<?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/26309?offset=1720</link>
	<atom:link href="https://bioinformaticsonline.com/related/26309?offset=1720" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	
<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/43001/gamper-lab</guid>
  <pubDate>Fri, 26 Mar 2021 07:45:02 -0500</pubDate>
  <link></link>
  <title><![CDATA[Gamper Lab]]></title>
  <description><![CDATA[
<p>Lab focuses on examining the mechanisms governing the signalling pathways from DNA damage sensing to the activation of stress-response genes. The long-term goal is to find proteins that are drug targets for cancer treatment (such as radiosensitizers for radiation therapy) or biomarkers that increase the predictive value of therapeutic outcome.</p>

<p>https://amgamper.weebly.com/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/7568/oldest-hominin-dna-sequenced</guid>
	<pubDate>Fri, 27 Dec 2013 19:58:31 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/7568/oldest-hominin-dna-sequenced</link>
	<title><![CDATA[Oldest Hominin DNA Sequenced]]></title>
	<description><![CDATA[<p>Matthias Meyer and his team from the Max Planck Institute for Evolutionary Anthropology in Leipzig, Germany, have developed new techniques for retrieving and sequencing highly degraded ancient DNA. They then joined forces with Juan-Luis Arsuaga and applied the new techniques to a cave bear from the Sima de los Huesos site. After this success, the researchers sampled two grams of bone powder from a hominin thigh bone from the cave. They extracted its DNA and sequenced the genome of the mitochondria or mtDNA, a small part of the genome that is passed down along the maternal line and occurs in many copies per cell. The researchers then compared this ancient mitochondrial DNA with Neandertals, Denisovans, present-day humans, and apes.<br /><br />From the missing mutations in the old DNA sequences the researchers calculated that the Sima hominin lived about 400,000 years ago. They also found that it shared a common ancestor with the Denisovans, an extinct archaic group from Asia related to the Neandertals, about 700,000 years ago. "The fact that the mtDNA of the Sima de los Huesos hominin shares a common ancestor with Denisovan rather than Neandertal mtDNAs is unexpected since its skeletal remains carry Neandertal-derived features," says Matthias Meyer. Considering their age and Neandertal-like features, the Sima hominins were likely related to the population ancestral to both Neandertals and Denisovans. Another possibility is that gene flow from yet another group of hominins brought the Denisova-like mtDNA into the Sima hominins or their ancestors.<br /><br /></p><p>Reference</p><p>http://www.sciencedaily.com/releases/2013/12/131204132018.htm</p>]]></description>
	<dc:creator>Surajeet</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/4107/natasa-przulj-lab</guid>
  <pubDate>Fri, 30 Aug 2013 06:29:17 -0500</pubDate>
  <link></link>
  <title><![CDATA[Nataša Pržulj Lab]]></title>
  <description><![CDATA[
<p>Nataša Pržulj Lab's research involves applications of graph theory, mathematical modeling, and computational techniques to solving large-scale problems in computational and systems biology.They are interested in computational and theoretical solutions to practical problems in many areas of systems biology, planar cell polarity, proteomics, cancer informatics, and drug discovery and design.</p>

