<?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/14011?offset=1560</link>
	<atom:link href="https://bioinformaticsonline.com/related/14011?offset=1560" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	
<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/14003/jrf-position-in-the-faculty-of-life-sciences-biotechnology-at-sauth-asian-university</guid>
  <pubDate>Wed, 13 Aug 2014 07:16:30 -0500</pubDate>
  <link></link>
  <title><![CDATA[JRF position in the Faculty of Life Sciences &amp; Biotechnology at  Sauth Asian University]]></title>
  <description><![CDATA[
<p>Opening for a Project-JRF position in the Faculty of Life Sciences &amp; Biotechnology</p>

<p>Applications are invited for the post of Junior Research Fellow (JRF) in a DBT funded IYBA project entitled “Generatingaprotein-ncRNA interactome for Dorsal mediated gene regulation and dorso-ventral patterning genes in Drosophila” in the Lab. Of Molecular Biology at the Faculty of Life Sciences and Biotechnology, South Asian University, New Delhi. The project requires extensive use of molecular, genetic and genomic approaches.</p>

<p>POST: Junior Research Fellow (JRF)</p>

<p>NO. OF VACANCIE(S) - (01)</p>

<p>FELLOWSHIP: Rs. 16,000/- plus HRA</p>

<p>PROJECT DURATION: 2014-2016 (Two years)</p>

<p>LAST DATE FOR APPLICATION: Aug 18, 2014.</p>

<p>Eligibility criteria:</p>

<p>M.Sc./M.Tech./ in Biological Sciences/Biotechnology/Bio-Informatics. Candidates with research experience in the field of Drosophila/Yeast genetics will be preferred.</p>

<p>Application Procedure:</p>

<p>A covering letter along with your CV, copy of prior publications (if any) and proof of experience should be e-mailed to lmb_sau@aol.com. Hardcopy of the application should be brought on the day of interview along with other testimonials and marks statements for verification purpose.</p>

<p>IMPORTANT NOTE:</p>

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

<p>-SAU may select candidates against the post depending upon qualification and experience of candidates and reserves the right to relax any of the qualifications in case the candidate is found otherwise well qualified by the Selection Committee</p>

<p>-The abovementioned post is temporary and will be initially offered for a period of one year and can be extended, on satisfactory performance. </p>

<p>More at http://www.sau.ac.in/recruitment/vacancy.html</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42987/public-databases-for-bioinformatics</guid>
	<pubDate>Tue, 23 Mar 2021 05:32:15 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42987/public-databases-for-bioinformatics</link>
	<title><![CDATA[Public Databases for Bioinformatics !]]></title>
	<description><![CDATA[<pre>https://www.nature.com/articles/s41467-020-17155-y<br><br>Server Infrastructure:

File Server:

dhara: Synology 3614 Storage Appliance
4 Core Xeon
108TB disk storage
10Gb ethernet to SCG3
Access atx: dhara:5000
Has btsync server (try it - its much better than dropbox)

Compute Servers:

nandi: Kundaje and Phi Server
24 intel cores
256GB RAM
500GB of SSD storage 
36TB RAID6 local storage
4 Intel Phi's (space for 4 more GPU's)


durga: Montgomery and sensitive data
24 intel cores
256GB RAM
500GB of SSD RAID0 storage 
60TB RAID6 local storage

mitra: Bassik and Web/DB Server
24 core
256GB RAM 
500GB of SSD RAID0 storage 
36TB RAID6 local storage

vayu: Kundaje GPU server
4 core
64GB RAM 
200GB of SSD storage 
8TB RAID10 local storage
4 Nvidia GTX 970 4GB GPUs

amold: Bickel and SGE server
32 AMD core
128GB RAM 
200GB of SSD storage 
12TB RAID5 local storage

wotan: Bickel and SGE server
64 AMD core
256GB RAM 
200GB of SSD storage 
12TB RAID5 local storage

Filesystem:

/users/$USER
default home directory
full backups nightly 
nfs mount to dhara
should store code, papers, and other highly processed data here

/mnt/data/
globally accessible data
should store common data here
e.g. genomes and indexes, annotations, ENCODE data  
if you dont want this to count towards your quote you must chown

/mnt/lab_data/$LAB/
lab accessible data
should store lab project data here 
e.g. ATAC-seq prediction data, enhancer prediction, motif calls

/srv/scratch/$USER
fast local storage
not backed up, but on raid and data will never be deleted
most analysis should be performed here

