To display all available datasets

busco --list-datasets

You can also download them manually and see a list with the number of marker genes.

Earlier versions: v3, v2, v1

../
acidobacteria_odb10.2020-03-06.tar.gz              16-Oct-2020 13:19     14M
aconoidasida_odb10.2020-08-05.tar.gz               16-Oct-2020 13:19     51M
actinobacteria_class_odb10.2020-03-06.tar.gz       16-Oct-2020 13:19      8M
actinobacteria_phylum_odb10.2020-03-06.tar.gz      16-Oct-2020 13:20      9M
actinopterygii_odb10.2020-08-05.tar.gz             16-Oct-2020 13:20    173M
agaricales_odb10.2020-08-05.tar.gz                 16-Oct-2020 13:20    186M
agaricomycetes_odb10.2020-08-05.tar.gz             16-Oct-2020 13:19    152M
alphaproteobacteria_odb10.2020-03-06.tar.gz        16-Oct-2020 13:20     11M
alteromonadales_odb10.2020-03-06.tar.gz            16-Oct-2020 13:20     18M
alveolata_odb10.2020-09-10.tar.gz                  16-Oct-2020 13:20     13M
apicomplexa_odb10.2020-09-10.tar.gz                16-Oct-2020 13:19     27M
aquificae_odb10.2020-03-06.tar.gz                  16-Oct-2020 13:19     12M
arachnida_odb10.2020-08-05.tar.gz                  16-Oct-2020 13:19    136M
archaea_odb10.2020-03-06.tar.gz                    16-Oct-2020 13:20      4M
arthropoda_odb10.2020-09-10.tar.gz                 16-Oct-2020 13:20     95M
ascomycota_odb10.2020-09-10.tar.gz                 16-Oct-2020 13:20    295M
aves_odb10.2020-09-10.tar.gz                       16-Oct-2020 13:20    465M
bacillales_odb10.2020-03-06.tar.gz                 16-Oct-2020 13:20     10M
bacilli_odb10.2020-03-06.tar.gz                    16-Oct-2020 13:19      7M
bacteria_odb10.2020-03-06.tar.gz                   16-Oct-2020 13:20      6M
bacteroidales_odb10.2020-03-06.tar.gz              16-Oct-2020 13:20     13M
bacteroidetes-chlorobi_group_odb10.2020-03-06.t..> 16-Oct-2020 13:19      9M
bacteroidetes_odb10.2020-03-06.tar.gz              16-Oct-2020 13:20     10M
bacteroidia_odb10.2020-03-06.tar.gz                16-Oct-2020 13:20     13M
basidiomycota_odb10.2020-09-10.tar.gz              16-Oct-2020 13:19    165M
betaproteobacteria_odb10.2020-03-06.tar.gz         16-Oct-2020 13:19     13M
boletales_odb10.2020-08-05.tar.gz                  16-Oct-2020 13:19    197M
brassicales_odb10.2020-08-05.tar.gz                16-Oct-2020 13:20    158M
burkholderiales_odb10.2020-03-06.tar.gz            16-Oct-2020 13:19     16M
campylobacterales_odb10.2020-03-06.tar.gz          16-Oct-2020 13:20     14M
capnodiales_odb10.2020-08-05.tar.gz                16-Oct-2020 13:19    178M
carnivora_odb10.2020-08-05.tar.gz                  16-Oct-2020 13:19    376M
cellvibrionales_odb10.2020-03-06.tar.gz            16-Oct-2020 13:19     19M
cetartiodactyla_odb10.2020-08-05.tar.gz            16-Oct-2020 13:19    407M
chaetothyriales_odb10.2020-08-05.tar.gz            16-Oct-2020 13:20    288M
chlamydiae_odb10.2020-03-06.tar.gz                 16-Oct-2020 13:20     13M
chlorobi_odb10.2020-03-06.tar.gz                   16-Oct-2020 13:20     22M
chloroflexi_odb10.2020-03-06.tar.gz                16-Oct-2020 13:20      6M
chlorophyta_odb10.2020-08-05.tar.gz                16-Oct-2020 13:20     58M
chromatiales_odb10.2020-03-06.tar.gz               16-Oct-2020 13:19     14M