<p>More at http://www.doc.ic.ac.uk/~natasha/index.html</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/7986/list-of-bioinformatics-open-source-projectssoftware</guid>
	<pubDate>Tue, 21 Jan 2014 14:28:37 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/7986/list-of-bioinformatics-open-source-projectssoftware</link>
	<title><![CDATA[List of bioinformatics open source projects/software.]]></title>
	<description><![CDATA[<p>Open source software is software that can be freely used, changed, and shared (in modified or unmodified form) by anyone. Open source software is made by many people, and distributed under licenses that comply with the Open Source Definition.The Open Source Initiative (OSI) is a global non-profit that supports and promotes the open source movement. Followings are the OS bioinformatics projects/software :</p><p><strong>.NET Bio</strong></p><p>http://blogs.msdn.com/b/msr_er/archive/2011/10/18/microsoft-biology-foundation-evolves-into-new-toolkit-net-bio.aspx</p><p>A language-neutral bioinformatics toolkit built using the Microsoft 4.0 .NET Framework to help developers, researchers, and scientists.</p><p><strong>AMPHORA</strong> ("AutoMated Phylogenomic infeRence Application")</p><p>http://wolbachia.biology.virginia.edu/WuLab/Software.html</p><p><a href="http://en.wikipedia.org/wiki/Metagenomics" title="Metagenomics">Metagenomics</a> analysis software</p><p><strong>Anduril</strong></p><p>http://www.anduril.org/anduril/site/</p><p>Component-based <a href="http://en.wikipedia.org/wiki/Workflow" title="Workflow">workflow</a> framework for data analysis</p><p>Armadillo workflow platform</p><p>Tool for designing and executing phylogenetic workflows</p><p><strong>AutoDock</strong></p><p>http://autodock.scripps.edu/</p><p>suite of automated docking tools</p><p><strong>Biochemical Algorithms Library (BALL)</strong></p><p>http://www.ball-project.org/</p><p>C++ library and framework for molecular modeling and visualization designed for rapid prototyping</p><p><strong>Bio4j</strong></p><p>http://bio4j.com/</p><p>Bio4j is a <a href="http://en.wikipedia.org/wiki/Bioinformatics" title="Bioinformatics">bioinformatics</a> platform and <a href="http://en.wikipedia.org/wiki/Chart" title="Chart">graph</a> based <a href="http://en.wikipedia.org/wiki/Database" title="Database">database</a> built around most data available in <a href="http://en.wikipedia.org/wiki/UniProt" title="UniProt">UniProt</a> KB(<a href="http://en.wikipedia.org/wiki/Swiss-Prot" title="Swiss-Prot">Swiss-Prot</a> + <a href="http://en.wikipedia.org/wiki/TrEMBL" title="TrEMBL">TrEMBL</a>), <a href="http://en.wikipedia.org/wiki/Gene_Ontology" title="Gene Ontology">Gene Ontology</a> (GO), <a href="http://en.wikipedia.org/w/index.php?title=UniRef&amp;action=edit&amp;redlink=1" title="UniRef (page does not exist)">UniRef</a> (50,90,100), <a href="http://en.wikipedia.org/wiki/RefSeq" title="RefSeq">RefSeq</a>, <a href="http://en.wikipedia.org/wiki/National_Center_for_Biotechnology_Information" title="National Center for Biotechnology Information">NCBI</a> taxonomy, and Expasy Enzyme DB</p><p><strong>Bioclipse</strong></p><p>www.bioclipse.net</p><p>Visual platform for <a href="http://en.wikipedia.org/wiki/Cheminformatics" title="Cheminformatics">chemo</a>- and <a href="http://en.wikipedia.org/wiki/Bioinformatics" title="Bioinformatics">bioinformatics</a> based on the <a href="http://en.wikipedia.org/wiki/Eclipse_%28software%29" title="Eclipse (software)">Eclipse</a> Rich Client Platform (RCP).</p><p><strong>Bioconductor</strong></p><p>http://www.bioconductor.org/</p><p><a href="http://en.wikipedia.org/wiki/R_%28programming_language%29" title="R (programming language)">R (programming language)</a> language toolkit</p><p><strong>Bioinformatics Learning Tutorial (BLT)</strong></p><p>http://sourceforge.net/projects/biotutorial/</p><p>Educational <a href="http://en.wikipedia.org/wiki/Interactive_tutorials" title="Interactive tutorials">interactive tutorials</a> and 3D animations for Replication, Transcription, and Translation</p><p><strong>BioHaskell</strong></p><p>http://biohaskell.org/</p><p><a href="http://en.wikipedia.org/wiki/Haskell_%28programming_language%29" title="Haskell (programming language)">Haskell (programming language)</a></p><p><strong>BioJava</strong></p><p>http://biojava.org/wiki/Main_Page</p><p><a href="http://en.wikipedia.org/wiki/Java_%28programming_language%29" title="Java (programming language)">Java (programming language)</a></p><p><strong>BioMOBY</strong></p><p>http://biomoby.org/</p><p>registry of <a href="http://en.wikipedia.org/wiki/Web_services" title="Web services">web services</a></p><p><strong>BioPerl</strong></p><p>http://www.bioperl.org/wiki/Main_Page</p><p><a href="http://en.wikipedia.org/wiki/Perl" title="Perl">Perl</a> language toolkit</p><p><strong>BioPHP</strong></p><p>http://www.biophp.org/</p><p><a href="http://en.wikipedia.org/wiki/PHP" title="PHP">PHP</a> language toolkit</p><p><strong>Biopython</strong></p><p>http://biopython.org/wiki/Main_Page</p><p><a href="http://en.wikipedia.org/wiki/Python_%28programming_language%29" title="Python (programming language)">Python</a> language toolkit</p><p><strong>BioRails</strong></p><p>https://github.com/biorails</p><p>a <a href="http://en.wikipedia.org/wiki/Data_management_system" title="Data management system">data management system</a> designed to support researchers in <a href="http://en.wikipedia.org/wiki/Drug_discovery" title="Drug discovery">drug discovery</a></p><p><strong>BioRuby</strong></p><p>http://bioruby.org/</p><p><a href="http://en.wikipedia.org/wiki/Ruby_%28programming_language%29" title="Ruby (programming language)">Ruby</a> language toolkit</p><p><strong>BioSmalltalk</strong></p><p>https://code.google.com/p/biosmalltalk/</p><p><a href="http://en.wikipedia.org/wiki/Smalltalk_%28programming_language%29" title="Smalltalk (programming language)">Smalltalk</a> language toolkit</p><p><strong>BioUno</strong></p><p>http://www.biouno.org/</p><p><a href="http://en.wikipedia.org/w/index.php?title=BioUno&amp;action=edit&amp;redlink=1" title="BioUno (page does not exist)">BioUno</a> is a project that applies <a href="http://en.wikipedia.org/wiki/Continuous_Integration" title="Continuous Integration">Continuous Integration</a> tools and techniques in <a href="http://en.wikipedia.org/wiki/Bioinformatics" title="Bioinformatics">Bioinformatics</a>. It uses <a href="http://en.wikipedia.org/wiki/Jenkins_%28software%29" title="Jenkins (software)">Jenkins</a> and its plug-in API to create <a href="http://en.wikipedia.org/wiki/Bioinformatics_workflow_management_system" title="Bioinformatics workflow management system">biology workflows</a> and manage <a href="http://en.wikipedia.org/wiki/Computer_clusters" title="Computer clusters">computer clusters</a>.</p><p><strong>caCORE</strong></p><p>&nbsp;</p><p>ontologic representation environment</p><p><strong>caArray</strong></p><p>https://cabig-stage.nci.nih.gov/community/tools/caArray</p><p>ontologic representation environment</p><p><strong>EMBOSS</strong></p><p>http://emboss.sourceforge.net/</p><p>Suite of packages for sequencing, searching, etc.</p><p><strong>Gaggle</strong></p><p>https://www.gaggle.net/</p><p>A framework for interoperability between systems biology software</p><p><strong>Galaxy</strong></p><p>http://galaxyproject.org/</p><p><a href="http://en.wikipedia.org/wiki/Scientific_workflow_system" title="Scientific workflow system">Scientific workflow</a> and <a href="http://en.wikipedia.org/wiki/Data_integration" title="Data integration">data integration</a> system</p><p><strong>GenePattern</strong></p><p>http://www.broadinstitute.org/cancer/software/genepattern/</p><p><a href="http://en.wikipedia.org/wiki/Scientific_workflow_system" title="Scientific workflow system">Scientific workflow system</a> that provides access to more than 150 genomic analysis tools</p><p><strong>GeWorkbench</strong></p><p>http://wiki.c2b2.columbia.edu/workbench/index.php/Home</p><p>Genomic <a href="http://en.wikipedia.org/wiki/Data_integration" title="Data integration">data integration</a> platform</p><p><strong>GMOD</strong></p><p>http://www.gmod.org/wiki/Main_Page</p><p>Toolkit for addressing many common challenges at biological databases.</p><p><strong>GeneProf</strong></p><p>http://www.geneprof.org/GeneProf/</p><p>A web-based, bioinformatics software suite for the analysis of functional genomics experiments, e.g. RNA-seq or ChIP-seq.</p><p><strong>GeneTalk</strong></p><p>http://www.gene-talk.de/</p><p>Tool for filtering sequence variants in <a href="http://en.wikipedia.org/wiki/Variant_Call_Format" title="Variant Call Format">VCF</a> files. Network for scientists and clinicians for expertise and knowledge exchange. Database of annotations aboute sequence variants with clinically relevant information.