/srv/persistent/$USER
fast local storage
synced nightly, but not backed up
       ie if the hard drives fail or you delete something and notice 
       within 24 hours we can recover. Otherwise not. (vs home which is 
       properly backed up )  
intermediate analysis products that would be hard to recover should be stored here 
       e.g. stochastic analysis results that need to be kept so that paper 
       results can be reproduced

/srv/www/$LABNAME/
web accessible from mitra.stanford.edu
*NOT BACKED UP*

Some parallel programming patterns:

# gzip a bunch of files
parallel gzip -- *.FILESTOGZIP

# fork example in python:
(for more detailed examples look at 
 https://github.com/nboley/grit/ grit/lib/multiprocessing_utils.py)

import os
import time
import random

import multiprocessing

class ProcessSafeOPStream( object ):
    def __init__( self, writeable_obj ):
        self.writeable_obj = writeable_obj
        self.lock = multiprocessing.Lock()
        self.name = self.writeable_obj.name
        return
    
    def write( self, data ):
        self.lock.acquire()
        self.writeable_obj.write( data )
        self.writeable_obj.flush()
        self.lock.release()
        return
    
    def close( self ):
        self.writeable_obj.close()

def worker(queue, ofp):
    # Try without this
    random.seed()
    while True:
        i = queue.get()
        if i == 'FINISHED': return
        # simulate an expensive function
        x = random.random()
        time.sleep(x/10)
        print i, x
        ofp.write("%i\t%s\n" % (i, x))

NSIMS = 10000
NPROC = 25

# populate queue
todo = multiprocessing.Queue()
for i in xrange(NSIMS): todo.put(i)
for i in xrange(NPROC): todo.put('FINISHED')

ofp = ProcessSafeOPStream( open("output.txt", "w") )

pids = []
for i in xrange(NPROC):
    pid = os.fork()
    if pid == 0:
       worker(todo, ofp)
       os._exit(0)
    else:
       pids.append(pid)  

for pid in pids:
    os.waitpid(pid, 0)

ofp.close()

print "FINISHED"<br><br></pre>
<p>For use case 1 we obtained the following ENCODE and ROADMAP datasets&nbsp;<a href="https://www.encodeproject.org/files/ENCFF446WOD/@@download/ENCFF446WOD.bed.gz">https://www.encodeproject.org/files/ENCFF446WOD/@@download/ENCFF446WOD.bed.gz</a>,&nbsp;<a href="https://www.encodeproject.org/files/ENCFF546PJU/@@download/ENCFF546PJU.bam">https://www.encodeproject.org/files/ENCFF546PJU/@@download/ENCFF546PJU.bam</a>,&nbsp;<a href="https://www.encodeproject.org/files/ENCFF059BEU/@@download/ENCFF059BEU.bam">https://www.encodeproject.org/files/ENCFF059BEU/@@download/ENCFF059BEU.bam</a>. Blacklisted regions were obtained from&nbsp;<a href="http://mitra.stanford.edu/kundaje/akundaje/release/blacklists/hg38-human/hg38.blacklist.bed.gz">http://mitra.stanford.edu/kundaje/akundaje/release/blacklists/hg38-human/hg38.blacklist.bed.gz</a>. The human genome version hg38 was obtained from&nbsp;<a href="http://hgdownload.cse.ucsc.edu/goldenPath/hg38/bigZips/hg38.fa.gz">http://hgdownload.cse.ucsc.edu/goldenPath/hg38/bigZips/hg38.fa.gz</a>.</p>
<p>For use case 2 we used the set of narrowPeak files summarized in&nbsp;<a href="https://github.com/wkopp/janggu_usecases/tree/master/extra/urls.txt">https://github.com/wkopp/janggu_usecases/tree/master/extra/urls.txt</a>&nbsp;(archived version v1.0.1). The human genome version hg19 was obtained from&nbsp;<a href="http://hgdownload.cse.ucsc.edu/goldenPath/hg19/bigZips/hg19.fa.gz">http://hgdownload.cse.ucsc.edu/goldenPath/hg19/bigZips/hg19.fa.gz</a></p>
<p>For use case 3 we used the ENCODE datasets&nbsp;<a href="https://www.encodeproject.org/files/ENCFF591XCX/@@download/ENCFF591XCX.bam">https://www.encodeproject.org/files/ENCFF591XCX/@@download/ENCFF591XCX.bam</a>,&nbsp;<a href="https://www.encodeproject.org/files/ENCFF736LHE/@@download/ENCFF736LHE.bigWig">https://www.encodeproject.org/files/ENCFF736LHE/@@download/ENCFF736LHE.bigWig</a>,&nbsp;<a href="https://www.encodeproject.org/files/ENCFF177HHM/@@download/ENCFF177HHM.bam">https://www.encodeproject.org/files/ENCFF177HHM/@@download/ENCFF177HHM.bam</a>&nbsp;as we as the GENCODE annotation v29 from&nbsp;<a href="ftp://ftp.ebi.ac.uk/pub/databases/gencode/Gencode_human/release_29/gencode.v29.annotation.gtf.gz">ftp://ftp.ebi.ac.uk/pub/databases/gencode/Gencode_human/release_29/gencode.v29.annotation.gtf.gz</a>.</p><p>Address of the bookmark: <a href="http://mitra.stanford.edu/" rel="nofollow">http://mitra.stanford.edu/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/14183/guest-faculty-at-pondicherry-university</guid>
  <pubDate>Wed, 20 Aug 2014 00:37:57 -0500</pubDate>
  <link></link>
  <title><![CDATA[Guest Faculty at Pondicherry University]]></title>
  <description><![CDATA[
<p>Pondicherry University, India</p>

