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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/31345?offset=630</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38208/anitools-web-a-web-tool-for-fast-genome-comparison-within-multiple-bacterial-strains</guid>
	<pubDate>Wed, 14 Nov 2018 04:34:23 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38208/anitools-web-a-web-tool-for-fast-genome-comparison-within-multiple-bacterial-strains</link>
	<title><![CDATA[ANItools web: a web tool for fast genome comparison within multiple bacterial strains]]></title>
	<description><![CDATA[<p><span>ANItools is a software package written by PERL scripts that can be run in a Linux/Unix system. If you want to compare bacterial genomes and calculate their average nucleotide identity (ANI), you could download and run this program directly. Or you could send us the genome sequence by email. Then we will do the analysis work for you.</span></p>
<p><span>https://academic.oup.com/database/article/doi/10.1093/database/baw084/2630454</span></p><p>Address of the bookmark: <a href="http://ani.mypathogen.cn/" rel="nofollow">http://ani.mypathogen.cn/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/4636/molecular-and-computational-biology-research-school</guid>
  <pubDate>Fri, 20 Sep 2013 09:01:18 -0500</pubDate>
  <link></link>
  <title><![CDATA[Molecular and Computational Biology Research School]]></title>
  <description><![CDATA[
<p>The ambition of the Molecular and Computational Biology Research School (MCB) is to create an attractive and stimulating training environment for PhD students in molecular and computational biology, both to better serve the needs for relevant training in the field, and to stimulate crossdiscipline developments in the research of the parties.</p>

<p>http://www.uib.no/rs/mcb</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38475/purge-haplotigs-pipeline-to-help-with-curating-heterozygous-diploid-genome-assemblies</guid>
	<pubDate>Mon, 17 Dec 2018 03:17:20 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38475/purge-haplotigs-pipeline-to-help-with-curating-heterozygous-diploid-genome-assemblies</link>
	<title><![CDATA[Purge Haplotigs: Pipeline to help with curating heterozygous diploid genome assemblies]]></title>
	<description><![CDATA[<p>Some parts of a genome may have a very high degree of heterozygosity. This causes contigs for both haplotypes of that part of the genome to be assembled as separate primary contigs, rather than as a contig and an associated haplotig. This can be an issue for downstream analysis whether you're working on the haploid or phased-diploid assembly.</p>
<p><span>Identify pairs of contigs that are syntenic and move one of them to the haplotig 'pool'. The pipeline uses mapped read coverage and Minimap2 alignments to determine which contigs to keep for the haploid assembly. Dotplots are optionally produced for all flagged contig matches, juxtaposed with read-coverage, to help the user determine the proper assignment of any remaining ambiguous contigs. The pipeline will run on either a haploid assembly (i.e. Canu, FALCON or FALCON-Unzip primary contigs) or on a phased-diploid assembly (i.e. FALCON-Unzip primary contigs + haplotigs). Here are&nbsp;</span><a href="https://bitbucket.org/mroachawri/purge_haplotigs/wiki/Examples">two examples</a><span>&nbsp;of how Purge Haplotigs can improve a haploid and diploid assembly.</span></p><p>Address of the bookmark: <a href="https://bitbucket.org/mroachawri/purge_haplotigs" rel="nofollow">https://bitbucket.org/mroachawri/purge_haplotigs</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>

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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/4888/murray-coxs-genomicus-lab</guid>
  <pubDate>Thu, 26 Sep 2013 16:42:42 -0500</pubDate>
  <link></link>
  <title><![CDATA[Murray Cox's Genomicus Lab]]></title>
  <description><![CDATA[
<p>This group interested in modeling genome dynamics in following topics:</p>

<p>---how genetic variation is distributed within and between individuals, <br />---determining how this diversity changes over evolutionary time.</p>

<p>Hence, Cox group work at the interface between biology, statistics and computer science to address questions of outstanding biological importance through intrepretation of large genetic datasets.</p>

<p>Profile:<br />Associate Professor Murray Cox, <br />Inaugural Rutherford Fellow of the Royal Society of New Zealand,  Principal Investigator in the BioProtection Research Center and Associate Investigator in the Allan Wilson Center for Molecular Ecology and Evolution<br />Email : m.p.cox@massey.ac.nz<br />Webpage: http://massey.genomicus.com/index.html</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38672/ltr-retriever-accurately-identifies-and-annotates-ltr-retrotransposons-and-use-lai-to-evaluates-the-continuity-of-genome-assemblies</guid>
	<pubDate>Sun, 13 Jan 2019 07:14:31 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38672/ltr-retriever-accurately-identifies-and-annotates-ltr-retrotransposons-and-use-lai-to-evaluates-the-continuity-of-genome-assemblies</link>
	<title><![CDATA[LTR_retriever: accurately identifies and annotates LTR retrotransposons and use LAI to evaluates the continuity of genome assemblies.]]></title>
	<description><![CDATA[<p>LTR_retriever is a command line program (in Perl) for accurate identification of LTR retrotransposons (LTR-RTs) from outputs of LTRharvest, LTR_FINDER, and/or MGEScan-LTR and generating non-redundant LTR-RT library for genome annotations.</p>
<p>By default, the program will generate whole-genome LTR-RT annotation and the LTR Assembly Index (LAI) for evaluations of the assembly continuity of the input genome. Users can also run LAI separately (see&nbsp;<code>Usage</code>).</p><p>Address of the bookmark: <a href="https://github.com/oushujun/LTR_retriever" rel="nofollow">https://github.com/oushujun/LTR_retriever</a></p>]]></description>
	<dc:creator>Neel</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/bookmarks/view/39903/integrative-meta-assembly-pipeline-imap-chromosome-level-genome-assembler-combining-multiple-de-novo-assemblies</guid>
	<pubDate>Sat, 31 Aug 2019 11:30:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39903/integrative-meta-assembly-pipeline-imap-chromosome-level-genome-assembler-combining-multiple-de-novo-assemblies</link>
	<title><![CDATA[Integrative Meta-Assembly Pipeline (IMAP): Chromosome-level genome assembler combining multiple de novo assemblies]]></title>
	<description><![CDATA[<p><span>Chromosome-level genome assembler combining multiple de novo assemblies</span></p>
<p><span><a href="https://github.com/jkimlab/IMAP">https://github.com/jkimlab/IMAP</a></span></p><p>Address of the bookmark: <a href="https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0221858" rel="nofollow">https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0221858</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<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/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/41144/seqmule-automated-human-exomegenome-variants-detection</guid>
	<pubDate>Tue, 18 Feb 2020 03:22:54 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41144/seqmule-automated-human-exomegenome-variants-detection</link>
	<title><![CDATA[SeqMule: Automated human exome/genome variants detection]]></title>
	<description><![CDATA[<p>SeqMule takes single-end or paird-end FASTQ or BAM files, generates a script consisting of more than 10 popular alignment, analysis tools and runs the script line by line. Users can change the pipeline or fine-tune the parameters by modifying its configuration file.</p><p>Address of the bookmark: <a href="https://doc-openbio.readthedocs.io/projects/seqmule/en/latest/" rel="nofollow">https://doc-openbio.readthedocs.io/projects/seqmule/en/latest/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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