chroococcales_odb10.2020-03-06.tar.gz              16-Oct-2020 13:19     27M
clostridia_odb10.2020-03-06.tar.gz                 16-Oct-2020 13:19      6M
clostridiales_odb10.2020-03-06.tar.gz              16-Oct-2020 13:20      6M
coccidia_odb10.2020-08-05.tar.gz                   16-Oct-2020 13:20     24M
coriobacteriales_odb10.2020-03-06.tar.gz           16-Oct-2020 13:19     12M
coriobacteriia_odb10.2020-03-06.tar.gz             16-Oct-2020 13:20      9M
corynebacteriales_odb10.2020-03-06.tar.gz          16-Oct-2020 13:19     16M
cyanobacteria_odb10.2020-03-06.tar.gz              16-Oct-2020 13:19     17M
cyprinodontiformes_odb10.2020-08-05.tar.gz         16-Oct-2020 13:19    504M
cytophagales_odb10.2020-03-06.tar.gz               16-Oct-2020 13:19     18M
cytophagia_odb10.2020-03-06.tar.gz                 16-Oct-2020 13:20     18M
delta-epsilon-subdivisions_odb10.2020-03-06.tar.gz 16-Oct-2020 13:19      6M
deltaproteobacteria_odb10.2020-03-06.tar.gz        16-Oct-2020 13:19      6M
desulfobacterales_odb10.2020-03-06.tar.gz          16-Oct-2020 13:20     13M
desulfovibrionales_odb10.2020-03-06.tar.gz         16-Oct-2020 13:19     17M
desulfurococcales_odb10.2020-03-06.tar.gz          16-Oct-2020 13:20      9M
desulfuromonadales_odb10.2020-03-06.tar.gz         16-Oct-2020 13:19     18M
diptera_odb10.2020-08-05.tar.gz                    16-Oct-2020 13:19    185M
dothideomycetes_odb10.2020-08-05.tar.gz            16-Oct-2020 13:19    194M
embryophyta_odb10.2020-09-10.tar.gz                16-Oct-2020 13:19    138M
endopterygota_odb10.2020-09-10.tar.gz              16-Oct-2020 13:19    190M
enterobacterales_odb10.2020-03-06.tar.gz           16-Oct-2020 13:19     11M
entomoplasmatales_odb10.2020-03-06.tar.gz          16-Oct-2020 13:19      7M
epsilonproteobacteria_odb10.2020-03-06.tar.gz      16-Oct-2020 13:20     13M
euarchontoglires_odb10.2020-09-10.tar.gz           16-Oct-2020 13:20    728M
eudicots_odb10.2020-09-10.tar.gz                   16-Oct-2020 13:19    168M
euglenozoa_odb10.2020-08-05.tar.gz                 16-Oct-2020 13:20     10M
eukaryota_odb10.2020-09-10.tar.gz                  16-Oct-2020 13:19    100M
eurotiales_odb10.2020-08-05.tar.gz                 16-Oct-2020 13:19    211M
eurotiomycetes_odb10.2020-08-05.tar.gz             16-Oct-2020 13:19    197M
euryarchaeota_odb10.2020-03-06.tar.gz              16-Oct-2020 13:20      5M
eutheria_odb10.2020-09-10.tar.gz                   16-Oct-2020 13:20    920M
fabales_odb10.2020-08-05.tar.gz                    16-Oct-2020 13:19    184M
firmicutes_odb10.2020-03-06.tar.gz                 16-Oct-2020 13:20      6M
flavobacteriales_odb10.2020-03-06.tar.gz           16-Oct-2020 13:19     18M
flavobacteriia_odb10.2020-03-06.tar.gz             16-Oct-2020 13:20     18M
fungi_odb10.2020-09-10.tar.gz                      16-Oct-2020 13:19    181M
fusobacteria_odb10.2020-03-06.tar.gz               16-Oct-2020 13:19     11M
fusobacteriales_odb10.2020-03-06.tar.gz            16-Oct-2020 13:19     11M
gammaproteobacteria_odb10.2020-03-06.tar.gz        16-Oct-2020 13:19     10M
glires_odb10.2020-08-05.tar.gz                     16-Oct-2020 13:19    549M
glomerellales_odb10.2020-08-05.tar.gz              16-Oct-2020 13:19    259M
