<?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/41493?offset=450</link>
	<atom:link href="https://bioinformaticsonline.com/related/41493?offset=450" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	
<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/43329/postdoc-position-at-kiel-university-germany</guid>
  <pubDate>Sat, 28 Aug 2021 01:16:55 -0500</pubDate>
  <link></link>
  <title><![CDATA[Postdoc position at Kiel University, Germany]]></title>
  <description><![CDATA[
<p>In the Genomic Microbiology Group of Prof. Tal Dagan at the Institute<br />of Microbiology at Kiel University, Germany, a</p>

<p>Postdoc position (m/w/d)</p>

<p>in the field of computational evolutionary microbiology is available<br />for an initially limited period of 36 months at the earliest possible<br />date. The weekly working time corresponds to 100% of full employment<br />(If the legal requirements under collective bargaining law are met, the<br />tariff grouping is carried out up to pay scale 13 TV-L. The obligation<br />to teach amounts to 4 hours.</p>

<p>The Genomic Microbiology Group research interests are focused on<br />microbial genome evolution with an emphasis on the study of lateral gene<br />transfer. In our research we use both computational and experimental<br />approaches (see www.uni-kiel.de/genomik). The position offers the<br />opportunity to develop an independent research profile within the group<br />research focus. The successful applicant is expected to be involved<br />in teaching of bioinformatics and molecular evolution, including the<br />development of teaching materials (lectures/exercises/short videos).</p>

<p>Your profile:<br />· Doctoral or PhD degree in Molecular Evolution, Bioinformatics or<br />related fields.<br />· Knowledge and experience in programming (e.g., Python) and<br />biostatistical analysis (e.g., with R or MatLab).<br />· Any of the following expertise is an advantage: the analysis of<br />genomic or transcriptomic data, phylogenetic reconstruction,<br />comparative genomics.<br />· Good oral and written communication skills in English.<br />· Ability to teach in German is an advantage (alternatively, an<br />indication to do so from the 2nd year on).<br />· Skills and motivation to communicate and interact with other<br />scientists.<br /> <br />The Christian-Albrechts-University sees itself as a modern and<br />cosmopolitan employer. We welcome your application regardless of your age,<br />gender, cultural and social background, religion, ideology, disability<br />or sexual identity. We promote equality of the sexes.</p>

<p>The Christian-Albrechts-University is committed to the employment of<br />people with disabilities. Preference will be given to applications from<br />severely handicapped persons and persons of equal standing, provided<br />they are suitable.</p>

<p>We expressly welcome applications from people with a migration background.</p>

<p>For enquiries regarding the position, teaching obligations and research<br />topic please contact Prof. Tal Dagan: tdagan@ifam.uni-kiel.de.</p>

<p>Applications should be submitted by email to Mrs. Haacks<br />(dhaacks@ifam.uni-kiel.de) as a single PDF and include: (1) a letter of<br />motivation (max 1 page, Arial 11, line spacing 1.15), (2) CV, (3) PhD<br />certificate. Please use 'GMG postdoc application - [your name]'<br />as a subject.</p>

<p>Please, refrain from sending us application photos.</p>

<p>Application deadline:  August 31 2021 or until the position is<br />filled. Interviews will take place during September/October 2021. The<br />planned starting date for the position is flexible (but in 2021).</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/44226/rotifers-lab</guid>
  <pubDate>Wed, 08 Mar 2023 23:23:14 -0600</pubDate>
  <link></link>
  <title><![CDATA[Rotifers Lab]]></title>
  <description><![CDATA[
<p>For scientists in the MBL’s Gribble Lab, the rotifer (Brachionus manjavacas) is used as a model organism to study evolution, stress responses, the biology of aging, and maternal effects. Rotifers are small, easy to grow in the lab, have a short lifespan, and share many of their genes with humans. That makes them ideal specimens in which to address questions relevant to human health as well as understand basic biological and evolutionary processes. Brachionus rotifers produces eggs that can be completely dried and frozen for decades, then hatch within a day when exposed to water and light.</p>

