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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/30203?offset=380</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40235/bioinformatics-web-development-course</guid>
	<pubDate>Wed, 06 Nov 2019 20:42:48 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40235/bioinformatics-web-development-course</link>
	<title><![CDATA[Bioinformatics web development course]]></title>
	<description><![CDATA[<p>This web development course, targeted at Biology and Bioinformatics students, aims at teaching from scratch all the skills needed to setup a fully working Linux web server and to develop and deploy web applications for Bioinformatics.</p>
<p>No previous programming knowledge is assumed. By following this tutorial you will learn the fundamental concepts of programming by using scripting languages: variables, types, arrays, cycles, conditional statements, functions, objects, regular expressions, files reading and manipulation et-cetera.</p><p>Address of the bookmark: <a href="http://www.cellbiol.com/bioinformatics_web_development/introduction/" rel="nofollow">http://www.cellbiol.com/bioinformatics_web_development/introduction/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/40945/the-clark-lab</guid>
  <pubDate>Fri, 07 Feb 2020 13:57:24 -0600</pubDate>
  <link></link>
  <title><![CDATA[The Clark Lab]]></title>
  <description><![CDATA[
<p>Study the process of Adaptive Evolution, during which species adopt novel traits to overcome challenges. We retrace the evolutionary histories of genomic elements to determine the changes underlying adaptation and to discover previously unknown genetic networks. These discoveries have already led to advances in human health, species conservation, and molecular biology. </p>

<p>More at http://clark.genetics.utah.edu/</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35920/mesquite-a-modular-system-for-evolutionary-analysis</guid>
	<pubDate>Tue, 13 Mar 2018 06:54:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35920/mesquite-a-modular-system-for-evolutionary-analysis</link>
	<title><![CDATA[Mesquite: A modular system for evolutionary analysis]]></title>
	<description><![CDATA[<p><span>Mesquite is modular, extendible software for evolutionary biology, designed to help biologists organize and analyze comparative data about organisms. Its emphasis is on phylogenetic analysis, but some of its modules concern population genetics, while others do non-phylogenetic multivariate analysis. Because it is modular, the analyses available depend on the modules installed.</span></p>
<p><span>https://github.com/MesquiteProject/MesquiteCore</span></p><p>Address of the bookmark: <a href="http://mesquiteproject.org/" rel="nofollow">http://mesquiteproject.org/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/42165/bioinformatics-scientistresearch-software-engineer-at-university-of-dundee-dundee-united-kingdom</guid>
  <pubDate>Wed, 26 Aug 2020 10:31:25 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics Scientist/Research Software Engineer at University of Dundee Dundee, United Kingdom]]></title>
  <description><![CDATA[
<p>We are recruiting for an exceptional individual to join us as a computational scientist, bioinformatician, or (research) software engineer with an interest in interactive data analysis platforms for biology and medicine within our Jalview (www.jalview.org) research software engineering team.</p>

<p>More at https://www.jobs.dundee.ac.uk/fe/tpl_uod01.asp?s=4A515F4E5A565B1A&amp;jobid=104342,2382988671&amp;key=147934117&amp;c=99413415238921&amp;pagestamp=sesxbbuyifokdsfygf</p>

<p>Last date: 30th August 2020</p>

<p>Informal enquiries about this position may be made to Prof. Geoff Barton (gjbarton@dundee.ac.uk) or Dr Jim Procter (jprocter@dundee.ac.uk). To find out more about Jalview research software engineering team please visit www.jalview.org and www.compbio.dundee.ac.uk</p>
]]></description>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/42227/two-faculty-positions-at-national-taiwan-university-taipei-taiwan</guid>
  <pubDate>Thu, 22 Oct 2020 04:53:12 -0500</pubDate>
  <link></link>
  <title><![CDATA[Two Faculty Positions at National Taiwan University, Taipei, Taiwan]]></title>
  <description><![CDATA[
<p>The Department of Agronomy at National Taiwan University, Taipei, Taiwan,<br />invites applications for two full-time faculty positions beginning August<br />1, 2021 at the rank of Assistant Professor, Associate Professor or<br />Professor in Biometry and Bioinformatics and Plant Breeding and Genetics,<br />respectively.</p>

<p>A qualified candidate should hold a Ph.D. in a relevant field including<br />Agronomy, Statistics, Bioinformatics, Plant Breeding, Plant Genetics or<br />Quantitative Genetics. For the position in Biometry and Bioinformatics, the<br />applicants capable of teaching fundamental statistics/bioinformatics<br />courses or with experience in crop science are preferable; for Plant<br />Breeding and Genetics, the applicants capable of teaching fundamental plant<br />breeding courses, with experience in crop breeding, or training in<br />quantitative genetics are preferred.</p>