halobacteria_odb10.2020-03-06.tar.gz               16-Oct-2020 13:19     18M
halobacteriales_odb10.2020-03-06.tar.gz            16-Oct-2020 13:20     18M
haloferacales_odb10.2020-03-06.tar.gz              16-Oct-2020 13:19     20M
helotiales_odb10.2020-08-05.tar.gz                 16-Oct-2020 13:19    224M
hemiptera_odb10.2020-08-05.tar.gz                  16-Oct-2020 13:19    115M
hymenoptera_odb10.2020-08-05.tar.gz                16-Oct-2020 13:19    321M
hypocreales_odb10.2020-08-05.tar.gz                16-Oct-2020 13:19    224M
insecta_odb10.2020-09-10.tar.gz                    16-Oct-2020 13:20    119M
lactobacillales_odb10.2020-03-06.tar.gz            16-Oct-2020 13:19      9M
laurasiatheria_odb10.2020-09-10.tar.gz             16-Oct-2020 13:20    688M
legionellales_odb10.2020-03-06.tar.gz              16-Oct-2020 13:19     16M
leotiomycetes_odb10.2020-08-05.tar.gz              16-Oct-2020 13:19    164M
lepidoptera_odb10.2020-08-05.tar.gz                16-Oct-2020 13:20    241M
liliopsida_odb10.2020-09-10.tar.gz                 16-Oct-2020 13:20    163M
mammalia_odb10.2020-09-10.tar.gz                   16-Oct-2020 13:19    677M
metazoa_odb10.2020-09-10.tar.gz                    16-Oct-2020 13:19    127M
methanobacteria_odb10.2020-03-06.tar.gz            16-Oct-2020 13:19     15M
methanococcales_odb10.2020-03-06.tar.gz            16-Oct-2020 13:20     17M
methanomicrobia_odb10.2020-03-06.tar.gz            16-Oct-2020 13:19     12M
methanomicrobiales_odb10.2020-03-06.tar.gz         16-Oct-2020 13:20     16M
micrococcales_odb10.2020-03-06.tar.gz              16-Oct-2020 13:19     12M
microsporidia_odb10.2020-08-05.tar.gz              16-Oct-2020 13:20     26M
mollicutes_odb10.2020-03-06.tar.gz                 16-Oct-2020 13:20      3M
mollusca_odb10.2020-08-05.tar.gz                   16-Oct-2020 13:20    266M
mucorales_odb10.2020-08-05.tar.gz                  16-Oct-2020 13:20    105M
mucoromycota_odb10.2020-08-05.tar.gz               16-Oct-2020 13:19     75M
mycoplasmatales_odb10.2020-03-06.tar.gz            16-Oct-2020 13:19      4M
natrialbales_odb10.2020-03-06.tar.gz               16-Oct-2020 13:19     24M
neisseriales_odb10.2020-03-06.tar.gz               16-Oct-2020 13:19     16M
nematoda_odb10.2020-08-05.tar.gz                   16-Oct-2020 13:20    138M
nitrosomonadales_odb10.2020-03-06.tar.gz           16-Oct-2020 13:19     15M
nostocales_odb10.2020-03-06.tar.gz                 16-Oct-2020 13:19     35M
oceanospirillales_odb10.2020-03-06.tar.gz          16-Oct-2020 13:19     13M
onygenales_odb10.2020-08-05.tar.gz                 16-Oct-2020 13:19    233M
oscillatoriales_odb10.2020-03-06.tar.gz            16-Oct-2020 13:19     29M
passeriformes_odb10.2020-08-05.tar.gz              16-Oct-2020 13:20    298M
pasteurellales_odb10.2020-03-06.tar.gz             16-Oct-2020 13:19     19M
planctomycetes_odb10.2020-03-06.tar.gz             16-Oct-2020 13:19     13M
plasmodium_odb10.2020-08-05.tar.gz                 16-Oct-2020 13:20    199M
pleosporales_odb10.2020-08-05.tar.gz               16-Oct-2020 13:19    288M
poales_odb10.2020-08-05.tar.gz                     16-Oct-2020 13:19    186M
polyporales_odb10.2020-08-05.tar.gz                16-Oct-2020 13:20    206M
