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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/19631?offset=1540</link>
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	<description><![CDATA[]]></description>
	
	
<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/4353/project-fellow-alagappa-university</guid>
  <pubDate>Sat, 07 Sep 2013 14:24:13 -0500</pubDate>
  <link></link>
  <title><![CDATA[Project Fellow @ Alagappa University]]></title>
  <description><![CDATA[
<p>Advertisement for the post of project Fellow in UGC project</p>

<p>Project Fellow – One Post</p>

<p>Duration: Three Years</p>

<p>Fellowship : Rs.14, 000/- per month + HRA</p>

<p>Walk-in-interview: 16th Sept, 2013 at 10.00 am</p>

<p>Venue : Department of Bioinformatics, Alagappa University</p>

<p>Eligible candidates can attend walk in interview for the post of Project Fellow in UGC supported project entitled “Shape and chemical feature based 3D- Pharmacophore Model generation, Virtual Screening and MESP studies to identify Potential Leads for Antifungal Azoles”</p>

<p>Interested candidates may apply to Dr. Sanjeev Kumar Singh, Principal Investigator, Department of Bioinformatics, Karaikudi with their Curriculum Vitae along with the copies of the certificates in proof of their educational qualification and experience at skysanjeev@gmail.com</p>

<p>Qualification:</p>

<p>PG Degree in Bioinformatics / Chemistry/ Molecular Biology/ Biotechnology / Biophysics / Biochemistry / Life Sciences/ Pharmacy with minimum of 55% marks in the PG examinations</p>

<p>Desirable:</p>

<p>Research experience in Molecular modeling and CADD will be given preference. UGC-NET/ CSIR-JRF qualified candidates will get preference.</p>

<p>The posts are purely on temporary basis. No TA/DA will be paid for attending the interview.</p>

<p>Advertisement: http://www.alagappauniversity.ac.in/files/news_files/new%20advt-UGC-16sept,13.doc</p>
]]></description>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/43262/bioinformatics-research-scientist-oklahoma-state-university-osu</guid>
  <pubDate>Tue, 17 Aug 2021 13:24:39 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics Research Scientist @ Oklahoma State University (OSU)]]></title>
  <description><![CDATA[
<p>This position is an early career research scientist in the area of Bioinformatics to support research projects involving faculty and staff, at Oklahoma State University (OSU). This is a highly technical position that requires a strong research background in biomedical or life sciences, including a high level of expertise with bioinformatics algorithms, databases, and analyses with a focus on next-generation sequence data. Although most of the projects will deal directly with the analysis of DNA and RNA sequence data the individual should be well versed in other types of data sources as well (i.e., microarrays) and handling of large datasets (using data analytics, machine learning, and deep learning techniques). </p>