<p>Walk in interview for guest faculty in Pondicherry University, India. For more information please visit http://www.bicpu.edu.in/bioinfor140814.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/14339/apps-for-busy-bioinformatics-researchers</guid>
	<pubDate>Mon, 25 Aug 2014 01:26:19 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/14339/apps-for-busy-bioinformatics-researchers</link>
	<title><![CDATA[Apps for Busy Bioinformatics Researchers !!!]]></title>
	<description><![CDATA[<h3>DNAApp:</h3><h4><strong>DNAApp: for </strong><a href="https://itunes.apple.com/us/app/dnaapp/id854944694?mt=8" target="_blank"><strong>iPhone/iPad</strong></a></h4><p>This is an <a href="http://www.apple.com/ios/" target="_blank" title="IOS">iOS</a> app that allows for the opening and analysis of <a href="http://en.wikipedia.org/wiki/DNA_sequencing" target="_blank" title="DNA sequencing">DNA sequencing</a> files - ab1. It includes handy tools such as "<a href="http://en.wikipedia.org/wiki/Complementarity_%28molecular_biology%29" target="_blank" title="Complementarity (molecular biology)">Reverse Complement</a>", "Jump to", "<a href="http://en.wikipedia.org/wiki/Cut%2C_copy%2C_and_paste" target="_blank" title="Cut, copy, and paste">Copy and Paste</a> sequences", fast and end scrolling, "<a href="http://en.wikipedia.org/wiki/Chromatography" target="_blank" title="Chromatography">Chromatogram</a> adjustments", and "Searching for segments" functions. <br /> When used in combination with other zip apps, and also web-tools like Blast, this app allows you to analyze, and also determine the quality of your sequencing files. <br /> This app works with cloud storage access like Dropbox to your sequencing files. <br /> This is now compatible with the new update for iOS 7.1. <br /> Demo video can be found at:<strong> https://www.youtube.com/watch?v=mXeo9hXdZgM&nbsp;</strong></p><p><strong>More @ </strong><a href="https://itunes.apple.com/us/app/dnaapp/id854944694?mt=8" target="_blank" title="https://itunes.apple.com/us/app/dnaapp/id854944694?mt=8"><strong>https://itunes.apple.com/us/app/dnaapp/id854944694?mt=8</strong></a></p><h4><a href="https://play.google.com/store/apps/details?id=bii.seqdatreader&amp;hl=en" target="_blank"><strong>DNAApp: For android</strong></a></h4><p>This is the first android app that allows for the opening and analysis of DNA sequencing files - ab1. It includes handy tools such as "Reverse Complement", "Jump to", fast and end scrolling, "Chromatogram adjustments", amino acid translations, "export to fasta", and "searching for segment" function.</p><ul>
<li>When used in combination with other zip apps, and also web-tools like Blast, this app allows you to analyze, and also determine the quality of your sequencing files.</li>
<li>This app works with cloud storage access like Dropbox to your sequencing files.</li>
<li>This is now compatible with the new update for <a href="http://code.google.com/android/" target="_blank" title="Android">Android</a> 4.4.2.</li>
</ul><p><strong>More @&nbsp; </strong><a href="https://play.google.com/store/apps/details?id=bii.seqdatreader&amp;hl=en" target="_blank" title="https://play.google.com/store/apps/details?id=bii.seqdatreader&amp;hl=en"><strong>https://play.google.com/store/apps/details?id=bii.seqdatreader&amp;hl=en</strong></a></p><h3>BioGene:iPhone/iPad</h3><p>BioGene is an information tool for biological research. Use BioGene to learn about gene function. Enter a gene symbol or gene name, for example "CDK4" or "cyclin dependent kinase 4" and BioGene will retrieve its gene function and references into its function (<a href="http://en.wikipedia.org/wiki/GeneRIF" target="_blank" title="GeneRIF">GeneRIF</a>).</p><ul>
<li>BioGene was produced in affiliation with the Computational Biology Center at <a href="http://maps.google.com/maps?ll=40.764096,-73.956842&amp;spn=0.01,0.01&amp;q=40.764096,-73.956842%20%28Memorial%20Sloan%E2%80%93Kettering%20Cancer%20Center%29&amp;t=h" target="_blank" title="Memorial Sloan&ndash;Kettering Cancer Center">Memorial Sloan-Kettering Cancer Center</a> with primary information from Entrez Gene at the <a href="http://maps.google.com/maps?ll=38.994994,-77.099339&amp;spn=0.01,0.01&amp;q=38.994994,-77.099339%20%28National%20Center%20for%20Biotechnology%20Information%29&amp;t=h" target="_blank" title="National Center for Biotechnology Information">NCBI</a>.</li>