</p><p><strong>GenGIS</strong></p><p>http://kiwi.cs.dal.ca/GenGIS/Main_Page</p><p>Application that allows users to combine digital map data with information about biological sequences collected from the environment.</p><p><strong>GenomeSpace</strong></p><p>http://www.genomespace.org/</p><p>Centralized web application that provides data format transformations and facilitates connections with other bioinformatics tools</p><p><strong>GENtle</strong></p><p>http://directory.fsf.org/wiki/GENtle</p><p>An equivalent to the proprietary <a href="http://en.wikipedia.org/wiki/Vector_NTI" title="Vector NTI">Vector NTI</a>, a tool to analyze and edit <a href="http://en.wikipedia.org/wiki/DNA" title="DNA">DNA</a> sequence files</p><p><strong>Integrated Genome Browser</strong></p><p>http://bioviz.org/igb/</p><p><a href="http://en.wikipedia.org/wiki/Java_%28software_platform%29" title="Java (software platform)">Java</a>-based desktop <a href="http://en.wikipedia.org/wiki/Genome_browser" title="Genome browser">genome browser</a></p><p><strong>Integrative Genomics Viewer (IGV)</strong></p><p>http://www.broadinstitute.org/igv/</p><p>High-performance desktop tool for interactive visual exploration of diverse genomic data</p><p><strong>IntAct</strong></p><p>http://www.ebi.ac.uk/intact/</p><p>molecular interaction database</p><p><strong>InterMine</strong></p><p>http://intermine.github.io/intermine.org/</p><p>Extensive data warehouse system for the analysis and integration of biological datasets</p><p><strong>Java Treeview</strong></p><p>http://jtreeview.sourceforge.net/</p><p>microarray data viewer</p><p><strong>LabKey Server</strong></p><p>http://labkey.com/</p><p>platform for integrating, analyzing and sharing data</p><p><strong>OpenClinica</strong></p><p>https://www.openclinica.com/</p><p>software for capturing and managing data in clinical trials</p><p><a href="http://www.biomedcentral.com/1471-2164/13/512">PromKappa</a></p><p>http://xbioinformatics.wordpress.com/tag/promkappa/</p><p>PromKappa (Promoter analysis by Kappa) software program used for promoter pattern generation and promoter analysis.</p><p><strong>MeV: Multi-Experiment Viewer</strong></p><p>http://www.tm4.org/mev.html</p><p>a desktop application for the analysis, visualization and data-mining of large-scale genomic data</p><p><strong>PathVisio</strong></p><p>http://www.pathvisio.org/</p><p>a desktop software for drawing, analysis and visualization of biological pathways</p><p>REDCRAFT</p><p>software for determining tertiary protein structure given assigned Residual Dipolar Coupling data</p><p>SAM Tools</p><p>Data format (SAM) and accompanying tool suite, for storing large nucleotide sequence alignments</p><p><a href="http://en.wikipedia.org/wiki/Staden_Package" title="Staden Package">Staden Package</a></p><p>Sequence assembly, editing and analysis, primarily consisting of gap4, gap5 and spin.</p><p><a href="http://en.wikipedia.org/wiki/STAMP" title="STAMP">STAMP</a></p><p>Software package for analyzing metagenomic profiles that promotes &lsquo;best practices&rsquo; in choosing appropriate statistical techniques and reporting results.</p><p><a href="http://supfam.org/supraHex">supraHex</a></p><p>An open-source R/Bioconductor package for omics data analysis using a supra-hexagonal map</p><p><a href="http://en.wikipedia.org/wiki/Taverna_workbench" title="Taverna workbench">Taverna workbench</a></p><p>Tool for designing and executing workflows</p><p>TGAC Browser</p><p>Genome Browser, visualisation solutions for big data in the genomic era</p><p>T-REX WebServer</p><p>Bioinformatics and phylogenetics webserver (NJ, PhyML, RAxML, MAFFT, MUSCLE, Newick viewer, <a href="http://en.wikipedia.org/wiki/Horizontal_gene_transfer" title="Horizontal gene transfer">Horizontal gene transfer</a> detection, Reticulograms, Substitution models)</p><p><a href="http://en.wikipedia.org/wiki/UGENE" title="UGENE">UGENE</a></p><p>integrated bioinformatics tools</p><p>Visomics</p><p>bioinformatics tools for omics data</p><p>Genome Analysis Toolkit 1.0 (GATK 1.0)</p><p>a software package to analyse next-generation resequencing data</p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/24984/ra-bioinformatics-at-nii</guid>
  <pubDate>Thu, 22 Oct 2015 01:56:26 -0500</pubDate>
  <link></link>
  <title><![CDATA[RA Bioinformatics at NII]]></title>
  <description><![CDATA[
<p>NATIONAL INSTITUTE OF IMMUNOLOGY</p>