<p>The application package should include two letters of reference and five<br />printed copies of the following documents (1) curriculum vitae, (2)<br />publication list, (3) undergraduate and graduate transcripts if applying<br />for the Assistant Professorship, (4) a photocopy of the Ph.D. diploma, (5)<br />teaching plan and course outline or syllabus (6) research proposal, (7) a<br />cover letter indicating the rank to apply, and one representative original<br />research article which was published by the applicant being the 1st or<br />corresponding author in an SCI peer-reviewed journal within 5 years (after<br />August 1, 2016); a copy of doctoral dissertation can be the representative<br />article if applying for the Assistant Professorship; (8) reprints of the<br />selected publications published within 7 years (after August 1, 2014).</p>

<p>The application package should mail to the Chair, Dr. Li-yu Daisy Liu<br />(lyliu@ntu.edu.tw), in the Department of Agronomy, National Taiwan<br />University, No. 1, Section 4, Roosevelt Road, Taipei 10617, Taiwan, before<br />December 15, 2020 for full consideration.</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41559/dahak-benchmarking-and-containerization-of-tools-for-analysis-of-complex-non-clinical-metagenomes</guid>
	<pubDate>Thu, 09 Apr 2020 04:56:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41559/dahak-benchmarking-and-containerization-of-tools-for-analysis-of-complex-non-clinical-metagenomes</link>
	<title><![CDATA[Dahak: benchmarking and containerization of tools for analysis of complex non-clinical metagenomes.]]></title>
	<description><![CDATA[<p><span>Dahak is a software suite that integrates state-of-the-art open source tools for metagenomic analyses. Tools in the dahak software suite will perform various steps in metagenomic analysis workflows including data pre-processing, metagenome assembly, taxonomic and functional classification, genome binning, and gene assignment. We aim to deliver the analytical framework as a robust and reliable containerized workflow system, which will be free from dependency, installation, and execution problems typically associated with other open-source bioinformatics solutions. This will maximize the transparency, data provenance (i.e., the process of tracing the origins of data and its movement through the workflow), and reproducibility.</span></p>
<p><span>More at&nbsp;<a href="https://dahak-metagenomics.github.io/dahak/">https://dahak-metagenomics.github.io/dahak/</a></span></p><p>Address of the bookmark: <a href="https://github.com/dahak-metagenomics/dahak" rel="nofollow">https://github.com/dahak-metagenomics/dahak</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42359/dnasp-dna-sequence-polymorphism-is-a-software-package-for-the-analysis-of-dna-polymorphisms</guid>
	<pubDate>Wed, 25 Nov 2020 19:51:38 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42359/dnasp-dna-sequence-polymorphism-is-a-software-package-for-the-analysis-of-dna-polymorphisms</link>
	<title><![CDATA[DnaSP: DNA Sequence Polymorphism, is a software package for the analysis of DNA polymorphisms]]></title>
	<description><![CDATA[<p><span>DnaSP, DNA Sequence Polymorphism, is a software package for the analysis of DNA polymorphisms using data from a single locus (a multiple sequence aligned -MSA data), or from several loci (a Multiple-MSA data, such as formats generated by some assembler RAD-seq software). DnaSP can estimate several measures of DNA sequence variation within and between populations in noncoding, synonymous or nonsynonymous sites, or in various sorts of codon positions), as well as linkage disequilibrium, recombination, gene flow and gene conversion parameters.</span></p><p>Address of the bookmark: <a href="http://www.ub.edu/dnasp/" rel="nofollow">http://www.ub.edu/dnasp/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42672/introduction-to-bioinformatics-and-computational-biology</guid>
	<pubDate>Mon, 25 Jan 2021 01:32:30 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42672/introduction-to-bioinformatics-and-computational-biology</link>
	<title><![CDATA[Introduction to Bioinformatics and Computational Biology]]></title>
	<description><![CDATA[<p><span>This is the course material for STAT115/215 BIO/BST282 at Harvard University.</span></p>
<p>Xiaole Shirley Liu (lead instructor)<br>Joshua Starmer<br>Martin Hemberg<br>Ting Wang<br>Feng Yue</p>
