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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/29108?offset=1370</link>
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	<description><![CDATA[]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44516/16srna-database-download</guid>
	<pubDate>Wed, 24 Apr 2024 04:33:15 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44516/16srna-database-download</link>
	<title><![CDATA[16sRNA Database Download]]></title>
	<description><![CDATA[<p>Downloading 16S rRNA databases can be crucial for various bioinformatics analyses, especially in microbiome research. However, it's important to note that databases can vary based on your specific needs, such as the taxonomic coverage you require or the type of analysis you're performing. Here's a general guideline on how you can obtain 16S rRNA databases:</p><ol>
<li>
<p><span>NCBI (National Center for Biotechnology Information)</span>:</p>
<ul>
<li>NCBI provides various databases related to genetic information, including 16S rRNA sequences.</li>
<li>You can access the 16S ribosomal RNA sequences from NCBI's Nucleotide database (<a href="https://www.ncbi.nlm.nih.gov/nucleotide/" target="_new">https://www.ncbi.nlm.nih.gov/nucleotide/</a>).</li>
<li>Perform a search using keywords like "16S rRNA" or specific bacterial names to find relevant sequences.</li>
<li>You can download sequences individually or in batches using the provided tools.</li>
</ul>
</li>
<li>
<p><span>GreenGenes</span>:</p>
<ul>
<li>GreenGenes is a widely used 16S rRNA gene sequence database.</li>
<li>You can access it at <a target="_new">http://greengenes.secondgenome.com/</a>.</li>
<li>GreenGenes provides precompiled databases for various purposes, including classification, alignment, and phylogenetic analysis.</li>
</ul>
</li>
<li>
<p><span>SILVA</span>:</p>
<ul>
<li>SILVA (<a href="https://www.arb-silva.de/" target="_new">https://www.arb-silva.de/</a>) is another comprehensive database for ribosomal RNA (rRNA) sequences.</li>
<li>It covers not only 16S rRNA but also other ribosomal RNA sequences.</li>
<li>SILVA provides precompiled databases for various purposes, including taxonomic classification and alignment.</li>
</ul>
</li>
<li>
<p><span>Ribosomal Database Project (RDP)</span>:</p>
<ul>
<li>RDP (<a target="_new">http://rdp.cme.msu.edu/</a>) is a curated database that offers 16S rRNA sequences.</li>
<li>It provides tools for sequence analysis and classification.</li>
<li>You can download sequences and taxonomy information from their website.</li>
</ul>
</li>
<li>
<p><span>QIIME (Quantitative Insights Into Microbial Ecology)</span>:</p>
<ul>
<li>QIIME (<a href="https://qiime2.org/" target="_new">https://qiime2.org/</a>) is a widely used bioinformatics platform for microbiome analysis.</li>
<li>It provides tools for analyzing microbial communities, including processing 16S rRNA sequences.</li>
<li>QIIME often includes its own preprocessed 16S rRNA databases that can be used for analysis within the platform.</li>
</ul>
</li>
</ol><p>Before downloading any database, make sure to read the terms of use and citation requirements, as some databases may have specific usage policies. Additionally, consider the compatibility of the database with your analysis pipeline and software tools.</p><p>&nbsp;</p><p>NCBI 16s RNA database location&nbsp;ftp://ftp.ncbi.nih.gov/blast/db/16SMicrobial.tar.gz</p>]]></description>
	<dc:creator>LEGE</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>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/4288/new-born-babies-get-ready-to-know-their-whole-genome-soon</guid>
	<pubDate>Thu, 05 Sep 2013 07:24:02 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/4288/new-born-babies-get-ready-to-know-their-whole-genome-soon</link>
	<title><![CDATA[New born babies get ready to know their whole genome soon!!!]]></title>
	<description><![CDATA[<p>USA launch a pilot projects to examine medical information of newborn baby, which are being funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) and the National Human Genome Research Institute (NHGRI), both parts of the National Institutes of Health.</p><p>Awards of $5 million to four grantees have been made in fiscal year 2013 under the Genomic Sequencing and Newborn Screening Disorders research program. The program will be funded at $25 million over five years, as funds are made available.</p><p>"Hundreds of US babies will be pioneers in genomic medicine through a&nbsp;US$25-million programme to sequence their genomes&nbsp;soon after they are born."</p><p><strong>Source</strong>:</p><p><a href="http://blogs.nature.com/news/2013/09/scientists-to-sequence-hundreds-of-newborns-genomes.html">http://blogs.nature.com/news/2013/09/scientists-to-sequence-hundreds-of-newborns-genomes.html</a></p><p><a href="http://www.genome.gov/27554919">http://www.genome.gov/27554919</a></p>]]></description>
	<dc:creator>Rahul Agarwal</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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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33976/goldgenomes-online-database</guid>
	<pubDate>Wed, 26 Jul 2017 07:49:29 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33976/goldgenomes-online-database</link>
	<title><![CDATA[GOLD:Genomes Online Database]]></title>
	<description><![CDATA[<p><span>GOLD</span><span>:Genomes Online Database, is a World Wide Web resource for comprehensive access to information regarding genome and metagenome sequencing projects, and their associated metadata, around the world.</span></p>
<p>https://gold.jgi.doe.gov/</p><p>Address of the bookmark: <a href="https://gold.jgi.doe.gov/" rel="nofollow">https://gold.jgi.doe.gov/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/5253/pre-or-postdoctoral-research-fellowship-in-structural-bioinformatics-in-padova</guid>
  <pubDate>Wed, 02 Oct 2013 15:12:22 -0500</pubDate>
  <link></link>
  <title><![CDATA[Pre- or postdoctoral research fellowship in Structural Bioinformatics in Padova]]></title>
  <description><![CDATA[
<p>University of Padova (URL: http://protein.bio.unipd.it/)</p>