<p>https://www.mbl.edu/research/research-organisms/rotifer<br />https://gribblebiolab.org/</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/4546/sowdhamini-lab</guid>
  <pubDate>Sun, 15 Sep 2013 09:19:12 -0500</pubDate>
  <link></link>
  <title><![CDATA[SOWDHAMINI Lab]]></title>
  <description><![CDATA[
<p>Genome sequencing projects have enormous potential for benefiting human endeavors. However, just as acquiring a language's vocabulary does not enable one to speak it, databases that list the amino acid composition of proteins do not directly tell us much about these proteins' higher-level structure and function. The most productive way to indirectly exploit these databases has been to start with the small number of proteins that are fully-characterised and to assume that other "similar" proteins will have a related structure and function. Proteins with very similar amino acid sequence are "no-brainers", but the real test, which our group largely focuses on, is to detect the "essential" similarity in proteins whose non-critical sections have experienced random rearrangements during evolution. In such cases functionally similar proteins may have less than 25% sequence overlap.</p>

<p>More @ http://www.ncbs.res.in/sowdhamini/groups_sowdhamini.htm</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37794/mimicree2-genome-wide-forward-simulations-of-evolve-and-resequencing-studies</guid>
	<pubDate>Fri, 28 Sep 2018 09:21:14 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37794/mimicree2-genome-wide-forward-simulations-of-evolve-and-resequencing-studies</link>
	<title><![CDATA[MimicrEE2: Genome-wide forward simulations of Evolve and Resequencing studies]]></title>
	<description><![CDATA[<p><span>MimicrEE2, a multi-threaded Java program for genome-wide forward simulations of evolving populations. MimicrEE2 enables the convenient usage of available genomic resources, supports biological particulars of model organism frequently used in E&amp;R studies and offers a wide range of different adaptive models (selective sweeps, polygenic adaptation, epistasis). MimicrEE2 runs on any computer with Java installed. It is distributed under the GPLv3 license at&nbsp;</span><a href="https://sourceforge.net/projects/mimicree2/">https://sourceforge.net/projects/mimicree2/</a><span>.</span></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/mimicree2/" rel="nofollow">https://sourceforge.net/projects/mimicree2/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/43769/ideaslab-workshop</guid>
  <pubDate>Wed, 02 Feb 2022 06:13:48 -0600</pubDate>
  <link></link>
  <title><![CDATA["IdeasLab"* workshop !]]></title>
  <description><![CDATA[
<p>A new, grant-funded opportunity seeks early career researchers interested<br />in life's origins: https://templetonideaslab.umbc.edu/</p>

