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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/2261?offset=240</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26525/ensembl-comparative-genomics-resources</guid>
	<pubDate>Sun, 28 Feb 2016 17:10:20 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26525/ensembl-comparative-genomics-resources</link>
	<title><![CDATA[Ensembl comparative genomics resources]]></title>
	<description><![CDATA[<div>
<p>The Ensembl comparative genomics resources are one such reference set that facilitates comprehensive and reproducible analysis of chordate genome data. Ensembl computes pairwise and multiple whole-genome alignments from which large-scale synteny, per-base conservation scores and constrained elements are obtained. Gene alignments are used to define Ensembl Protein Families, GeneTrees and homologies for both protein-coding and non-coding RNA genes. These resources are updated frequently and have a consistent informatics infrastructure and data presentation across all supported species. Specialized web-based visualizations are also available including synteny displays, collapsible gene tree plots, a gene family locator and different alignment views. The Ensembl comparative genomics infrastructure is extensively reused for the analysis of non-vertebrate species by other projects including Ensembl Genomes and Gramene and much of the information here is relevant to these projects. The consistency of the annotation across species and the focus on vertebrates makes Ensembl an ideal system to perform and support vertebrate comparative genomic analyses. We use robust software and pipelines to produce reference comparative data and make it freely available.</p>
<p><strong>Database URL:</strong> <a href="http://www.ensembl.org" target="pmc_ext">http://www.ensembl.org</a>.</p>
</div><p>Address of the bookmark: <a href="http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4761110/" rel="nofollow">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4761110/</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26306/busco</guid>
	<pubDate>Sun, 07 Feb 2016 16:02:39 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26306/busco</link>
	<title><![CDATA[BUSCO]]></title>
	<description><![CDATA[<p>Assessing genome assembly and annotation completeness with Benchmarking Universal Single-Copy Orthologs</p>
<p>More at http://busco.ezlab.org/</p><p>Address of the bookmark: <a href="http://busco.ezlab.org/" rel="nofollow">http://busco.ezlab.org/</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26325/crossmap</guid>
	<pubDate>Mon, 08 Feb 2016 15:47:00 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26325/crossmap</link>
	<title><![CDATA[CrossMap]]></title>
	<description><![CDATA[<p>CrossMap is a program for convenient conversion of genome coordinates (or annotation files) between <em>different assemblies</em> (such as Human <a href="http://www.ncbi.nlm.nih.gov/assembly/2928/">hg18 (NCBI36)</a> &lt;&gt; <a href="http://www.ncbi.nlm.nih.gov/assembly/2758/">hg19 (GRCh37)</a>, Mouse <a href="http://www.ncbi.nlm.nih.gov/assembly/165668/">mm9 (MGSCv37)</a> &lt;&gt; <a href="http://www.ncbi.nlm.nih.gov/assembly/327618/">mm10 (GRCm38)</a>).</p>
<p>It supports most commonly used file formats including SAM/BAM, Wiggle/BigWig, BED, GFF/GTF, VCF.</p>
<p>CrossMap is designed to liftover genome coordinates between assemblies. It&rsquo;s <em>not</em> a program for aligning sequences to reference genome.</p>
<p>We <em>do not</em> recommend using CrossMap to convert genome coordinates between species.</p>
<p>More at http://crossmap.sourceforge.net/</p><p>Address of the bookmark: <a href="http://crossmap.sourceforge.net/" rel="nofollow">http://crossmap.sourceforge.net/</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/26432/summer-2016</guid>
  <pubDate>Sun, 21 Feb 2016 06:17:55 -0600</pubDate>
  <link></link>
  <title><![CDATA[Summer 2016]]></title>
  <description><![CDATA[
<p>REU at Fordham University- Summer 2016</p>

<p>An NSF-funded REU to study Y-chromosome diversity and sex-biased dispersal in wild brown rats (Rattus norvegicus) is available in the Munshi-South Lab at Fordham University. Our lab is currently investigating rat evolution at scales ranging from landscape genetics of individual cities to global patterns of diversity. Development of resources for investigating Y-chromosome diversity will support many of these studies. The REU student will work with the lab to bioinformatically identify Y-chromosome SNPs, design SNPtype assays,<br />extract DNA, genotype samples, and analyze data.</p>

<p>We seek applicants interested in bioinformatics, evolutionary biology, and related disciplines.  Applicants must have taken a college-level genetics course.  This REU will require attention to detail, reliability, independence, and critical thinking.</p>

<p>This position is based at Fordham University's field station, the Louis Calder Center, in Armonk, NY. The Calder Center is located approximately 25 miles north of New York City in a protected woodland area. Housing<br />will be provided at the Calder Center for the duration of the REU (May 23 to Aug 12, 2016). Additionally, the student will receive a $6,000 stipend. The selected student will participate in professional development activities through the Calder Centers REU program, including presentation of results at a research colloquium at the end of the summer.</p>

