<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/26179?offset=450 https://bioinformaticsonline.com/researchlabs/view/26234/manolis-kellis-lab Sun, 31 Jan 2016 20:51:06 -0600 <![CDATA[Manolis Kellis Lab]]> A major focus of our lab is understanding the effects of genetic variation on molecular phenotypes and human disease. We develop methods for integrating diverse functional genomic datasets of transcription, chromatin modifications, regulator binding, and their changes across multiple conditions to interpret genetic associations, identify causal variants, and predict the effects of genetic perturbations.

More at http://compbio.mit.edu

]]> https://bioinformaticsonline.com/opportunity/view/30331/16th-congress-of-the-european-society-for-evolutionary-biology-eseb Thu, 22 Dec 2016 08:08:37 -0600 <![CDATA[16th Congress of the European Society for Evolutionary Biology (ESEB)]]> Abstract submissions for our upcoming symposium on the Genomics of Adaptation that will take place as part of the 16th Congress of the European Society for Evolutionary Biology (ESEB). The conference will take place from August 20th - August 25th, 2017 in Groningen, the Netherlands.

SYMPOSIUM DESCRIPTION: Genomics of Adaptation [S16] Model organisms for life-history research are mainly studied in the lab where functional genetics is assessable. In general, however, knowledge about their eco-evolutionary dynamics, such as biotic interactions, is rare. By contrast, in organisms for which the ecology and adaptation strategies in the field are well known, we typically lack the appropriate genetic tools to investigate functionality. Advances in genomics and statistics as well as investments in evolutionary model organisms are now providing access to putatively adaptive genome-wide variation within species from across the tree of life. In this symposium, we focus on integrating life-history biology, genetics and evolutionary ecology in the genomics era.

We wish to (1) highlight the role of genetic architecture of complex traits, such as adaptations to biotic interactions or life-history traits; (2) contrast this to morphological traits which are generally thought to have a less complex genetic architecture; and (3) discuss the opportunities and drawbacks of specific model systems.

INVITED SPEAKERS: Josephine Pemberton, University of Cambridge (http://bit.ly/2hJWytJ ) Peter Tiffin, University of Minnesota (http://bit.ly/2hK7HuS )

ABSTRACT SUBMISSION The deadline for abstract submission is January 10, 2017. For more information and to submit abstracts online, please visit: http://bit.ly/2fBXlvN We look forward to an exciting symposium and seeing you all in Groningen! Sincerely, Ben Blackman, UC Berkeley Maaike de Jong, University of Bristol Bart Pannebakker, Wageningen University Noah Whiteman, UC Berkeley Jelle Zandveld, Wageningen University

]]> https://bioinformaticsonline.com/researchlabs/view/42903/katherine-belov-lab Sun, 21 Feb 2021 22:59:35 -0600 <![CDATA[Katherine Belov Lab]]> Evolution of the adaptive immune system Marsupial and monotreme immune genes MHC Diversity and Conservation Marsupial and monotreme genomics Comparative Genomics Genetics of Tasmanian Devil facial tumour disease

More at https://www.sydney.edu.au/science/about/our-people/academic-staff/kathy-belov.html

]]> https://bioinformaticsonline.com/opportunity/view/43823/the-helsinki-summer-school-on-mathematical-ecology-and-evolution Thu, 10 Mar 2022 01:06:28 -0600 <![CDATA[The Helsinki Summer School on Mathematical Ecology and Evolution]]> https://wiki.helsinki.fi/display/BioMath/The+Helsinki+Summer+School+on+Mathematical+Ecology+and+Evolution+2022

This is the seventh school of a biennial series of international summer schools on mathematical ecology and evolution in Finland, organised by the Biomathematics Group of the University of Helsinki. The series of The Helsinki Summer School on Mathematical Ecology and Evolution is part of the EMS-ESMTB Schools in Applied Mathematics.

After the two-year break forced upon by the pandemic, we are looking forward to continue this series in August 2022, if only the covid situation permits.

]]> https://bioinformaticsonline.com/opportunity/view/44727/postdoctoral-scholar-in-bacterial-evolution-at-pathogen-and-microbiome-institute-at-northern-arizona-university Fri, 13 Dec 2024 12:49:16 -0600 <![CDATA[Postdoctoral Scholar in Bacterial Evolution at Pathogen and Microbiome Institute at Northern Arizona University]]> We are pleased to announce a Postdoctoral Scholar position to study
bacterial evolution at the Pathogen and Microbiome Institute at
Northern Arizona University with Professor Paul Keim. The scholar
will have the opportunity also work with Professor Sam Sheppard at
The University of Oxford on joint projects. See our recent paper
on interspecific gene flow in Campylobacter. (DOI:
https://doi.org/10.1128/mbio.00581-24)