<p>NEW DELHI-110067</p>

<p>Applications are invited for the position of Research Associate (RA) for the following time-bound sponsored project as per the details given below:</p>

<p>1. BTIS project entitled, “National Infrastructural Facility in the Area of Immunology” funded by DBT</p>

<p>Research Associate (One Position only)</p>

<p>Dr. Debasisa Mohanty Staff Scientist-VI deb@nii.res.in</p>

<p>Educational Qualifications: Ph.D in Bioinformatics or Biological Sciences or Biotechnology with research experience and publication record in indexed peer reviewed journals in the area of bioinformatics or computational biology.</p>

<p>Emoluments: The selected candidates will draw consolidated emoluments as per Institute Rules, depending upon qualifications &amp; experience Research Associate: Rs. 36,000/- per month plus 30% HRA</p>

<p>Job description &amp; Desired Knowledge: The candidate should be well versed in Programming in PERL/C++, HTML, CGI, web sever and portal development, computational analysis of protein structure &amp; function, molecular dynamics simulations and use of high performance computing systems.</p>

<p>General Terms &amp; Conditions:-</p>

<p>1. The candidates selected for the above posts will be on contract for one year or duration of the project whichever is shorter, at a time.</p>

<p>2. No hostel/ housing facility will be provided.</p>

<p>3. Applicants may clearly mention the category they belong to i.e. SC/ST/OBC/PH and attach documentary proof of the same.</p>

<p>4. No TA/DA will be paid for attending the interview, if called for.</p>

<p>5. Apart from sending application in the prescribed format given below, candidates should send complete Curriculum Vitae along with the names of three referees. Curriculum Vitae should contain details of the experimental expertise and list of publications. 6. Canvassing in any form will be a disqualification.</p>

<p>HOW TO APPLY Interested candidates may apply directly, STRICTLY IN THE PRESCRIBED FORMAT GIVEN BELOW, through e-mail, to the Investigator of the project, clearly indicating the name of the project along with their complete C.V., Email ID, fax numbers, telephone numbers. Only Short listed candidates will be called for interview and they required to submit attested copies of all their certificates and a Demand Draft of Rs 100/- drawn on Canara Bank or Indian Bank payable at Delhi/New Delhi in favour of the Director, NII (SC/ST/PH and Women candidates are exempted from payment of fees) subject to submission of documentary proof), at the time of interview. (E-MAIL APPLICATIONS SHOULD MENTION BTIS-RA 2015 IN THE SUBJECT LINE)</p>