primates_odb10.2020-08-05.tar.gz                   16-Oct-2020 13:19    451M
propionibacteriales_odb10.2020-03-06.tar.gz        16-Oct-2020 13:19     14M
proteobacteria_odb10.2020-03-06.tar.gz             16-Oct-2020 13:19      8M
pseudomonadales_odb10.2020-03-06.tar.gz            16-Oct-2020 13:19     17M
rhizobiales_odb10.2020-03-06.tar.gz                16-Oct-2020 13:19     15M
rhizobium-agrobacterium_group_odb10.2020-03-06...> 16-Oct-2020 13:19     34M
rhodobacterales_odb10.2020-03-06.tar.gz            16-Oct-2020 13:19     19M
rhodospirillales_odb10.2020-03-06.tar.gz           16-Oct-2020 13:19     14M
rickettsiales_odb10.2020-03-06.tar.gz              16-Oct-2020 13:19      8M
saccharomycetes_odb10.2020-08-05.tar.gz            16-Oct-2020 13:20    109M
sauropsida_odb10.2020-09-10.tar.gz                 16-Oct-2020 13:19    499M
selenomonadales_odb10.2020-03-06.tar.gz            16-Oct-2020 13:19     16M
solanales_odb10.2020-08-05.tar.gz                  16-Oct-2020 13:19    196M
sordariomycetes_odb10.2020-08-05.tar.gz            16-Oct-2020 13:19    206M
sphingobacteriia_odb10.2020-03-06.tar.gz           16-Oct-2020 13:20     21M
sphingomonadales_odb10.2020-03-06.tar.gz           16-Oct-2020 13:19     22M
spirochaetales_odb10.2020-03-06.tar.gz             16-Oct-2020 13:20      8M
spirochaetes_odb10.2020-03-06.tar.gz               16-Oct-2020 13:20      6M
spirochaetia_odb10.2020-03-06.tar.gz               16-Oct-2020 13:19      6M
stramenopiles_odb10.2020-08-05.tar.gz              16-Oct-2020 13:19      5M
streptomycetales_odb10.2020-03-06.tar.gz           16-Oct-2020 13:20     31M
streptosporangiales_odb10.2020-03-06.tar.gz        16-Oct-2020 13:19     22M
sulfolobales_odb10.2020-03-06.tar.gz               16-Oct-2020 13:19     22M
synechococcales_odb10.2020-03-06.tar.gz            16-Oct-2020 13:19     16M
synergistetes_odb10.2020-03-06.tar.gz              16-Oct-2020 13:19     14M
tenericutes_odb10.2020-03-06.tar.gz                16-Oct-2020 13:20      4M
tetrapoda_odb10.2020-09-10.tar.gz                  16-Oct-2020 13:19    561M
thaumarchaeota_odb10.2020-03-06.tar.gz             16-Oct-2020 13:20     13M
thermoanaerobacterales_odb10.2020-03-06.tar.gz     16-Oct-2020 13:19     10M
thermoplasmata_odb10.2020-03-06.tar.gz             16-Oct-2020 13:20      7M
thermoproteales_odb10.2020-03-06.tar.gz            16-Oct-2020 13:19      8M
thermoprotei_odb10.2020-03-06.tar.gz               16-Oct-2020 13:20      6M
thermotogae_odb10.2020-03-06.tar.gz                16-Oct-2020 13:19     16M
thiotrichales_odb10.2020-03-06.tar.gz              16-Oct-2020 13:20     11M
tissierellales_odb10.2020-03-06.tar.gz             16-Oct-2020 13:19      9M
tissierellia_odb10.2020-03-06.tar.gz               16-Oct-2020 13:19      8M
tremellomycetes_odb10.2020-08-05.tar.gz            16-Oct-2020 13:19    210M
verrucomicrobia_odb10.2020-03-06.tar.gz            16-Oct-2020 13:19     11M
vertebrata_odb10.2020-09-10.tar.gz                 16-Oct-2020 13:19    409M
vibrionales_odb10.2020-03-06.tar.gz                16-Oct-2020 13:20     26M
viridiplantae_odb10.2020-09-10.tar.gz              16-Oct-2020 13:20     36M
xanthomonadales_odb10.2020-03-06.tar.gz            16-Oct-2020 13:19     24M