<p>To apply, please send a one page personal statement about your scientific interests and how this REU will support your professional goals, unofficial transcripts including a list of Spring 2016 courses, and names of two professional references (including title, address, phone number, and email address) as a single pdf (with your last name in the file name) to Dr. Jason Munshi-South (jmunshisouth@fordham.edu).</p>

<p>Applications are due March 4th, 2016.</p>

<p>Jason Munshi-South</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26543/breakseq2</guid>
	<pubDate>Mon, 29 Feb 2016 17:45:38 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26543/breakseq2</link>
	<title><![CDATA[BreakSeq2]]></title>
	<description><![CDATA[<p>Ultrafast and accurate nucleotide-resolution analysis of structural variants</p>
<p>More at http://bioinform.github.io/breakseq2/</p>
<p>Download BreakSeq2</p>
<p>Latest version: https://github.com/bioinform/breakseq2/archive/2.2.tar.gz<br><br>For other versions, see "releases". https://github.com/bioinform/breakseq2/releases</p><p>Address of the bookmark: <a href="http://bioinform.github.io/breakseq2/" rel="nofollow">http://bioinform.github.io/breakseq2/</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/27555/phd-at-institute-of-life-sciences-bhubaneswar</guid>
  <pubDate>Mon, 30 May 2016 03:36:04 -0500</pubDate>
  <link></link>
  <title><![CDATA[PhD at INSTITUTE OF LIFE SCIENCES, Bhubaneswar]]></title>
  <description><![CDATA[
<p>INSTITUTE OF LIFE SCIENCES</p>

<p>Bhubaneswar 751023</p>

<p>Advt No. 07/2016</p>

<p>Institute of Life Sciences (ILS), Bhubaneswar, an autonomous Institute of the Department of Biotechnology, Ministry of Science &amp; Technology, Government of India engaged in advanced research invites applications from Indian nationals for the Ph.D. program. The main focus of the projects will be computational biology in the following areas.</p>

<p>S. No. Area of Research Principal investigator</p>

<p>1. Computational Cancer Biology Dr. Anshuman Dixit</p>

<p>2. Immunogenomics &amp; Systems Biology Dr. Sunil Kumar Raghav</p>

<p>3. Chromatin remodeling and hematopoiesis Dr. Punit Prasad</p>

<p>Candidates are strongly encouraged to visit ILS webpage for detailed information, regarding the research activities of the above mentioned scientists.</p>

<p>Essential Qualifications:</p>

<p>(a) Eligibility: M.Sc., M.V.Sc., M.Pharm., M.S. Pharma. (with NET/GATE/GPAT/BINC/any other equivalent national level exam) or M.Tech with minimum of 60% marks (or equivalent grade point). Those awaiting final result may also apply.</p>

<p>Applications received after the last date will not be accepted. The envelope should clearly be superscribed with “Application for Ph.D. program (computational biology)”. Short-listed candidates selected for the interview will be published in the Institute website (www.ils.res.in).</p>

<p>Application Fees: Applicants except SC/ST candidates are required to send a non-refundable D.D. for Rs.100/- in favour of “Director, Institute of Life Sciences, Bhubaneswar” payable at Bhubaneswar along with duly filled-in application form by the date mentioned below. Director, ILS reserves the right to withdraw the procedure without assigning any reasons thereof.</p>

<p>Important dates: </p>

<p>Last date of receiving applications: 24th June 2016 </p>

<p>Date of display of short-listed candidates and instructions on the Institute website: 30th June 2016 </p>