<p>LAST DATE OF RECEIPT OF APPLICATIONS: 29th October, 2015</p>

<p>Advertisement:</p>

<p>www1.nii.res.in/sites/default/files/projectappointments-Dr.Mohanty-29oct2015.pdf</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/bookmarks/view/34377/genomicus-genome-browser-that-enables-users-to-navigate-in-genomes-in-several-dimensions</guid>
	<pubDate>Sat, 18 Nov 2017 16:10:16 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34377/genomicus-genome-browser-that-enables-users-to-navigate-in-genomes-in-several-dimensions</link>
	<title><![CDATA[Genomicus: genome browser that enables users to navigate in genomes in several dimensions]]></title>
	<description><![CDATA[<p>Genomicus is a genome browser that enables users to navigate in genomes in several dimensions: linearly along chromosome axes, transversaly across different species, and chronologicaly along evolutionary time.</p>
<p>Once a query gene has been entered, it is displayed in its genomic context in parallel to the genomic context of all its orthologous and paralogous copies in all the other sequenced metazoan genomes. Moreover, Genomicus stores and displays the predicted ancestral genome structure in all the ancestral species within the phylogenetic range of interest.</p>
<p>All the data on extant species displayed in this browser are from&nbsp;<a href="http://www.ensembl.org/">Ensembl</a>.</p><p>Address of the bookmark: <a href="http://genomicus.biologie.ens.fr/genomicus-90.01/cgi-bin/search.pl" rel="nofollow">http://genomicus.biologie.ens.fr/genomicus-90.01/cgi-bin/search.pl</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</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/bookmarks/view/34715/delta-a-new-web-based-3d-genome-visualization-and-analysis-platform</guid>
	<pubDate>Wed, 20 Dec 2017 08:49:55 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34715/delta-a-new-web-based-3d-genome-visualization-and-analysis-platform</link>
	<title><![CDATA[Delta: a new Web-based 3D genome visualization and analysis platform]]></title>
	<description><![CDATA[<p><em>Delta</em><span>&nbsp;is an integrative visualization and analysis platform to facilitate visually annotating and exploring the 3D physical architecture of genomes.&nbsp;</span><em>Delta</em><span>&nbsp;takes Hi-C or ChIA-PET contact matrix as input and predicts the topologically associating domains and chromatin loops in the genome. It then generates a physical 3D model which represents the plausible consensus 3D structure of the genome.&nbsp;</span><em>Delta</em><span>features a highly interactive visualization tool which enhances the integration of genome topology/physical structure with extensive genome annotation by juxtaposing the 3D model with diverse genomic assay outputs.</span></p>
<p>https://github.com/zhangzhwlab/delta</p><p>Address of the bookmark: <a href="https://github.com/zhangzhwlab/delta" rel="nofollow">https://github.com/zhangzhwlab/delta</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35384/mgcv-the-microbial-genomic-context-viewer-for-comparative-genome-analysis</guid>
	<pubDate>Mon, 29 Jan 2018 04:55:46 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35384/mgcv-the-microbial-genomic-context-viewer-for-comparative-genome-analysis</link>
	<title><![CDATA[MGcV: the microbial genomic context viewer for comparative genome analysis]]></title>
	<description><![CDATA[<p><span>MGcV is an interactive web-based visalization tool tailored to facilitate small scale genome analysis. To start using MGcV:</span></p>
<ol>
<li>Supply your genes/genomic segments/phylogenetic tree of interest in the input-box by
<ul>
<li>selecting the type of identifier and pasting identifiers (one per line)</li>
<li><em><strong>or</strong></em>&nbsp;by using the&nbsp;<a>gene ID search tool</a></li>
<li><em><strong>or</strong></em>&nbsp;with the&nbsp;<a>BLAST search tool</a></li>
</ul>
</li>
<li>Click "Visualize context".</li>
</ol>
<p><span>Consult the&nbsp;</span><a href="http://mgcv.cmbi.ru.nl/help.html" target="_blank">documentation</a><span>&nbsp;to learn more about MGcV.</span></p><p>Address of the bookmark: <a href="http://mgcv.cmbi.ru.nl/" rel="nofollow">http://mgcv.cmbi.ru.nl/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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