</ul><p><strong>More @&nbsp; </strong><a href="https://itunes.apple.com/us/app/biogene/id333180084?mt=8" target="_blank" title="https://itunes.apple.com/us/app/biogene/id333180084?mt=8"><strong>https://itunes.apple.com/us/app/biogene/id333180084?mt=8</strong></a></p><h3>Mentha - the interactome browser: Android</h3><p>About: mentha - the interactome browser, is a project that offers protein-protein physical/enzymatic interaction information from various sources. For more details about mentha, visit mentha's website. This client application is an independent project. This application is designed to allow you to search proteins on the go.</p><h4><strong>Key features (Also in website):</strong></h4><ul>
<li>Search proteins by <a href="http://en.wikipedia.org/wiki/UniProt" target="_blank" title="UniProt">UniProt</a> IDs, gene name or keywords</li>
<li>Collect proteins from different queries.</li>
<li>Spot common interactors in clusters.</li>
<li>Easily distinguish between proteins from Homo sapiens and other organisms (Yellow rounded rectangles)</li>
<li>Click on edges(links) to get scientific evidence.</li>
<li>Click on proteins to see descriptions.</li>
</ul><p><strong>More @&nbsp; </strong><a href="https://play.google.com/store/apps/details?id=com.sinnefa.mentha&amp;hl=en" target="_blank" title="https://play.google.com/store/apps/details?id=com.sinnefa.mentha&amp;hl=en"><strong>https://play.google.com/store/apps/details?id=com.sinnefa.mentha&amp;hl=en</strong></a></p><h3>GeneIndex: iPhone/iPad</h3><p>GeneIndex quickly provides information about genes from various sources. It also includes a RSS reader for journal feeds as well as a PubMed viewer.</p><h4><strong>Key Features:</strong></h4><ul>
<li>Look up genes by symbol or description.</li>
<li>Gene indexes for many mammals, plants, invertebrates, and bacteria.</li>
<li>Link to gene info on websites.</li>
<li>Download files for offline use. (.pdf, .mp3, .m4v, .doc, .ppt, .xls )</li>
<li>transfer files via open in, email, or iTunes file sharing</li>
<li>View RSS feeds for journals</li>
<li>Query GeneRIF interactions, COSMIC mutations, and CNV data for cell lines.</li>
<li>Does not require a network connection for local databases.</li>
<li>View and search PubMed in table view.</li>
</ul><p><br /> GeneIndex provides a convenient and portable way to lookup gene symbols while at a seminar, conference, or lab meeting. Genes are linked to common life science websites such as NCBI, COSMIC, KEGG, PubMed, SymAtlas, UCSC genome browser, Pathway Commons, Genatlas, Wikipedia, HUGO, and OMIM. GeneRIF gene interactions can also be queried.</p><ul>
<li>Keep current on the scientific literature. GeneIndex includes a RSS reader and web browser for browsing popular journals like Nature, Science, and Cell. You can also add your own RSS feeds. PDFs and podcasts can be saved as files that you can view on the device or email as attachments.</li>
<li>Examine the status of genes in common cell lines. A subset of COSMIC containing cell lines can be queried for mutations. Copy Number Variation (CNV) plots from cell lines profiled by GSK and Sanger are also linked to genes.</li>
</ul><p><strong>More @&nbsp; </strong><a href="https://itunes.apple.com/us/app/geneindex/id319769866?mt=8" target="_blank" title="https://itunes.apple.com/us/app/geneindex/id319769866?mt=8"><strong>https://itunes.apple.com/us/app/geneindex/id319769866?mt=8</strong></a></p><h3>Genome Voyager: iPad</h3><p>Gain first hand experience identifying the genomic basis of disease by analyzing cases with whole genome sequencing data that have been published for research and learning purposes.</p><ul>
<li>Visualize whole human genome sequencing data including small variations, copy number variations (CNVs), and loss of heterozygosity (LOH) events</li>
<li>Quickly find variants of interest by filtering variants based on associated genes, functional impact, allele frequency in data sets, and cross-references with various genomic databases.</li>
<li>Collaborate on variant assessments with other researchers and academics to improve knowledge of both pathogenic and benign variants. <br /> To use Genome Voyager, users must join Genome Voyager&rsquo;s community of researchers and academics. Visit <strong>http://voyager.completegenomics.com to signup.</strong></li>
