<?xml version='1.0'?><rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:georss="http://www.georss.org/georss" xmlns:atom="http://www.w3.org/2005/Atom" >
<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/22807?offset=1190</link>
	<atom:link href="https://bioinformaticsonline.com/related/22807?offset=1190" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	
<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/4351/cpcri-kasaragod-bioinformatics-pa</guid>
  <pubDate>Sat, 07 Sep 2013 14:15:53 -0500</pubDate>
  <link></link>
  <title><![CDATA[CPCRI Kasaragod Bioinformatics PA]]></title>
  <description><![CDATA[
<p>CENTRAL PLANTATION CROPS RESEARCH INSTITUTE<br />(Indian Council of Agricultural Research)<br />KASARAGOD -671 124, KERALA</p>

<p>WALK-IN-INTERVIEW</p>

<p>Walk-in-test cum interview for selection to the following temporary assignments sanctioned under the DBT sponsored adhoc time bound research scheme entitled "Establishment of a Sub-DIC" will be held at CPCRl, Kudlu PO, Kasaragod District, Kerala -6711 24 on the date and time indicated against each:</p>

<p>Project Assistant</p>

<p>    Qualification: Essential: Masters Degree in Bioinformatics / B.Tech Degree in Bioinformatics</p>

<p>    Desirable: 1. Experience in the field of bioinformatics<br />    2. M.Phil / Doctoral degree in the field</p>

<p>    Date of interview 24.09.2013 at 10.00 a.m.</p>

<p>Trainee – 2 Posts</p>

<p>    Essential: Masters Degree in Bioinformatics or B.Tech Degree in Bioinformatics.</p>

<p>    Date of interview 25.09.2013 at 10.00 a.m.</p>

<p>Studentship – 2 Posts</p>

<p>    Essential Final Year/Semester students of MSc Bioinformatics or B.Tech Bioinformatics</p>

<p>    Date of Interview 25.09.2013 at 10.00 a.m.</p>

<p>The candidates fulfilling the above eligibility criteria for Item No.1 &amp; II shall apply online and walk-in for a written test and interview at CPCRI, Kasaragod on the respective dates at 10.00 a.m. The candidates for Studentship should submit the application through their Head of the Department. They shall also bring with them a set of bio data and original certificates in proof of age, educational qualifications, experience etc. Candidates who fail to produce the original of the Degree/PO certificates OR provisional certificate will not be allowed to attend the test / interview. Those who are qualified in written test will only be permitted to attend the interview.</p>

<p>No TA will be paid for the journey for attending the interview.</p>

<p>Advertisement: http://www.cpcri.gov.in/images/images/opportunity/sep4_opp.pdf</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/4654/la-trobe-university-melbourne-australia</guid>
  <pubDate>Fri, 20 Sep 2013 13:05:14 -0500</pubDate>
  <link></link>
  <title><![CDATA[La Trobe University, Melbourne, Australia]]></title>
  <description><![CDATA[
<p>La Trobe University, Melbourne, Australia</p>

<p>An exciting opportunity exists for a highly motivated and enthusiastic bioinformatics researcher to work in the Exosome, Secretome and Systems Biology laboratory of Dr Suresh Mathivanan. This position is funded through the National Institutes of Health (NIH) USA, to study the role of extracellular RNA or ExRNA in intercellular communication.</p>

<p>The successful applicant will be involved in collaborative bioinformatics research with more than 30 American Universities/Institutes.  The ExRNA consortium is a multi-institute USD 17 million funded program which has 5 primary aims: to understand the biogenesis of ExRNA (vesicles and non-vesicles), to explore the use of ExRNA in biomarker research, to establish a reference profile of ExRNA in various disease conditions, to explore the role of ExRNA in therapeutic purposes and to manage the generated data through a reference portal.  The bioinformatics component is critical in managing and analysing the data generated by the entire consortium.  The researcher is required to contribute to the management and perform the analysis of ExRNA data.</p>

<p>The candidate to succeed, you will possess:</p>

<p>Experience in the analysis and modelling of data, including the capacity to integrate data from a range of sources and of uneven quality.</p>

<p>Evidence of experience in research and of the ability to work effectively under limited supervision or independently.</p>