<p>Applications are invited to an all-expenses paid position at a 5-day<br />"IdeasLab"* workshop to be held near Prague CZ in June 2022. Thirty<br />successful applicants will be drawn in equal number from the relevant<br />sectors biological evolution, A-Life anbd theoretical physics. The week's<br />activities will lead these thirty to form interdisciplinary teams which<br />each propose how they can advance frontiers of abiogenesis research. Up to<br />$5 million total funding will be available for developing these ideas<br />produced by the week's activities. Further details of the event,<br />including the online application form, are found at the link posted above</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44525/synorth-exploring-the-evolution-of-synteny-and-long-range-regulatory-interactions-in-vertebrate-genomes</guid>
	<pubDate>Mon, 06 May 2024 06:21:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44525/synorth-exploring-the-evolution-of-synteny-and-long-range-regulatory-interactions-in-vertebrate-genomes</link>
	<title><![CDATA[Synorth: exploring the evolution of synteny and long-range regulatory interactions in vertebrate genomes]]></title>
	<description><![CDATA[<p><span>Genomic regulatory blocks are chromosomal regions spanned by long clusters of highly conserved noncoding elements devoted to long-range regulation of developmental genes, often immobilizing other, unrelated genes into long-lasting syntenic arrangements. Synorth&nbsp;</span><a href="http://synorth.genereg.net/" target="_blank">http://synorth.genereg.net/</a><span>&nbsp;is a web resource for exploring and categorizing the syntenic relationships in genomic regulatory blocks across multiple genomes, tracing their evolutionary fate after teleost whole genome duplication at the level of genomic regulatory block loci, individual genes, and their phylogenetic context.</span></p>
<p><span>More at&nbsp;https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2745767/</span></p><p>Address of the bookmark: <a href="http://synorth.genereg.net/" rel="nofollow">http://synorth.genereg.net/</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</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/34519/bandage-interactive-visualization-of-de-novo-genome-assemblies</guid>
	<pubDate>Mon, 04 Dec 2017 10:09:37 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34519/bandage-interactive-visualization-of-de-novo-genome-assemblies</link>
	<title><![CDATA[Bandage: interactive visualization of de novo genome assemblies]]></title>
	<description><![CDATA[<p>Bandage (a Bioinformatics Application for Navigating&nbsp;<em>De&nbsp;novo</em>&nbsp;Assembly Graphs Easily) is a tool for visualizing assembly graphs with connections. Users can zoom in to specific areas of the graph and interact with it by moving nodes, adding labels, changing colors and extracting sequences. BLAST searches can be performed within the Bandage graphical user interface and the hits are displayed as highlights in the graph. By displaying connections between contigs, Bandage presents new possibilities for analyzing&nbsp;<em>de novo</em>&nbsp;assemblies that are not possible through investigation of contigs alone.</p>
<p><strong>Availability and implementation:</strong>&nbsp;Source code and binaries are freely available at&nbsp;<a href="https://github.com/rrwick/Bandage" target="pmc_ext">https://github.com/rrwick/Bandage</a>. Bandage is implemented in C++ and supported on Linux, OS X and Windows. A full feature list and screenshots are available at&nbsp;<a href="http://rrwick.github.io/Bandage" target="pmc_ext">http://rrwick.github.io/Bandage</a>.</p><p>Address of the bookmark: <a href="http://rrwick.github.io/Bandage/" rel="nofollow">http://rrwick.github.io/Bandage/</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/34685/tools-for-bacterial-whole-genome-annotation</guid>
	<pubDate>Sat, 16 Dec 2017 17:37:47 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/34685/tools-for-bacterial-whole-genome-annotation</link>
	<title><![CDATA[Tools for bacterial whole genome annotation]]></title>
	<description><![CDATA[<p><a href="http://rast.nmpdr.org/">RAST</a>&nbsp;&ndash;&nbsp;Web tool (upload contigs), uses the subsystems in the SEED database and&nbsp;provides detailed annotation and pathway analysis. Takes several hours per genome but I think this is the best way to get a high quality annotation (if you have only a few genomes to annotate).</p><p><a href="http://www.vicbioinformatics.com/software.prokka.shtml">Prokka</a>&nbsp;&ndash;&nbsp;Standalone command line tool, takes just a few minutes per genome.&nbsp;This is the best way to get good quality annotation in a flash, which is particularly useful if you have loads of genomes or need to annotate a pangenome or metagenome. Note however that the quality of functional information is not as good as RAST, and you&nbsp;will need several extra steps if you want to do&nbsp;functional profiling and pathway analysis of your genome(s)&hellip; which is in-built in RAST.</p><p>NCBI Prokaryotic Genome Annotation Pipeline is designed to annotate bacterial and archaeal genomes (chromosomes and plasmids).