</ul><p><strong>More @&nbsp; </strong><a href="https://itunes.apple.com/us/app/genome-voyager/id637353801?mt=8" target="_blank" title="https://itunes.apple.com/us/app/genome-voyager/id637353801?mt=8"><strong>https://itunes.apple.com/us/app/genome-voyager/id637353801?mt=8</strong></a></p><h3>YeastGenome: iPhone/iPad</h3><p>Use YeastGenome to quickly find fundamental information about Saccharomyces cerevisae genes and chromosomal features. Search gene names, gene descriptions or browse the database to find information about your favorite gene, as well as more detailed information such as Gene Ontology, mutant phenotype, and protein and genetic interaction data. <br /> YeastGenome contains the latest from the Saccharomyces Genome Database (www.yeastgenome.org) in an on bound app database. As more detailed information is presented the app switches to web services access to SGD, and then for even more details provides complete information via hyperlinks to the appropriate SGD database pages.</p><h4><strong>Key features:</strong></h4><ul>
<li>Search using gene name or keywords</li>
<li>Browse by feature type</li>
<li>Save your favorite features</li>
<li>Can be used in airplane mode</li>
<li>Email information about features to collaborators</li>
</ul><h4><strong>What's New in Version 1.8.1</strong></h4><ul>
<li>This update is required to provide continued functionality. Some of the data provided by this app accesses the SGD service using a method that is changing in May 2013. This version provides changes to allow access to continue. The on board database of yeast gene information has also been updated to March 2013.</li>
</ul><p><strong>More @&nbsp; </strong><a href="https://itunes.apple.com/us/app/yeastgenome/id520868597?mt=8" target="_blank" title="https://itunes.apple.com/us/app/yeastgenome/id520868597?mt=8"><strong>https://itunes.apple.com/us/app/yeastgenome/id520868597?mt=8</strong></a></p><h3>SNPdbe: iPhone/iPad</h3><p>SNPdbe &mdash; SNP database of effects, with predictions of computationally annotated functional impacts of SNPs. Database entries represent nsSNPs in dbSNP and 1000 Genomes collection, as well as variants from UniProt and PMD. SAASs come from &gt;2600 organisms; &lsquo;human&rsquo; being the most prevalent. The impact of each SAAS on protein function is predicted using the SNAP and SIFT algorithms and augmented with experimentally derived function/structure information and disease associations from PMD, OMIM and UniProt.</p><p><strong>More @&nbsp; </strong><a href="https://itunes.apple.com/us/app/snpdbe/id588289719?mt=8" target="_blank" title="https://itunes.apple.com/us/app/snpdbe/id588289719?mt=8"><strong>https://itunes.apple.com/us/app/snpdbe/id588289719?mt=8</strong></a></p><h3>SimGene: iPhone/iPad / Android</h3><h4><strong>SimGene: for iPhone/iPad </strong></h4><p>SimGene is an iPhone/iPad/iPod touch application designed for molecular biologists, bioinformaticians and medical researchers. The application interfaces with Simbiot, Ensembl, NCBI, Gene Ontology, KEGG Pathways, PubMed, Genomic Variations and many other databases to retrieve up-to-date annotation information for over 30 species, based on gene symbol search. The application provides gene and transcript cross reference information for NCBI, Ensembl, RefSeq and UniProt. SimGene also contains an integrated genome browser with information on genes, transcripts, exons and SNPs.</p><p><strong>More @&nbsp; </strong><a href="https://itunes.apple.com/us/app/simgene/id427772349?mt=8" target="_blank" title="https://itunes.apple.com/us/app/simgene/id427772349?mt=8"><strong>https://itunes.apple.com/us/app/simgene/id427772349?mt=8</strong></a></p><h4><strong>SimGene: for Android</strong></h4><p>bioinformaticians and medical researchers. The application interfaces with Simbiot,Ensembl, NCBI, Gene Ontology, KEGG Pathways, PubMed, Genomic Variations andmany other databases to retrieve up-to-date annotation information for over 30species, based on gene symbol search. The application provides gene and transcriptcross reference information for NCBI, Ensembl, RefSeq and UniProt. SimGene alsocontains an integrated genome browser with information on genes, transcripts,exons and SNPs.</p><p><strong>More @&nbsp; </strong><a href="https://play.google.com/store/apps/details?id=com.japanbioinformatics.simgene&amp;hl=en" target="_blank" title="https://play.google.com/store/apps/details?id=com.japanbioinformatics.simgene&amp;hl=en"><strong>https://play.google.com/store/apps/details?</strong></a></p><h3>TimeTree: iPhone/iPad</h3><p>TimeTree is a public knowledge-base for information on the evolutionary timescale of life. This application allows easy exploration of the thousands of divergence times among organisms in the scientific literature. A tree-based (hierarchical) system is used to identify all published molecular time estimates bearing on the divergence of two chosen organisms, such as species, compute summary statistics, and present the results. Names of two taxa to be compared are entered in the search window and the results are presented on a set of self-explanatory tabs.</p><ul>