<p>A record of contribution to publications, conference papers and/or reports, or professional or technical contributions which provide evidence of research potential.</p>

<p>Completion of a doctoral degree in bioinformatics or biostatistics with a focus on transcriptomic data will be highly regarded.</p>

<p>Preference will be given to applicants with competence in programming (JavaScript, Perl/Python), any web-based applications (PHP, ZOPE) and relational databases (MySQL).</p>

<p>Closing date:  30 September 2013</p>

<p>Position Enquiries: Dr Suresh Mathivanan (s.mathivanan@latrobe.edu.au)</p>

<p>More at http://www.mathivananlab.org/</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/42953/ra-bioinformatics-at-sir-ganga-ram-hospital-new-delhi</guid>
  <pubDate>Sun, 14 Mar 2021 10:40:18 -0500</pubDate>
  <link></link>
  <title><![CDATA[RA Bioinformatics at Sir Ganga Ram Hospital, New Delhi]]></title>
  <description><![CDATA[
<p>Opportunities available at Institute of Medical Genetics &amp; Genomics, Sir Ganga Ram Hospital, New Delhi.</p>

<p>1) Senior Research Fellow under ICMR Project: M.Sc. (Life Sciences) with 2 years of experience (preferable in the field of Bioinformatics) or MBBS Degree.</p>

<p>2) Research Associate under ICMR Project: . Ph.D.(Life Science/Biotechnology/Bioinformatics) or equivalent degree or having 3 years of research, teaching and design and development experience after M.Tech with at least one research paper in science Citation Indexed (SCI) Journal.<br />Work experience in the area of Human genomics/Next Generation Sequencing data analysis/Big data genomics would be preferred.<br />Application link:</p>

<p>https://sgrh.com/joblist</p>

<p>Post Code: 2023, 2024</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/43341/nigerian-bioinformatics-and-genomics-network-nbgn</guid>
  <pubDate>Tue, 31 Aug 2021 08:29:40 -0500</pubDate>
  <link></link>
  <title><![CDATA[Nigerian Bioinformatics and Genomics Network (NBGN)]]></title>
  <description><![CDATA[
<p>This is to announce the second official conference of the Nigerian Bioinformatics and Genomics Network (NBGN). October 11-13,2021 at Landmark University, Omu-Aran, Kwara State and Zoom ( conference link to be announced soon</p>

<p>#NBGN21</p>

<p>www.nbgn21conference.com</p>
]]></description>
</item>
<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/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>

<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/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>
	
</item>
<item>
	<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/opportunity/view/44669/bioinformatician-at-qub-uk</guid>
  <pubDate>Tue, 01 Oct 2024 21:43:23 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatician at QUB, UK]]></title>
  <description><![CDATA[
<p>The post-holder will work under the direction of the Precision Medicine Centre of Excellence's (PMC) Bioinformatics lead and collaborate closely with the Scientific and Clinical leads. The primary responsibilities will be to develop, validate and maintain data analysis pipelines and algorithms that enable the comprehensive analysis of genomic information derived from cancer specimens, within the context of clinical studies. The PMC is an ISO 15189:2012 accredited medical laboratory (Ref 20634), providing an integrated cancer diagnostic and clinical research service that combines high throughput genomics and digital pathology (www.qub.ac.uk/research-centres/PMC).</p>

<p>About the person:</p>

<p>Essential criteria:</p>

<p>Hold or be about to obtain* a PhD in Computational biology, Bioinformatics, computing science or related subjects. (*must be obtained within 3 months of the closing date for the post) or MSc equivalent with at least 3 years' work experience in a relevant role.<br />Significant relevant research experience in genomics or work experience in a relevant technical/scientific role.<br />Significant experience in managing and analysing NGS data and other big data.<br />Experience in developing and maintaining analysis pipelines.<br />Experience working with Linux/UNIX environments.<br />Proficiency with python, bash, R and/or equivalent languages.<br />To be successful at shortlisting stage, please ensure you clearly evidence in your application how you meet the essential and, where applicable, desirable criteria listed in the Candidate Information document linked on our website.</p>

<p>More at https://hrwebapp.qub.ac.uk/tlive_webrecruitment/wrd/run/ETREC107GF.open</p>
]]></description>
</item>

</channel>
</rss>