The job description: "This research position focuses on the science
of bacterial evolution. It will consist of researching theoretical
principles, but could include translational applications. Phylogenomic
and bioinformatic analysis of bacterial populations in nature or
in laboratory experiments will be a key component of the work. Prior
experience is an asset though training will be possible at PMI.
Likewise, laboratory microbiological, molecular, and biochemical
skills are an asset though not essential. Communication and critical
thinking skills are essential for performing the work and for
communicating to the local and international scientific communities.
Participating in team or independent grant writing to obtain research
funding will be required. Student mentoring is a part of the NAU
mission and is a partial expectation."

https://hr.peoplesoft.nau.edu/psp/ph92prta/EMPLOYEE/HRMS/c/HRS_HRAM.HRS_APP_SCHJOB.GBL?Page=HRS_APP_JBPST&Action=U&FOCUS=Applicant&SiteId=1&JobOpeningId=608024&PostingSeq=1

Northern Arizona University is located in Flagstaff, Arizona, a
beautiful mountain town with a surprisingly vibrant restaurant
scene. Located a little over an hour from the Grand Canyon and ~45
min from Sedona, Flagstaff is a hiker's paradise. In fact, the city
of Flagstaff operates more than 50 miles of unpaved trails and there
are, on average, 266 sunny days per year with which to enjoy them.
At 7000 ft in elevation, Flagstaff experiences all four seasons,
but thesummers are mild and, in the winter, you can be on the ski
slopes within 30 min! https://www.flagstaffarizona.org/

As mentioned, joint projects with Professor Sheppard at Oxford
University are possible, including travel to his laboratory in the
United Kingdom. https://www.biology.ox.ac.uk/people/samuel-sheppard

Contact Information:
Paul.Keim@nau.edu

Paul S. Keim, Ph.D.
Regents Professor, &
Cowden Endowed Chair of Microbiology
Northern Arizona University
Flagstaff, AZ 86011-4073

Paul S Keim

]]> https://bioinformaticsonline.com/opportunity/view/45115/postdoctoral-fellow-in-genomics-and-comparative-genomics Thu, 09 Apr 2026 02:12:32 -0500 <![CDATA[Postdoctoral Fellow in Genomics and Comparative Genomics]]> Environnement de travail (Work environment):
The successful candidate will join a dynamic research group working
on the ecology and evolution of host'parasite'environment
interactions in non-model organisms, particularly snail vectors and
its trematode parasites. She/He will conduct genomic analyses aimed at
understanding host'parasite coevolution and the genetic architecture
of resistance in the invasive snail Pseudosuccinea columella to the
zoonotic parasite Fasciola hepatica. This thematic line is embedded
within the regional scientific project InvaSnail financed by the
ExposUM initiative from the Montpellier. The position is based in
Montpellier, a vibrant scientific hub in Southern France internationally
recognized for excellence in ecology and evolutionary biology. The IHPE
laboratory provides a collaborative research environment with access
to high-performance computing facilities, sequencing platforms, and
strong interdisciplinary interactions across research institutions in
the Montpellier area. University

Main mission:

Develop and implement strategies for whole-genome sequencing of non-model
species
Generate high-quality de novo genome assemblies using short- and long-read
sequencing technologies
Perform genome annotation and structural/functional characterization
Conduct comparative genomic analyses across related species or populations
Design and implement genome-wide association studies (GWAS) to identify
loci associated with phenotypic or adaptive traits
Integrate genomic, phenotypic, and environmental datasets
Contribute to the development of reproducible bioinformatics pipelines

Activités (Activities):

Lead the genomic component of the research project
High-molecular-weight DNA extraction optimization
Long-read genome assembly (PacBio HiFi / ONT)
Genome polishing and quality assessment (BUSCO, QUAST)
Structural and functional annotation
Variant discovery (SNPs, indels, SVs)
Population genomic analyses (FST, demographic inference)
Mixed-model GWAS accounting for structure
Workflow development (Snakemake/Nextflow)
HPC-based pipeline implementation
Publish results in peer-reviewed journals
Present findings at international conferences
Collaborate with experimental and computational team members
Contribute to project development
Mentor graduate students when appropriate

More at https://evol.mcmaster.ca/brian/evoldir/PostDocs//MontpellierU.ComparativeGenomics

]]> https://bioinformaticsonline.com/bookmarks/view/37584/mulan-multiple-sequence-local-alignment-and-visualization-for-studying-function-and-evolution Fri, 24 Aug 2018 09:50:01 -0500 https://bioinformaticsonline.com/bookmarks/view/37584/mulan-multiple-sequence-local-alignment-and-visualization-for-studying-function-and-evolution <![CDATA[Mulan: Multiple-sequence local alignment and visualization for studying function and evolution]]> Mulan: Multiple-sequence local alignment and visualization for studying function and evolution

Mulan (http://mulan.dcode.org/), a novel method and a network server for comparing multiple draft and finished-quality sequences to identify functional elements conserved over evolutionary time. Mulan brings together several novel algorithms: the TBA multi-aligner program for rapid identification of local sequence conservation, and the multiTF program for detecting evolutionarily conserved transcription factor binding sites in multiple alignments. In addition, Mulan supports two-way communication with the GALA database; alignments of multiple species dynamically generated in GALA can be viewed in Mulan, and conserved transcription factor binding sites identified with Mulan/multiTF can be integrated and overlaid with extensive genome annotation data using GALA.