Address of the bookmark: https://busco-data.ezlab.org/v4/data/lineages/

Research Area

We are interested in the development of the statistics and computational methods for the analysis of this data in breast cancer.
We have worked on probabilistic models for subcellular localization, protein-protein interactions, and problems related to chemical genomics.
We are interested in the development of bioinformatics/biostatistical methodology in the analysis of epigenetic/epigenomic data.
We are interested in integrative bioinformatics approaches to learn the gene, gene products, interactions, and regulatory mechanisms involved in mental retardation.

Link @ http://www.mcgill.ca/mcb/

Awesome viddeo explaining the way in which the antibody, HuLuc 63, appears to induce anti-tumor effects by binding to a protein that is only expressed on the surface of myeloma cells. This initiates antibody-dependent cellular cytotoxicity activity that kills myeloma cells and leaves healthy cells intact.

Master's degree in bioinformatics, computer science, molecular biology, or related field
One year of experience in analyzing RNA-Seq data
In lieu of a degree, consideration will be given to an equivalent combination of related education and required work experience.
Understanding of molecular biology, biochemistry, and genetics
Proficiency in writing scripts using Perl, Python, Java, or equivalent languages
Proficiency in R and UNIX/LINUX
Knowledge of genomics, alignment, annotation, bioinformatics, concepts of sequence assembly
Highly motivated and detail-oriented
Ability, interest, and curiosity to learn new skills
Must possess strong communication skills to work effectively with users across disciplines
Ability to work independently and as part of a multi-disciplinary team
Strong visual, verbal, and written communication skills
Excellent time organizational skills
Preferred:

Experience writing software or building software pipelines
Experience with oncology-specific public databases including TCGA
Experience with deploying and/or running software on high-performance computational systems
Statistical and experimental design knowledge
Additional Information:

This position is contingent on the availability of funding
Purdue will not sponsor employment authorization for this position
A background check will be required for employment in this position
FLSA: Exempt (Not Eligible For Overtime)
Retirement Eligibility: Defined Contribution Waiting Period
Purdue University is an EOE/AA employer. All individuals, including minorities, women, individuals with disabilities, and veterans are encouraged to apply

More at https://careers.purdue.edu/job/West-Lafayette-Bioinformatician-Purdue-Cancer-Center-IN-47906/686617600/

Novel diagnostic platform for detection of Osteoarthritis

I invite applications from highly motivated individuals to join my laboratory as a PhD student in Systems Biology at the University of Calgary McCaig Institute for Bone and Joint Health. This project is aimed at characterizing the networks of physical (protein-protein) interactions underlying inflammatory processes in patients with Osteoarthritis and how this differs from patients with Rheumatoid Arthritis and normal individuals. This work will eventually lead to the development of a novel diagnostic platform for the non-invasive and accurate detection of early Osteoarthritis. The selected candidate will use state-of-the-art computational methodologies to systematically analyze proteomic data, and develop /implement new algorithms to identify protein and functional interaction networks from high throughput experimental data. The individual will also benefit by working closely with experts at the UofC and UofA through an AIHS Alberta Osteoarthritis Team Grant which includes experts from all pillars of health research. The candidate will also be supported to attend bioinformatics workshops and conferences to advance and disseminate their research.
Qualifications: The ideal candidate will have a Master’s degree in Computational Biology, Bioinformatics, or equivalent with strong background knowledge of the Biological Sciences, Biochemistry, and Microbiology. The individual should additionally have experience in handling high-throughput data sets as well as programming skills. The candidate will be registered as a PhD student in Dr. Krawetz’s laboratory, located in the new state-of-the-art Health Research Innovation Centre at the UofC. The individual will have strong verbal and written skills and the ability to work efficiently in a team environment.