</p><p>Genome annotation is a multi-level process that includes prediction of protein-coding genes, as well as other functional genome units such as structural RNAs, tRNAs, small RNAs, pseudogenes, control regions, direct and inverted repeats, insertion sequences, transposons and other mobile elements.</p><p><a href="https://www.ncbi.nlm.nih.gov/genome/annotation_prok/">PGAP</a>: NCBI has developed an automatic prokaryotic genome annotation pipeline that combines&nbsp;<em>ab initio</em>&nbsp;gene prediction algorithms with homology based methods. The first version of NCBI Prokaryotic Genome Automatic Annotation Pipeline (PGAAP;&nbsp;<a href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=pubmed&amp;dopt=Abstract&amp;list_uids=18416670">see Pubmed Article</a>) developed in 2005 has been replaced with an upgraded version that is capable of processing a larger data volume.&nbsp; NCBI's annotation pipeline depends on several internal databases and is not currently available for download or use outside of the NCBI environment.</p><p><a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC453985">BEACON</a> (automated tool for Bacterial GEnome Annotation ComparisON), a fast tool for an automated and a systematic comparison of different annotations of single genomes. The extended annotation assigns putative functions to many genes with unknown functions. BEACON is available under GNU General Public License version 3.0 and is accessible at:&nbsp;<a href="http://www.cbrc.kaust.edu.sa/BEACON/" target="pmc_ext">http://www.cbrc.kaust.edu.sa/BEACON/</a>.</p><p><a href="http://www.kegg.jp/blastkoala/">BlastKOLA</a>: Assigns K numbers to the user's sequence data by BLAST searches, respectively, against a nonredundant set of KEGG GENES. KOALA (KEGG Orthology And Links Annotation) is KEGG's internal annotation tool for K number assignment of KEGG GENES using SSEARCH computation. Annotate Sequence in KEGG Mapper and Pathogen Checker in KEGG Pathogen are special interfaces to this server and can be executed in an interactive mode. BlastKOALA is suitable for annotating fully sequenced genomes.</p><p><a href="http://www.sanger.ac.uk/science/tools/pagit">PAGIT</a>: Provides a toolkit for improving the quality of genome assemblies created via an assembly software. PAGIT compiled four tools: (i) ABACAS which classifies and orientates contigs and estimates the sizes of gaps between them; (ii) IMAGE uses paired-end reads to extend contigs and close gaps within the scaffolds; (iii) ICORN for identifying and correcting small errors in consensus sequences and; (iv) RATT for help annotation. The software was mainly created to analyze parasite genomes of up to about 300 Mb.</p><p><a href="http://www.yandell-lab.org/software/maker.html">MAKER: </a>A portable and easily configurable genome annotation pipeline. MAKER allows smaller eukaryotic and prokaryotic genome projects to independently annotate their genomes and to create genome databases. It identifies repeats, aligns ESTs and proteins to a genome, produces ab-initio gene predictions and automatically synthesizes these data into gene annotations having evidence-based quality values. MAKER's inputs are minimal and its ouputs can be directly loaded into a Generic Model Organism Database (GMOD). They can also be viewed in the Apollo genome browser; this feature of MAKER provides an easy means to annotate, view and edit individual contigs and BACs without the overhead of a database. MAKER is available for download and can be tested online via the MAKER Web Annotation Service (MWAS).</p><p><a href="https://www.sciencedirect.com/science/article/pii/S0167701215001207">MyPro</a> is a software pipeline for high-quality prokaryotic genome assembly and annotation. It was validated on 18 oral streptococcal strains to produce submission-ready, annotated draft genomes. MyPro installed as a virtual machine and supported by updated databases will enable biologists to perform quality prokaryotic genome assembly and annotation with ease.</p>]]></description>
	<dc:creator>Radha Agarkar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35135/alitv%E2%80%94interactive-visualization-of-whole-genome-comparisons</guid>
	<pubDate>Wed, 10 Jan 2018 07:08:17 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35135/alitv%E2%80%94interactive-visualization-of-whole-genome-comparisons</link>
	<title><![CDATA[AliTV—interactive visualization of whole genome comparisons]]></title>
	<description><![CDATA[<p>AliTV, which provides interactive visualization of whole genome alignments. AliTV reads multiple whole genome alignments or automatically generates alignments from the provided data. Optional feature annotations and phylo- genetic information are supported. The user-friendly, web-browser based and highly customizable interface allows rapid exploration and manipulation of the visualized data as well as the export of publication-ready high-quality figures. AliTV is freely available at&nbsp;<a href="https://github.com/AliTVTeam/AliTV">https://github.com/AliTVTeam/AliTV</a></p>
<p>https://alitvteam.github.io/AliTV/</p><p>Address of the bookmark: <a href="https://github.com/AliTVTeam/AliTV" rel="nofollow">https://github.com/AliTVTeam/AliTV</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

</channel>
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