<li>TimeTree 3.0 was released September 27, 2011 with new data from 1209 studies including 25342 time nodes. We will be adding more data in the future as it comes in from researchers.</li>
<li>TimeTree is jointly directed by Blair Hedges (Pennsylvania State University) and Sudhir Kumar (Arizona State University). This project has been supported, in part, by grants from the National Science Foundation, National Institutes of Health, NASA Astrobiology Institute, and Science Foundation of Arizona.</li>
</ul><p><strong>More @&nbsp; </strong><a href="https://itunes.apple.com/us/app/timetree/id372842500?mt=8" target="_blank" title="https://itunes.apple.com/us/app/timetree/id372842500?mt=8"><strong>https://itunes.apple.com/us/app/timetree/id372842500?mt=8</strong></a></p><h3><strong>GeneGroove: iPhone/iPad </strong></h3><p>GeneGroove is the first application to create a music melody from DTC-Genomics data. If you own 23andMe (Mountain View, CA) personal genomic results, GeneGroove will create for you a unique melody intimately based on your 23andMe genome informations. The music in you.</p><ul>
<li>After uploading your 23andMe raw data onto your iPhone via iTunes, GeneGroove will analyze your genome informations and generate a unique identifier key. This key, called the GeNumber, will embed the uniqueness of your genome data while keeping your privacy safe, and will be used by GeneGroove to generate your music melody.</li>
<li>The GeNumber doesn't contain anymore genomic information but it is based on your genome and it is unique, it is yours. It will be used in upcoming Portable Genomics applications to mix and remix music, manipulate sounds and share your art with your friends and family.</li>
</ul><p><strong>More @&nbsp; </strong><a href="https://itunes.apple.com/us/app/genegroove/id492247404?mt=8" target="_blank" title="https://itunes.apple.com/us/app/genegroove/id492247404?mt=8"><strong>https://itunes.apple.com/us/app/genegroove/id492247404?mt=8</strong></a></p>]]></description>
	<dc:creator>Manisha Mishra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34482/ribbon-visualizing-complex-genome-alignments-and-structural-variation</guid>
	<pubDate>Wed, 29 Nov 2017 07:40:22 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34482/ribbon-visualizing-complex-genome-alignments-and-structural-variation</link>
	<title><![CDATA[Ribbon: Visualizing complex genome alignments and structural variation:]]></title>
	<description><![CDATA[<p>Ribbon can be used for long reads, short reads, paired-end reads, and assembly/genome alignments. Instructions for each data format are available by clicking on "instructions" in each tab on the right.</p>
<p>Local installation:</p>
<p>You can install Ribbon locally from Github by following the instructions here:&nbsp;<a href="https://github.com/MariaNattestad/ribbon" target="_blank">https://github.com/MariaNattestad/Ribbon</a></p><p>Address of the bookmark: <a href="http://genomeribbon.com/" rel="nofollow">http://genomeribbon.com/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/14899/post-doc-positions-at-the-institute-of-evolution-university-of-haifa-haifa-israel</guid>
  <pubDate>Thu, 04 Sep 2014 03:59:38 -0500</pubDate>
  <link></link>
  <title><![CDATA[Post-Doc Positions at the Institute of Evolution, University of Haifa, Haifa, Israel]]></title>
  <description><![CDATA[
<p>We are looking for independent, motivated, diligent, laborious, dedicated Bioinformaticians as post-doctorate fellows for a project aimed at revealing the mechanisms of cancer-resistance and anti-cancer activity of the hypoxia-tolerant subterranean, blind mole-rat, Spalax along its underground evolutionary adaptations. Our project has captured the interest of the scientific community and we have ample financial support for the studies. Generous fellowships ($30K to $40K according to qualifications and performance) are available, immediately, for Post-Docs experts in bioinformatics with a background of good understanding biological questions. That is that can independently handle raw output data of RNA-seq / miR seq/ Genomic, analyze it and can interpret intelligently the relevant biological background. Outstanding candidates for PhD experienced in Bioinformatics will also be considered. Familiarity with cancer research is an advantage. Experience of writing manuscripts for publication and a publication record in relevant journals are expected. English skills both oral and written are required. American, Western-European or Israeli education is a significant benefit. </p>