<p>More at https://okstate.csod.com/ats/careersite/JobDetails.aspx?site=8&amp;id=9874</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43390/getting-started-with-nextflow</guid>
	<pubDate>Sat, 18 Sep 2021 01:28:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43390/getting-started-with-nextflow</link>
	<title><![CDATA[Getting Started with Nextflow]]></title>
	<description><![CDATA[<p>Introduction to Bioinformatics workflows with Nextflow and nf-core</p>
<p>Getting Started with Nextflow</p>
<p>Objectives Understand</p>
<p>What a workflow management system is.</p>
<p>Understand the benefits of using a workflow management system.</p>
<p>Explain the benefits of using Nextflow as part of your bioinformatics workflow.</p>
<p>Explain the components of a Nextflow script.</p>
<p>Run a Nextflow script.</p>
<h1 style="font-size: 36px; margin: 20px 0px 10px; font-weight: 500; text-align: center;"><a href="https://carpentries-incubator.github.io/workflows-nextflow/index.html">Introduction to Bioinformatics workflows with Nextflow and nf-core</a></h1>
<h1 id="getting-started-with-nextflow" style="font-size: 36px; margin: 20px 0px 10px; font-weight: 500; color: inherit; text-align: center;">Getting Started with Nextflow</h1><p>Address of the bookmark: <a href="https://carpentries-incubator.github.io/workflows-nextflow/aio/index.html" rel="nofollow">https://carpentries-incubator.github.io/workflows-nextflow/aio/index.html</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/4706/junior-research-fellow-iit</guid>
  <pubDate>Sat, 21 Sep 2013 18:04:50 -0500</pubDate>
  <link></link>
  <title><![CDATA[Junior Research Fellow @ IIT]]></title>
  <description><![CDATA[
<p>Applications are invited from the citizens of India for filling up the following temporary position for the sponsored project undertaken in the Department of Biosciences and Bioengineering of this Institute. The position is temporary initially for a period of  1 Year  and tenable only for the duration of the project. The requisite qualification &amp; experience etc. are given below:<br /> <br />Project Code, Project Title &amp; Funding Agency<br />13DST016 : "Studies on the component of mimivirus DNA replication machinery" (Department of Science &amp; Technology)<br /> <br />Position &amp; Salary	<br />Junior Research Fellow (1 Post )<br />Consolidated salary <br /> Rs.16000/- p.m. + HRA<br />Qualification	<br />MSc or MTech or BTech or BE in one of the following branches with first class-Biochemistry, Microbiology, genetic Engineering, Biotechnology, Medical Microbiology, Bioinformatics, life sciences etc.<br />Job Profile	<br />Project involves virus culturing and purification, cloning, protein purification and measurement of helicase, primase, nuclease, translocase activities using various methods. Person should be highly motivated and some experience in cloning and protein purification is desirable. Experience in handling insect cell lines will be an added advantage.</p>

<p>More at http://www.ircc.iitb.ac.in/IRCC-Webpage/rnd/RecruitmentGenerateCircular.jsp?srno=2013086</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44002/interesting-bioinformatics-resources</guid>
	<pubDate>Fri, 11 Nov 2022 06:30:46 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44002/interesting-bioinformatics-resources</link>
	<title><![CDATA[Interesting Bioinformatics Resources !]]></title>
	<description><![CDATA[<p>1. a reproducible workflow.&nbsp;<a href="https://www.youtube.com/watch?v=s3JldKoA0zw">https://www.youtube.com/watch?v=s3JldKoA0zw</a>&nbsp;This two minute video will change your mind on reproducible research&nbsp;</p><p>2. Parallel sequencing lives, or what makes large sequencing projects successful&nbsp;<a href="https://academic.oup.com/gigascience/article/6/11/gix100/4557140?login=false">https://academic.oup.com/gigascience/article/6/11/gix100/4557140?login=false</a></p><p>3. Common-sense approaches to sharing tabular data alongside publication&nbsp;<a href="https://www.sciencedirect.com/science/article/pii/S2666389921002300">https://www.sciencedirect.com/science/article/pii/S2666389921002300</a></p><p>4. A Reproducible Data Analysis Workflow with R Markdown, Git, Make, and Docker&nbsp;<a href="https://psyarxiv.com/8xzqy/">https://psyarxiv.com/8xzqy/</a></p><p>5. Practical Computational Reproducibility in the Life Sciences&nbsp;<a href="https://www.cell.com/cell-systems/fulltext/S2405-4712(18)30140-6">https://www.cell.com/cell-systems/fulltext/S2405-4712(18)30140-6</a></p><p>6. A video by Dr.Keith A. Baggerly from MD Anderson [The Importance of Reproducible Research in High-Throughput Biology](<a href="https://www.youtube.com/watch?v=7gYIs7uYbMo">https://www.youtube.com/watch?v=7gYIs7uYbMo</a>) highly recommended.</p><p>7. Ten Simple Rules for Reproducible Computational Research&nbsp;<a href="http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1003285">http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1003285</a>)</p><p>8. Good Enough Practices in Scientific Computing&nbsp;<a href="http://arxiv.org/abs/1609.00037">http://arxiv.org/abs/1609.00037</a>&nbsp;</p><p>9. Best Practices for Scientific Computing&nbsp;<a href="https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.1001745">https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.1001745</a></p><p>10. A Quick Guide to Organizing Computational Biology Projects&nbsp;<a href="http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.100042">http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.100042</a>&nbsp; A must read for computational biologists!</p><p>11. Reproducibility of computational workflows is automated using continuous analysis&nbsp;<a href="https://www.nature.com/articles/nbt.3780">https://www.nature.com/articles/nbt.3780</a></p><p>12. Five selfish reasons to work reproducibly&nbsp;<a href="https://genomebiology.biomedcentral.com/articles/10.1186/s13059-015-0850-7">https://genomebiology.biomedcentral.com/articles/10.1186/s13059-015-0850-7</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/4728/3-days-intensive-course-on-understanding-omics-data-in-basel-switzerland-19-21st-november</guid>
  <pubDate>Mon, 23 Sep 2013 10:46:57 -0500</pubDate>
  <link></link>
  <title><![CDATA[3 days intensive course on Understanding 'omics data in Basel, Switzerland, 19-21st November]]></title>
  <description><![CDATA[
<p>Benefits for the participants</p>