<p>A research fellowship is available at the BioComputing Laboratory, University of Padova (URL: http://protein.bio.unipd.it/). A highly motivated and creative candidate is sought to work on structural bioinformatics. Specifically, the project entails the development of novel methods, tools and databases for the analysis of protein structures. The BioComputing Laboratory is a group of a dozen people working on several aspects of prediction of protein structure &amp; function employing techniques at the intersection between biology, medicine, chemistry, physics &amp; computer science. Our aim is to integrate the development of novel methods and their application to biologically relevant problems. We are looking for candidates with a solid Bioinformatics background, programming experience (Python, Perl, C++ and/or Java) and good knowledge of molecular biology (protein structure/function, signalling pathways). Candidates should have a degree with top marks, optionally hold a PhD, and be highly motivated to work on interdisciplinary research. Good knowledge of English, an open-minded spirit, being collaborative and creative are crucial. The fellowship, which should start in late 2013, is initially for one year. It will be commensurate to experience, can be extended depending on performance and may lead to a PhD degree. The successful candidate will be located at the BioComputing Laboratory, University of Padova. Travel support for conferences and/or research visits abroad may be provided. To apply, please send your CV, a brief description of your research background and the names of two (or more) references to Prof. Silvio Tosatto (Email: silvio.tosatto@unipd.it). </p>

<p>Contact Person (Referent): Silvio Tosatto<br />Ref. E-Mail: silvio.tosatto@unipd.it<br />Tel: +39 049 827 6269<br />Fax: +39 049 827 6260<br />Group Web Page: http://protein.bio.unipd.it/</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34413/coursera-genome-assembly-tutorial</guid>
	<pubDate>Sat, 25 Nov 2017 08:57:25 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34413/coursera-genome-assembly-tutorial</link>
	<title><![CDATA[coursera genome assembly tutorial]]></title>
	<description><![CDATA[<p><span>Solutions to Coursera Genome Sequencing (Bioinformatics II)</span></p><p>Address of the bookmark: <a href="https://github.com/iansealy/coursera-assembly" rel="nofollow">https://github.com/iansealy/coursera-assembly</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/7217/contract-faculty-bioinformatics-at-maulana-azad-national-institute-of-technology</guid>
  <pubDate>Thu, 12 Dec 2013 20:46:52 -0600</pubDate>
  <link></link>
  <title><![CDATA[Contract Faculty-Bioinformatics at Maulana Azad National Institute of Technology]]></title>
  <description><![CDATA[
<p>Contract Faculty-Bioinformatics at Maulana Azad National Institute of Technology</p>

<p>Job Description:F.No.11/10(1)/929 Qualifications: Candidates should have Ph.D. degree. If Ph.D. candidates are not available at least Post Graduate degree with GATE/NET qualification is a must. Walk-in-Interview on 19.12.2013 at 2.30 P.M. to 5.30 P.M .. at Maulana Azad National Institute of Technology: Bhopal For more details,please visit website:http://www.manit.ac.in/manitbhopal/Year2013/Recruitment/Contract_faculty/contract%20faculty%202013-2014.pdf</p>

<p>For more @ http://www.manit.ac.in/manitbhopal/Year2013/Recruitment/Contract_faculty/contract%20faculty%202013-2014.pdf</p>

<p>Web address @ :http://www.manit.ac.in</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34528/cope-an-accurate-k-mer-based-pair-end-reads-connection-tool-to-facilitate-genome-assembly</guid>
	<pubDate>Wed, 06 Dec 2017 02:08:14 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34528/cope-an-accurate-k-mer-based-pair-end-reads-connection-tool-to-facilitate-genome-assembly</link>
	<title><![CDATA[COPE: an accurate k-mer-based pair-end reads connection tool to facilitate genome assembly]]></title>
	<description><![CDATA[<p><span>An efficient tool called Connecting Overlapped Pair-End (COPE) reads, to connect overlapping pair-end reads using k-mer frequencies. We evaluated our tool on 30&times; simulated pair-end reads from Arabidopsis thaliana with 1% base error. COPE connected over 99% of reads with 98.8% accuracy, which is, respectively, 10 and 2% higher than the recently published tool FLASH. When COPE is applied to real reads for genome assembly, the resulting contigs are found to have fewer errors and give a 14-fold improvement in the N50 measurement when compared with the contigs produced using unconnected reads.</span></p><p>Address of the bookmark: <a href="ftp://ftp.genomics.org.cn/pub/cope" rel="nofollow">ftp://ftp.genomics.org.cn/pub/cope</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/5623/yau-group</guid>
  <pubDate>Tue, 15 Oct 2013 13:05:15 -0500</pubDate>
  <link></link>
  <title><![CDATA[Yau Group]]></title>
  <description><![CDATA[
<p>Yau Group are a new research group based at the Wellcome Trust Centre for Human Genetics and the Department of Statistics at the University of Oxford.</p>

<p>Yau Group develops statistical and computational methods for the analysis of genomic datasets with a particular interest in cancer sequencing applications and the use of Bayesian Statistics.</p>

<p>Yau Group are currently have projects in somatic mutation analysis of heterogeneous cancers, data fusion or integration techniques and single cell genomics.</p>

<p>More @ http://www.well.ox.ac.uk/~cyau/index.html</p>
]]></description>
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