<p>Our present objectives is to identify and isolate the substances secreted by Spalax cells, resolve with which components they interact that are active only on cancer cells, in order to unravel the biological mechanisms and pathways that evolved in Spalax cell machinery and ultimately lead to the death of cancer-cells. The study could attest to be a breakthrough in cancer research, using the long lived, hypoxia- and cancer-tolerant Spalax as a significant biological resource for biomedical research that hopefully could open new horizons in treatment and prevention of cancer in humans. </p>

<p>Contact: The applications should be submitted, together with extended CV and bibliography, summary of past accomplishments, and contact information of 3 referees, to Prof of Research Aaron Avivi (aaron@research.haifa.ac.il) AND Dr. Imad Shams (imadshams@gmail.com). (http://bit.ly/1lywShk) aaron@research.haifa.ac.il </p>

<p>More at http://evolution.haifa.ac.il/index.php/29-people/personal-websites/77-personal-site-avivi</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34567/jobtree-based-python-wrapper-to-run-the-genome-simulation-tool-suite-evolver</guid>
	<pubDate>Fri, 08 Dec 2017 16:26:32 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34567/jobtree-based-python-wrapper-to-run-the-genome-simulation-tool-suite-evolver</link>
	<title><![CDATA[jobTree based python wrapper to run the genome simulation tool suite Evolver]]></title>
	<description><![CDATA[<p><span>evolverSimControl</span><span>&nbsp;(</span><span>eSC</span><span>) can be used to simulate multi-chromosome genome evolution on an arbitrary phylogeny (</span><a href="http://evolution.genetics.washington.edu/phylip/newicktree.html">Newick format</a><span>). In addition to simply running evolver,&nbsp;</span><span>eSC</span><span>&nbsp;also automatically creates statistical summaries of the simulation as it runs including text and image files. Also included are convenience scripts to: check on a running simulation and see detailed status and logging information; extract fasta sequence files from the leaf nodes of a completed simulation; extract pairwise multiple alignment files (</span><a href="http://genome.ucsc.edu/FAQ/FAQformat.html#format5">.maf</a><span>) from leaf and branch nodes from a completed simulation and with the help of&nbsp;</span><a href="https://github.com/dentearl/mafTools/">mafJoin</a><span>, join them together into a single maf covering the entire simulation.</span></p><p>Address of the bookmark: <a href="https://github.com/dentearl/evolverSimControl" rel="nofollow">https://github.com/dentearl/evolverSimControl</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/15030/software-engineercomputational-biologist-equinome-ltd-dublin-ireland</guid>
  <pubDate>Thu, 04 Sep 2014 19:21:26 -0500</pubDate>
  <link></link>
  <title><![CDATA[Software engineer/Computational Biologist - Equinome Ltd., Dublin, Ireland]]></title>
  <description><![CDATA[
<p>Equinome (www.equinome.com) is the world leader in the research and<br />development of state-of-the-art novel genomic tools to inform the breeding,<br />selection and training of Thoroughbred racehorses. Since its launch in 2010,<br />Equinome has successfully commercialised three performance-related genetic<br />tests, with a pipeline of further genetic tests in development. We work with<br />many of the world's leading racehorse trainers and breeders in Europe,<br />Australasia, USA and South Africa. The company has been featured on CNN,<br />Bloomberg, RTE, BBC, The Guardian, Discovery Channel and Channel 4, among<br />others.</p>