In addition to the outstanding research opportunities available in this setting, students also enjoy the many cultural and sporting amenities provided in the city of Calgary, and can take advantage of the unparalleled skiing and hiking in the Rocky Mountains that are less than an hour away.

Candidates must be academically competitive and will be expected to apply for external funding. The stipend is $25,000/yr. For outstanding PhD students, internal top-up award opportunities are available on a competitive basis. If interested in joining the lab, please contact Dr. Krawetz directly at rkrawetz@ucalgary.ca and provide the following information:

- Short cover letter explaining your interest in the lab
- Resume
- Scanned copy of transcript or listing of course grades
- Names and contact information for two individuals who will be willing to provide letters of reference

Essential experience / qualifications:
We are looking for highly motivated candidates holding a Master / Diploma in Biology, Biochemistry, Molecular Medicine or similar; solid knowledge of molecular and cell biological techniques; good English knowledge.

Applications:
Please send your application (including CV, letter of motivation, contact information of two references, and list of publication) by 13.03.2020 at the latest to:

Universitätsklinikum Erlangen
Chirurgische Klinik
Translational Research Center
Prof. Dr. rer. nat. Michael Stürzl
Schwabachanlage 12
91054 Erlangen
E-Mail: michael.stuerzl@uk-erlangen.de

The course topics will include theoretical and practical aspects in:
- Genomes comparisons,
- Evolutionary analyses (orthologs, paralogs and ancestral genomes
inference),
- RNAseq and Next Generation Sequencing (including algorithms, methods
and sequence mapping tools, data analyses and applications).

The course programme will be centred on theoretical presentations
followed by practical sessions. Practical sessions in a Linux
environment will involve Unix shell and Perl scripting. Participants
are assumed to be familiar with this environment.

A series of lectures delivered by prominent scientists on recent hot
topics in genome (Viruses, Prokaryotes, Eukaryotes) studies will be
included in the programme and future research perspectives will be
highlighted.

The topics that will be included in the course programme are similar
to those included in previously organized courses:http://www.pasteur.fr/~tekaia/BGA_courses.html

The course is aimed at motivated Ph.D students and Post-Doctoral
Researchers in Academic Institutions, with background in Mathematics,
Statistics, Biology or Computer Science and who are involved in
Bioinformatics and Genomes studies.

Selection of participants will be based on their background, running
research projects and on expressed motivations.
Selected students will have free accommodation and meals and are
expected to contribute with 200 euros and to pay for their travel
expenses.
All participants (students and invited speakers) will stay in the same
hotel.

Detailed indications are available on the course web site: http://events.embo.org/14-comparative-genomics/index.html

Candidates are advised to complete carefully the application form,
together with an abstract of at least one of their running projects, a
"one-page CV" and a personal Identity Picture (Photo).

The application deadline is March 14, 2014.

The organizers:
Menelaos Manoussakis, Hellenic Pasteur Institute, Athens, Greece.
Evdokia Karagouni, Hellenic Pasteur Institute, Athens - Greece.
Evie Melanitou, Institut Pasteur Paris - France.
Fredj Tekaia ( Institut Pasteur Paris France)
URL: http://www.pasteur.fr/~tekaia/BGA_courses.html

Date: 5 – 17 May, 2014.
More at http://events.embo.org/14-comparative-genomics/index.html
will take place in the ,

An international team, including researchers from Google Health and Imperial College London, designed and trained a computer model on X-ray images from nearly 29,000 women.

The algorithm outperformed six radiologists in reading mammograms.

AI was still as good as two doctors working together.

Unlike humans, AI is tireless. Experts say it could improve detection. Read More: https://www.bbc.com/news/health-50857759

Reference

http://www.sciencedaily.com/releases/2013/12/131204132018.htm