<p>Ming Tang<br>Yang Liu<br>Jack Kang<br>Scarlett Ge<br>Jiazhen Rong<br>Phillip Nicol<br>Maartin De Vries</p>
<p>We thank many colleagues in the community, who helped Dr.&nbsp;Liu in prepare the STAT115/215 BIO/BST282 course over the years.&nbsp;</p><p>Address of the bookmark: <a href="https://liulab-dfci.github.io/bioinfo-combio/" rel="nofollow">https://liulab-dfci.github.io/bioinfo-combio/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/42809/bioinformatics-in-africa-part2-kenya</guid>
	<pubDate>Sat, 06 Feb 2021 13:23:54 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/42809/bioinformatics-in-africa-part2-kenya</link>
	<title><![CDATA[Bioinformatics in Africa: Part2 - Kenya]]></title>
	<description><![CDATA[<p>International Livestock Research Institute (ILRI):</p><p>Under&nbsp; &nbsp;a&nbsp; &nbsp;NEPAD&nbsp; &nbsp;initiative,&nbsp; &nbsp;the&nbsp; &nbsp;Biosciences&nbsp; &nbsp;Eastern&nbsp; &nbsp;and&nbsp; &nbsp;Central&nbsp; &nbsp;Africa&nbsp; &nbsp;(BECA)&nbsp; (www.biosciencesafrica.org) was established at ILRI. BECA consists of a hub, regional nodes, and&nbsp; other affiliated laboratories and partner institutes. A state of the art joint Bioinformatics Platform&nbsp; (www.becabioinfo.org), whose overall goal is to provide a coherent and powerful bioinformatics&nbsp; infrastructure for use by all scientists in East and central Africa. The Platform goal requires both&nbsp; physical and intellectual developments that together provide researchers with access to diverse&nbsp; infrastructure in a wide&shy;area network, thereby addressing four important aspects of bioinformatics:&nbsp;</p><p>1) Science: bioinformatics tools for data integration and visualization, standardization of data&nbsp; formats and data analysis strategies, and distribution of analysis tasks over local&shy; and widearea networks are in development;&nbsp;</p><p>2)&nbsp; Bioinformatics Support Facility: provides assistance and custom programming to projects&nbsp; and those unable to establish a bioinformatics support function intrinsic to their project due&nbsp; to shortage of qualified personnel or lack of funding;&nbsp;</p><p>3) Hardware Platform: provide a powerful high performance computing platform capable of&nbsp; handling the largest analysis needs for projects;&nbsp;</p><p>4) Bioinformatics Training for East and central African scientists: While many Web&shy;based&nbsp; tools are available to the wet&shy;lab researcher, the Web is not well suited for tasks beyond&nbsp; single&shy;sequence annotation. Researchers need to become productive in a server&shy;based Unix&nbsp; environment with its wealth of scripting and automation tools. Even at an entry&shy;level, this&nbsp; can be an intimidating task if proper guidance is not available.</p><p>International&nbsp;Centre&nbsp;of&nbsp;Insect&nbsp;Physiology&nbsp;and&nbsp;Ecology&nbsp;(ICIPE): ICIPE&rsquo;s&nbsp;research&nbsp;focus&nbsp;is&nbsp;on&nbsp;insect&nbsp;biology,&nbsp;in&nbsp;order&nbsp;to&nbsp;improve&nbsp;the&nbsp;wellbeing&nbsp;of&nbsp;the&nbsp;peoples&nbsp;of&nbsp;the&nbsp; tropics&nbsp;through&nbsp;insect&nbsp;science.&nbsp;There&nbsp;is&nbsp;a&nbsp;commitment&nbsp;to&nbsp;utilise&nbsp;contemporary&nbsp;science&nbsp;in&nbsp;order&nbsp;to&nbsp; limit&nbsp;the&nbsp;impact&nbsp;of&nbsp;disease&nbsp;vectors,&nbsp;and&nbsp;agricultural&nbsp;pests.&nbsp;The&nbsp;understanding&nbsp;of&nbsp;the&nbsp;mechanisms&nbsp; associated&nbsp;with&nbsp;behaviour&nbsp;(e.g.&nbsp;attraction&nbsp;and&nbsp;repellency)&nbsp;is&nbsp;crucial.&nbsp;ICIPE&nbsp;seeks&nbsp;to&nbsp;enhance&nbsp;its&nbsp; bioinformatics&nbsp;capacity&nbsp;in&nbsp;order&nbsp;to&nbsp;support&nbsp;data&nbsp;from&nbsp;various&nbsp;EST&nbsp;projects&nbsp;designed&nbsp;to&nbsp;gain&nbsp;insights&nbsp; into&nbsp;the&nbsp;insect&nbsp;ecology&nbsp;and&nbsp;plant&nbsp;pathogen&nbsp;interactions&nbsp;though&nbsp;studies&nbsp;of&nbsp;metabolic&nbsp;pathways&nbsp; associated&nbsp;with&nbsp;production&nbsp;of&nbsp;all&nbsp;elochemicals.&nbsp;</p><p>Long&shy;term training activities:</p><p>Kenyatta University: An introductory course in Bioinformatics is offers to MSc Biotechnology&nbsp; students. This comprises of 35 hours of lectures and practicals.