<p>The Role</p>

<p>We are looking for a Software Engineer - Computational Biologist with 3+<br />years' experience in a similar role to design and implement a backend system<br />to support an online individualised genomics interface. This position is a<br />great opportunity for an ambitious, self-motivated individual to work in a<br />demanding, challenging and interesting role.</p>

<p>Position Description:<br />. Participate in planning, design, and implementation of Equinome back<br />end systems and technologies.<br />. Implement interfaces and management tools for back end services.<br />. Manage, analyse, interpret and visualise large genomics data sets.<br />. Work closely with scientific team to develop new features and<br />application enhancements<br />. Design, develop and manage a genomics research database.</p>

<p>Qualification/Experience:<br />. Minimum MSc in Computer Science, Genetics, Bioinformatics or in a<br />related field (A Ph.D qualification would be an advantage).<br />. Proven 3+ years of experience in similar role.<br />. Highly proficient in Python, SQL, MySQL.<br />. Excellent knowledge of mammalian genomics, bioinformatics and<br />statistical/population genetics.<br />. Hands-on experience working with large data sets.<br />. Experience with front-end technologies (HTML/CSS/Javascript) an<br />advantage.<br />. Experience in rapid web application development: e.g. Django.<br />. Knowledge or experience of Unix Scripting and R statistical<br />programming language would be an advantage.<br />. Ability to work with minimum supervision to deliver high-quality<br />code on time.<br />. Fluency in English and good written and communication skills.<br />. Meticulous attention to detail.</p>

<p>Applications should be submitted before Friday, 26 September 2014 using the<br />following link:<br />http://bit.ly/WgbhxS</p>

<p>Note: Full information and application procedure is available at this link:<br />http://bit.ly/WgbhxS</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34620/mash-fast-genome-and-metagenome-distance-estimation-using-minhash</guid>
	<pubDate>Tue, 12 Dec 2017 17:30:12 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34620/mash-fast-genome-and-metagenome-distance-estimation-using-minhash</link>
	<title><![CDATA[Mash: fast genome and metagenome distance estimation using MinHash]]></title>
	<description><![CDATA[<p>Mash is normally distributed as a dependency-free binary for Linux or OSX (see&nbsp;<a href="https://github.com/marbl/Mash/releases">https://github.com/marbl/Mash/releases</a>). This source distribution is intended for other operating systems or for development. Mash requires c++11 to build, which is available in and GCC &gt;= 4.8 and OSX &gt;= 10.7.</p>
<p>See&nbsp;<a href="http://mash.readthedocs.org/">http://mash.readthedocs.org</a>&nbsp;for more information.</p><p>Address of the bookmark: <a href="https://github.com/marbl/Mash/releases" rel="nofollow">https://github.com/marbl/Mash/releases</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/16313/project-assistant-position-at-jmi</guid>
  <pubDate>Fri, 12 Sep 2014 00:37:44 -0500</pubDate>
  <link></link>
  <title><![CDATA[Project Assistant Position at JMI]]></title>
  <description><![CDATA[
<p>Project Assistant Position (@ Rs.10,000/pm Fixed) is available for one year ina research project funded by the Department of Science and Technology entitled, "Folding and stability of naturally truncated photosynthetic pigment,C- phycoerythrin from cyanobacterium Phormidium tenue", at Centre forInterdisciplinary Research in Basic Sciences, lamia Millia Islamia, New Delhi-110025 under' the supervision of Dr. Md. Imtaiyaz Hassan (PrincipalInvestigator).</p>

<p>Eligibility:<br />M.Sc. in any stream of Life Sciences with minimum 55% marks.</p>

<p>Desirable:<br />Candidates having experience in Molecular Spectroscopy, Protein Folding and Bioinformatics will be preferred.</p>

<p>Interested candidate may appear in the walk in Interview conducted on September 16, 2014 (Tuesday) 11:00 AM in the Director's Office, Centre for Interdisciplinary Research in Basic Sciences, lamia Millia Islamia, New Delhi-110025.<br />Candidates are required to bring a set of Xerox copy of their recent CV and qualifying degree (certificate/mark sheet) along with original documents. NoTA/DA will be paid.</p>

<p>For any further information you may e-mail to: mihassan@jmLac.in</p>

<p>Read more at http://jmi.ac.in/upload/advertisement/jobs_cirbs_2014september8.pdf</p>
]]></description>
</item>

</channel>
</rss>