).The objective of BIITP is to provide an opportunity to bioinformatics students to acquire practical skills and experience by working on projects alongside industry experts as well as to provide an opportunity for the industry to identify potential employees.</p><p><strong>DBT Invites online applications from the bioinformatics&nbsp;students and requisitions from biotech/bioinformatics companies.</strong></p><p><strong>Biotech Industry</strong>&nbsp;:</p><p>Biotech/Bioinformatics companies interested to provide hands on industrial training to the students of Bioinformatics under BIITP may apply online. The companies would have no obligation towards any payments to trainees. The companies would be paid bench fee to cover expenses towards training. Trainees would be provided to companies subject to availability.</p><p><strong>Attn: Bioinformatics Students</strong></p><p>Bioinformatics students interested in training in biotech / bioinformatics companies may apply online.&nbsp;<strong>Stipend of Rs. 10,000/- per month</strong>&nbsp;will be paid to candidates placed for training. The candidates will be selected for training through an interview.</p><p><strong>Eligiblity</strong>&nbsp;:</p><p>a) B.E /B.Tech./M.Sc./M.Tech./Advanced Post Graduate Diploma in Bioinformatics from an Indian recognized university with minimum 55% marks or equivalent grade at highest degree/diploma completed in the year 2015 or 2016 are only eligible to apply.</p><p>b) The Advanced Post Graduate diploma should be of at least one year duration after graduation.</p><p>c)&nbsp; Students whose result of last semester/final year is not declared can also apply mentioning their marks upto the semester/year upto which result declared. The final result with original mark sheet(s) of all the semesters/years will have to be produced at the time of interview.</p><p><strong>Application Procedure</strong>&nbsp;:</p><p>The online application form is available below :</p><p><strong><a href="https://www.biotecnika.org/2016/07/dbt-bioinformatics-industrial-training-programme-biitp-2016-17/?xurl=%3A%2F%2Fwww.bcil.nic.in%2Fbiitp2016-17%2Fregistration1.asp" target="_blank">Application Form For Students (New User)</a></strong></p><p><strong><a href="https://www.biotecnika.org/2016/07/dbt-bioinformatics-industrial-training-programme-biitp-2016-17/?xurl=%3A%2F%2Fwww.bcil.nic.in%2Fbiitp2016-17%2Fregistration.asp%3FT1%3DCompany" target="_blank">Requisition form for companies (New User)</a></strong></p><p><strong><a href="https://www.biotecnika.org/2016/07/dbt-bioinformatics-industrial-training-programme-biitp-2016-17/?xurl=%3A%2F%2Fwww.bcil.nic.in%2Fbiitp2016-17%2Findex1.asp" target="_blank">Already registered User Click Here</a></strong></p><p>The following documents are to be sent to Mr. Manoj Gupta, Manager, Biotech Consortium India Limited, 5th floor, Anuvrat Bhawan, 210, Deen Dayal UpadhyayaMarg, New Delhi-110002.</p><p>More at&nbsp;http://www.bcil.nic.in/biitp2016-17/index.asp</p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/2253/best-practices-in-bioinformatics-training-for-life-scientists</guid>
	<pubDate>Tue, 13 Aug 2013 15:47:34 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/2253/best-practices-in-bioinformatics-training-for-life-scientists</link>
	<title><![CDATA[Best practices in bioinformatics training for life scientists]]></title>
	<description><![CDATA[<p>Among life scientists, from clinicians to environmental researchers, a common theme is the need not just to use, and gain familiarity with, bioinformatics tools and resources but also to understand their underlying fundamental theoretical and practical concepts.</p>
<p>Find the detail paper at http://bib.oxfordjournals.org/content/early/2013/06/25/bib.bbt043.full</p><p>Address of the bookmark: <a href="http://bib.oxfordjournals.org/content/early/2013/06/25/bib.bbt043.full" rel="nofollow">http://bib.oxfordjournals.org/content/early/2013/06/25/bib.bbt043.full</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/41905/research-associate-bioinformatics-in-iisc-recruitment-2020</guid>
  <pubDate>Tue, 23 Jun 2020 21:53:34 -0500</pubDate>
  <link></link>
  <title><![CDATA[Research Associate Bioinformatics in IISc Recruitment 2020]]></title>
  <description><![CDATA[
<p>Research Associate Bioinformatics in IISc Recruitment 2020</p>

<p>Essential Qualifications: Ph.D. (Bioinformatics/ Biophysics/ Biotechnology or any other stream of biological/ physical sciences) with a minimum of two publications in reputed peer reviewed journals in the area of structural bioinformatics or biophysics or biomolecular modeling/ simulation.</p>

<p>Job description: Development of bioinformatics tools and algorithms/software for structure based analysis of biomolecular systems. Programmatic access to major biomolecular databases using APIs Knowledge based prediction and analysis of biomolecular structure, function and interactions. Docking/simulations for inhibitor design.</p>

<p>Desirable Qualifications (Research Associate/s): i)  Strong computer programming skills (in Python/PERL/PHP or C++ or object oriented database management systems like MySQL etc or scripting languages under LINUX/UNIX environment). </p>

<p>ii) Extensive experience in computational analysis of biomolecular structure/interactions and usage of advanced biomolecular simulation softwares. iii) Adequate knowledge of major databases, webservers and softwares in the area of biomolecular structure/function and drug design. iv)  Familiarity with Parallel Programming environments and experience in usage of high-end HPC clusters.</p>

<p>The candidates must highlight their experience in above mentioned fields/topics in their CV. Initial appointment will be for a period of 1 year, subject to extension after review of performance.</p>

<p>Emoluments: As per DST, GOI norms and commensurate with experience.</p>

<p>More at https://www.iisc.ac.in/positions-open/</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42499/galaxy-training-resources</guid>
	<pubDate>Sun, 27 Dec 2020 05:28:07 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42499/galaxy-training-resources</link>
	<title><![CDATA[Galaxy Training Resources !]]></title>
	<description><![CDATA[<p>Welcome to Galaxy Training!</p>
<p>Collection of tutorials developed and maintained by the worldwide Galaxy community</p>
<table>
<thead>
<tr><th>Topic</th><th>Tutorials</th></tr>
</thead>
<tbody>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/introduction/">Introduction to Galaxy Analyses</a></td>
<td>10</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/assembly/">Assembly</a></td>
<td>6</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/climate/">Climate</a></td>
<td>3</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/computational-chemistry/">Computational chemistry</a></td>
<td>6</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/ecology/">Ecology</a></td>
<td>6</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/epigenetics/">Epigenetics</a></td>
<td>6</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/genome-annotation/">Genome Annotation</a></td>
<td>3</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/imaging/">Imaging</a></td>
<td>3</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/metabolomics/">Metabolomics</a></td>
<td>4</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/metagenomics/">Metagenomics</a></td>
<td>7</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/proteomics/">Proteomics</a></td>
<td>18</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/sequence-analysis/">Sequence analysis</a></td>
<td>2</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/statistics/">Statistics and machine learning</a></td>
<td>8</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/transcriptomics/">Transcriptomics</a></td>
<td>23</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/variant-analysis/">Variant Analysis</a></td>
<td>8</td>
</tr>
<tr>
<td><a href="https://training.galaxyproject.org/training-material/topics/visualisation/">Visualisation</a></td>
<td>2</td>
</tr>
</tbody>
</table>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://training.galaxyproject.org/training-material/" rel="nofollow">https://training.galaxyproject.org/training-material/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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