<p>- Plan more efficient experiments<br />- Correctly interpret results<br />- Communicate results in publications more effectively</p>

<p>The course focus is on methodologies, not on particular software tools. After the course participants should be able to apply the methods in their respective environment. However, during the course, hands-on sessions will be performed using the Genedata Expressionist® software, which enables participants to quickly apply the discussed methods and visualize results. No previous knowledge on Expressionist® is required; access to the software is free of charge during the course.</p>

<p>More @ http://www.dixa-fp7.eu/dixa-training/dixa-training-agenda/genedata-academy#!</p>
]]></description>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/44294/opportunity-at-mcdermott-center-bioinformatics-lab</guid>
  <pubDate>Sat, 01 Apr 2023 09:56:39 -0500</pubDate>
  <link></link>
  <title><![CDATA[Opportunity at McDermott Center Bioinformatics Lab]]></title>
  <description><![CDATA[
<p>Our team, composed of experts from diverse backgrounds including genetics, cancer biology, computer science, bioinformatics, and microbiology, stays current with evolving bioinformatics techniques. We offer consulting, customized service, and collaboration opportunities. We suggest visiting us to discuss your experiment design and results, as we can tailor our assistance to meet your specific research goals.</p>

<p>https://labs.utsouthwestern.edu/bioinformatics-lab/positions</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/5380/04-informatics-approach-to-cancer-interview-with-dr-joel-saltz</guid>
	<pubDate>Mon, 07 Oct 2013 14:35:43 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/5380/04-informatics-approach-to-cancer-interview-with-dr-joel-saltz</link>
	<title><![CDATA[04- Informatics Approach to Cancer - Interview with Dr. Joel Saltz]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/8Kf5EP4LY7k" frameborder="0" allowfullscreen></iframe>For additional information visit http://www.cancerquest.org/joel-saltz-interview.

Dr. Joel Saltz is a Professor in the Departments of Pathology, Biostatistics and Bioinformatics, and Mathematics and Computer Science at
Emory University. Dr. Saltz's research on bioinformatics spans several disciplines.  One project involves applying computer analysis to medical imaging to yield better results for patients.  As an example, a computer program may able to help doctors detect small cancers in a CT scan or mammogram. 

In this interview segment, Dr. Saltz  discusses the informatics approach to cancer.

To learn more about cancer and watch additional interviews, please visit the CancerQuest website at http://www.cancerquest.org.]]></description>
	