</p><p>University of Nairobi: A centre for Biotechnology and Bioinformatics (CEBIB), which will offer&nbsp; postgraduate training (diplomas, MSc and PhD) in areas of biotechnology and bioinformatics has&nbsp; recently been launched. Other universities in Kenya, including Egerton, Maseno and the Jomo Kenyatta University of&nbsp; Agriculture and Technology offer introductory courses to undergraduates in biomedical sciences. In addition, under the BECA platform MSc and PhD fellowships are being made available for&nbsp; Bioinformatics students. ILRI is forging links with Universities in South Africa and the United&nbsp; Kingdom to provide access to courses and training material.&nbsp;</p><p>Research Interest and Activities:</p><p>The following are the present areas of research interest: 1. EST clustering 2. Genome sequencing and annotation 3. Functional genomics and proteomics (including key tropical pathogens) 4. Structural bioinformatics 5. Development of Bioinformatics Data Management Systems 6. Gene Mining 7. High Throughput Genotyping 8. Microarray data management and analysis 9. Metagenomics 10. Immunoinformatics 11. Host&shy;pathogen interaction 12. High performance computing and grid development 13. Parasite transfection technologies 14. Cell cycle regulation 15. Population genetics 16. Vector genomics 17. Drug, vaccine and diagnostic target discovery</p><p>More at&nbsp;Web&nbsp;site&nbsp;and&nbsp;links:</p><p>http://www.ilri.cgiar.org/</p><p>http://www.icipe.org/ &nbsp; &nbsp;</p><p>http://www.uonbi.ac.ke/cebib</p>]]></description>
	<dc:creator>BioStar</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44257/calculate-the-significance-of-the-difference-between-two-trends</guid>
	<pubDate>Tue, 14 Mar 2023 05:41:53 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44257/calculate-the-significance-of-the-difference-between-two-trends</link>
	<title><![CDATA[Calculate the significance of the difference between two trends]]></title>
	<description><![CDATA[<div><div><div><div><div><div><div><div><div><div><p>To calculate the significance of the difference between two trends, you can use a statistical test such as a t-test or ANOVA (analysis of variance). Here are the general steps to follow:</p><ol>
<li>
<p>Define your null hypothesis (H0) and alternative hypothesis (H1). For example, H0 might be that there is no significant difference between the two trends, while H1 might be that there is a significant difference.</p>
</li>
<li>
<p>Collect data on the two trends. Make sure that the data is independent, normally distributed, and has equal variances.</p>
</li>
<li>
<p>Calculate the means and standard deviations of each trend.</p>
</li>
<li>
<p>Calculate the test statistic using a t-test or ANOVA. The test statistic will depend on the specific test you choose, but it will generally compare the difference in means between the two trends to the variability within each trend.</p>
</li>
<li>
<p>Determine the p-value associated with the test statistic. The p-value represents the probability of obtaining a test statistic as extreme as the one you calculated, assuming that the null hypothesis is true.</p>
</li>
<li>
<p>Compare the p-value to your chosen significance level (usually 0.05 or 0.01). If the p-value is less than or equal to the significance level, reject the null hypothesis and conclude that there is a significant difference between the two trends. If the p-value is greater than the significance level, fail to reject the null hypothesis and conclude that there is not enough evidence to support a significant difference.</p>
</li>
</ol><p>It's important to note that the specific details of each step will depend on the type of test you choose and the software you use to perform the analysis.</p><p>The most common methods for comparing means include:</p><table>
<thead>
<tr><th>Methods</th><th>R function</th><th>Description</th></tr>
</thead>
<tbody>
<tr>
<td>T-test</td>
<td>t.test()</td>
<td>Compare two groups (parametric)</td>
</tr>
<tr>
<td>Wilcoxon test</td>
<td>wilcox.test()</td>
<td>Compare two groups (non-parametric)</td>
</tr>
<tr>
<td>ANOVA</td>
<td>aov() or anova()</td>
<td>Compare multiple groups (parametric)</td>
</tr>
<tr>
<td>Kruskal-Wallis</td>
<td>kruskal.test()</td>
<td>Compare multiple groups (non-parametric)<br /><br /></td>
</tr>
</tbody>
</table></div></div></div></div></div></div></div></div></div></div>]]></description>
	<dc:creator>BioStar</dc:creator>
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