Address of the bookmark: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC540288/

]]> Jit https://bioinformaticsonline.com/bookmarks/view/42798/what-is-the-hologenome-concept-of-evolution Wed, 03 Feb 2021 12:23:54 -0600 https://bioinformaticsonline.com/bookmarks/view/42798/what-is-the-hologenome-concept-of-evolution <![CDATA[What is the hologenome concept of evolution?]]> All multicellular organisms are colonized by microbes, but a gestalt study of the composition of microbiome communities and their influence on the ecology and evolution of their macroscopic hosts has only recently become possible. One approach to thinking about the topic is to view the host–microbiome ecosystem as a “holobiont”.

Address of the bookmark: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6198262/

]]> Jit https://bioinformaticsonline.com/blog/view/43980/useful-link-to-teach-evolution Wed, 05 Oct 2022 18:29:30 -0500 https://bioinformaticsonline.com/blog/view/43980/useful-link-to-teach-evolution <![CDATA[Useful link to teach evolution !]]> Mimicry and other resources Mimicry games: Great Heliconius game: http://heliconius.org/evolving_butterflies/ (See also https://royalsocietypublishing.org/doi/10.1098/rspb.2020.0014) Other one, a bit less friendly: https://ccl.northwestern.edu/netlogo/models/Mimicry Camouflage practical https://alexis-catherine.github.io/publication/natural-selection-and-camouflage/ (NetLogo also has one: https://ccl.northwestern.edu/netlogo/models/BugHuntCamouflage) Peppered moth game: https://askabiologist.asu.edu/peppered-moths-game/play.html General resources The always popular Populus: https://cbs.umn.edu/populus/overview Drift & Gene Flow https://cartwrig.ht/apps/genie/ (Cock van Oosterhout has a great ppt to lead students through this) See also https://cartwrig.ht/apps/redlynx/ https://demonstrations.wolfram.com/ReplicatorMutatorDynamicsWithThreeStrategies/ NetLogo: http://ccl.northwestern.edu/netlogo/models/index.cgi Population Genetics: https://www.radford.edu/~rsheehy/Gen_flash/popgen/ Evolution in general https://evolution.berkeley.edu/evolibrary/home.php Mitochondrial Eve: https://projects.ncsu.edu/cals/gn/ex/mit-eve.html Y chromosomes: https://projects.ncsu.edu/cals/gn/ex/y-chrom.html A professional online package from Michael Kasumovic: https://arludo.com/ a compilation of resources: https://planted.botany.org/index.php?P=Home Finally, Donald Forsdyke has some great on-line videos explaining evolutionary principles (occasionally in a fake Scottish accent): http://post.queensu.ca/~forsdyke/videolectures.htm]]> Abhi https://bioinformaticsonline.com/bookmarks/view/42987/public-databases-for-bioinformatics Tue, 23 Mar 2021 05:32:15 -0500 https://bioinformaticsonline.com/bookmarks/view/42987/public-databases-for-bioinformatics <![CDATA[Public Databases for Bioinformatics !]]> https://www.nature.com/articles/s41467-020-17155-y

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"

For use case 1 we obtained the following ENCODE and ROADMAP datasets https://www.encodeproject.org/files/ENCFF446WOD/@@download/ENCFF446WOD.bed.gz, https://www.encodeproject.org/files/ENCFF546PJU/@@download/ENCFF546PJU.bam, https://www.encodeproject.org/files/ENCFF059BEU/@@download/ENCFF059BEU.bam. Blacklisted regions were obtained from http://mitra.stanford.edu/kundaje/akundaje/release/blacklists/hg38-human/hg38.blacklist.bed.gz. The human genome version hg38 was obtained from http://hgdownload.cse.ucsc.edu/goldenPath/hg38/bigZips/hg38.fa.gz.

For use case 2 we used the set of narrowPeak files summarized in https://github.com/wkopp/janggu_usecases/tree/master/extra/urls.txt (archived version v1.0.1). The human genome version hg19 was obtained from http://hgdownload.cse.ucsc.edu/goldenPath/hg19/bigZips/hg19.fa.gz

For use case 3 we used the ENCODE datasets https://www.encodeproject.org/files/ENCFF591XCX/@@download/ENCFF591XCX.bam, https://www.encodeproject.org/files/ENCFF736LHE/@@download/ENCFF736LHE.bigWig, https://www.encodeproject.org/files/ENCFF177HHM/@@download/ENCFF177HHM.bam as we as the GENCODE annotation v29 from ftp://ftp.ebi.ac.uk/pub/databases/gencode/Gencode_human/release_29/gencode.v29.annotation.gtf.gz.

Address of the bookmark: http://mitra.stanford.edu/

]]> Jit