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44624/bioinformatics-workshops</guid>
	<pubDate>Wed, 31 Jul 2024 02:16:53 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44624/bioinformatics-workshops</link>
	<title><![CDATA[Bioinformatics Workshops !]]></title>
	<description><![CDATA[<p>When delving into bioinformatics, having access to reliable resources is crucial for effective research and analysis. Key online resources include the National Center for Biotechnology Information (NCBI), which offers tools like BLAST for sequence alignment and comprehensive gene databases. For presentations and educational materials, exploring SlideShare for introductory and advanced bioinformatics topics can provide valuable insights and learning aids.</p>
<p>https://evomics.org/2024-workshop-on-genomics/</p><p>Address of the bookmark: <a href="https://evomics.org/2024-workshop-on-genomics/" rel="nofollow">https://evomics.org/2024-workshop-on-genomics/</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/4959/evolution-and-cancer</guid>
	<pubDate>Fri, 27 Sep 2013 11:28:49 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/4959/evolution-and-cancer</link>
	<title><![CDATA[Evolution and Cancer]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/j3uKOcNwYBw" frameborder="0" allowfullscreen></iframe>Air date:  Wednesday, January 04, 2012, 3:00:00 PM
Time displayed is Eastern Time, Washington DC Local  
 
Category:  Wednesday Afternoon Lectures  
Description:  There is a broad consensus that cancer is the result of somatic cells having serially gained, by a series of mutations, the ability to grow independently, to recruit resources from the circulation and the stroma, to invade local tissues, and to found anatomically distant metastases, ultimately killing the host. From the point of view of the cancer-causing somatic cell population, this is evolution driven by mutation and selection. Genomics has resulted in a parallel consensus that the central functions of all eukaryotes are highly conserved, not only at the level of individual protein functions, but also complex biological pathways and systems. These ideas motivated a comparison between results of molecular genetic studies of experimental evolution in yeast and the molecular genetic phenomena associated with tumorigenesis and tumor progression. We find some very striking similarities, including recurring genomic rearrangements, alterations of the regulation of specific growth-promoting genes, population-genetic features that affect the fitness trajectories of growth rate variants in evolving populations, and physiological and metabolic similarities derived from the conservation of the basic plan of growth and cell multiplication among all eukaryotes. It is hoped that some of the insights from yeast will aid the interpretation of sequence changes found in tumors, especially in the urgent necessity to distinguish 'driver' from 'passenger' mutations." 

David Botstein's fundamental contributions to modern genetics include the development of genetic methods for understanding biological functions and the discovery of the functions of many yeast and bacterial genes. In 1980, Botstein and three colleagues proposed a method for mapping human genes that laid the groundwork for the Human Genome Project. The basic principle of the mapping scheme was to develop, by recombinant DNA techniques, random single-copy DNA probes capable of detecting DNA sequence polymorphisms when hybridized to restriction digests, or specific fragments, of an individual's DNA. The method was used in subsequent years to identify several human disease genes, such as Huntington's and BRCA1. Variations of this method enabled the sequencing phase of the Human Genome Project. 

In the 1990s Botstein, having moved to Stanford University School of Medicine, collaborated with Patrick O. Brown of Stanford in exploiting DNA microarrays to study genome-wide gene expression patterns in yeast and in human cancers. This required developing a new statistical method and graphical interface, widely used today to interpret genomic data. Botstein also has helped to create, with Michael Ashburner and Gerald Rubin, a bioinformatics initiative to unify the representation of gene and gene product attributes across all species, called Gene Ontology. He graduated from Harvard College and earned his doctorate from the University of Michigan. He worked at Massachusetts Institute of Technology from 1967 to 1988; served as vice president for science at Genentech from 1988 to 1990; chaired the Department of Genetics at the Stanford University School of Medicine from 1990 to 2003; and joined the Princeton University faculty in 2003. He has sat on numerous editorial boards and was the founding editor of Molecular Biology of the Cell. Among recent major awards, Bostein won the Peter Gruber Foundation Prize in Genetics in 2003, the Apple Science Innovator Award in 2008, and the Albany Medical Center Prize in 2010. 

The NIH Wednesday Afternoon Lecture Series includes weekly scientific talks by some of the top researchers in the biomedical sciences worldwide. 

For more information, visit: The NIH Director's Wednesday Afternoon Lecture Series  
Author:  Dr. David Botstein, Princeton University  
Runtime:  00:59:58  

Permanent link:  http://videocast.nih.gov/launch.asp?17046]]></description>
	
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