<p>Date of interview: The interview will be organized on 25th July 2016</p>

<p>Advertisement: https://www.ils.res.in/wp-content/uploads/2016/05/advt07-16.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26852/awesome-bioinformatics-pipelines</guid>
	<pubDate>Wed, 30 Mar 2016 21:50:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26852/awesome-bioinformatics-pipelines</link>
	<title><![CDATA[Awesome bioinformatics pipelines !]]></title>
	<description><![CDATA[<p><span>A curated list of awesome pipeline toolkits ...</span></p>
<p><span>https://github.com/pditommaso/awesome-pipeline</span></p><p>Address of the bookmark: <a href="https://github.com/pditommaso/awesome-pipeline" rel="nofollow">https://github.com/pditommaso/awesome-pipeline</a></p>]]></description>
	<dc:creator>Jitendra Prajapati</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29284/genebreak-a-tool-to-systematically-identify-genes-recurrently-affected-by-the-genomic-location-of-chromosomal-cna-associated-breaks-by-a-genome-wide-approach</guid>
	<pubDate>Sat, 01 Oct 2016 15:15:29 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29284/genebreak-a-tool-to-systematically-identify-genes-recurrently-affected-by-the-genomic-location-of-chromosomal-cna-associated-breaks-by-a-genome-wide-approach</link>
	<title><![CDATA[GeneBreak: a tool to systematically identify genes recurrently affected by the genomic location of chromosomal CNA-associated breaks by a genome-wide approach]]></title>
	<description><![CDATA[<p>Development of cancer is driven by somatic alterations, including numerical and structural chromosomal aberrations. Currently, several computational methods are available and are widely applied to detect numerical copy number aberrations (CNAs) of chromosomal segments in tumor genomes. However, there is lack of computational methods that systematically detect structural chromosomal aberrations by virtue of the genomic location of CNA-associated chromosomal breaks and identify genes that appear non-randomly affected by chromosomal breakpoints across (large) series of tumor samples. ‘GeneBreak’ is developed to systematically identify genes recurrently affected by the genomic location of chromosomal CNA-associated breaks by a genome-wide approach, which can be applied to DNA copy number data obtained by array-Comparative Genomic Hybridization (CGH) or by (low-pass) whole genome sequencing (WGS). First, ‘GeneBreak’ collects the genomic locations of chromosomal CNA-associated breaks that were previously pinpointed by the segmentation algorithm that was applied to obtain CNA profiles. Next, a tailored annotation approach for breakpoint-to-gene mapping is implemented. Finally, dedicated cohort-based statistics is incorporated with correction for covariates that influence the probability to be a breakpoint gene. In addition, multiple testing correction is integrated to reveal recurrent breakpoint events. This easy-to-use algorithm, ‘GeneBreak’, is implemented in R (www.cran.r-project.org) and is available from Bioconductor (www.bioconductor.org/packages/release/bioc/html/GeneBreak.html).</p>
<p> </p><p>Address of the bookmark: <a href="http://www.bioconductor.org/packages/release/bioc/html/GeneBreak.html" rel="nofollow">http://www.bioconductor.org/packages/release/bioc/html/GeneBreak.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29620/hybpiper</guid>
	<pubDate>Fri, 04 Nov 2016 05:02:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29620/hybpiper</link>
	<title><![CDATA[HybPiper]]></title>
	<description><![CDATA[<p>HybPiper was designed for targeted sequence capture, in which DNA sequencing libraries are enriched for gene regions of interest, especially for phylogenetics. HybPiper is a suite of Python scripts that wrap and connect bioinformatics tools in order to extract target sequences from high-throughput DNA sequencing reads.</p>
<p>Targeted bait capture is a technique for sequencing many loci simultaneously based on bait sequences. HybPiper pipeline starts with high-throughput sequencing reads (for example from Illumina MiSeq), and assigns them to target genes using BLASTx or BWA. The reads are distributed to separate directories, where they are assembled separately using SPAdes. The main output is a FASTA file of the (in frame) CDS portion of the sample for each target region, and a separate file with the translated protein sequence.</p>
<p>HybPiper also includes post-processing scripts, run after the main pipeline, to also extract the intronic regions flanking each exon, investigate putative paralogs, and calculate sequencing depth. For more information,&nbsp;<a href="https://github.com/mossmatters/HybPiper/wiki/">please see our wiki</a>.</p>
<p>HybPiper is run separately for each sample (single or paired-end sequence reads). When HybPiper generates sequence files from the reads, it does so in a standardized directory hierarchy. Many of the post-processing scripts rely on this directory hierarchy, so do not modify it after running the initial pipeline. It is a good idea to run the pipeline for each sample from the same directory. You will end up with one directory per run of HybPiper, and some of the later scripts take advantage of this predictable directory structure.</p><p>Address of the bookmark: <a href="https://github.com/mossmatters/HybPiper" rel="nofollow">https://github.com/mossmatters/HybPiper</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/2464/computer-theory-genetics-george-chao-at-tedxumnsalon</guid>
	<pubDate>Thu, 15 Aug 2013 22:08:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/2464/computer-theory-genetics-george-chao-at-tedxumnsalon</link>
	<title><![CDATA[Computer Theory & Genetics: George Chao at TEDxUMNSalon]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/7_GL17oiak8" frameborder="0" allowfullscreen></iframe>George Chao is an undergraduate senior studying Genetics and Computer Science at the University of Minnesota. Having started genetics research as soon as he entered the university, he has worked in labs spanning multiple disciplines as well as in Japan. Some of these researches include developmental genetics in Drosophila, computational techniques for analyzing protein interactions, and helping with the development of algorithms to analyze motion capture data of patients with neck pain. During this time, George steadily developed a fascination with the field of bioinformatics, the study of using computational techniques to learn from genetic data. He would like to go into a career of research into the application of bioinformatics in various fields.

----

The individuals involved with TEDxUMN have a passion for bringing together the great thinkers at the University of Minnesota and giving them the opportunity to share their ideas worth spreading and to discuss our shared future. We provide these great people the opportunity to share these ideas on a global stage and with an incredibly diverse audience. We believe in the power of ideas to change attitudes, lives and ultimately the world.

Check out TEDxUMN at http://www.TEDxUMN.com/

In the spirit of ideas worth spreading, TEDx is a program of local, self-organized events that bring people together to share a TED-like experience. At a TEDx event, TEDTalks video and live speakers combine to spark deep discussion and connection in a small group. These local, self-organized events are branded TEDx, where x = independently organized TED event. The TED Conference provides general guidance for the TEDx program, but individual TEDx events are self-organized.* (*Subject to certain rules and regulations)]]></description>
	
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