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hybrid · semantic + lexical · 1 datasets ranked · 0.42s

Structuretensor1
Depthmeasured1
Licenseopen1
Accessopen1
Formathdf51
Sourcezenodo1
clear
1-1 of 1sortrelevancemeasured firstqualitysize
tensor

Precomputed Databases for OMAmer

0.00

Altenhoff, Adrian

6 files · 100 MB · hdf5

OMAmer - tree-driven and alignment-free protein assignment to subfamilies OMAmer is an alignment-free protein family assignment method designed to avoid overly specific subfamily predictions and to scale efficiently to phylogenomic databases containing thousands of genomes. It relies on an innovative approach that uses evolutionarily informed k-mers for alignment-free mapping to ancestral protein subfamilies. This dataset provides precomputed OMAmer databases derived from the Hierarchical Orthologous Groups in the OMA Browser . We aim to update these databases with every new OMA Browser release. Each OMAmer database is built using the latest version of the OMAmer package available at the time of the corresponding OMA Browser release. The dataset includes databases for different subsets of the species taxonomy. In most cases, we recommend using the LUCA.h5 database, which contains information from all species in the OMA database. The subset-specific databases are mainly useful when disk space is limited. The release May2026 is based on the OMA Browser release May 2026 which comprises 2983 species. We used OMAmer version 2.1.0 to build these databases.

open·CC-BY-4.0·Zenodo·completeSource
closeopen full
tabular · zenodo

On the impact of the turbulent grazing flow development on the acoustic response of an acoustic liner

Paduano, Angelo · Scarano, Francesco · Casalino, Damiano · A. Cordioli, Julio · Avallone, Francesco

measured·open·37 files
Measuredstructure observed by touching the bytes
topology
tabular
records
200
sampled
full dataset
null rate
0.0%
duplicate rate
0.0%
size
39 KB
profiler
tabular:stdlib/v1

Measured the full file.

Columns (10)
columntypenullsdistribution
y_h_smoothnumeric number0%0.002114 - 1.19 · med 0.3407
sigma_u_U0_smoothnumeric number0%0.01095 - 0.09779 · med 0.03382
y_h_linednumeric number0%0.002114 - 1.19 · med 0.3407
sigma_u_U0_linednumeric number0%0.01403 - 0.09094 · med 0.04745
y_h_lined_130_1400_up
numeric number
0%
0.002114 - 1.19 · med 0.3407
sigma_u_U0_lined_130_1400_upnumeric number0%0.01475 - 0.09021 · med 0.04849
y_h_lined_145_1400_upnumeric number0%0.002114 - 1.19 · med 0.3407
sigma_u_U0_lined_145_1400_upnumeric number0%0.01412 - 0.08632 · med 0.04911
y_h_lined_145_1400_dwnumeric number0%0.002114 - 1.19 · med 0.3407
sigma_u_U0_lined_145_1400_dwnumeric number0%0.01631 - 0.08896 · med 0.04791
Columns by kind

Measured distributions

y_h_smooth
p10 0.04544 · median 0.3407 · p90 0.9616
sigma_u_U0_smooth
p10 0.01153 · median 0.03382 · p90 0.06884
y_h_lined
p10 0.04544 · median 0.3407 · p90 0.9616
sigma_u_U0_lined
p10 0.01583 · median 0.04745 · p90 0.07613
y_h_lined_130_1400_up
p10 0.04544 · median 0.3407 · p90 0.9616
sigma_u_U0_lined_130_1400_up
p10 0.01623 · median 0.04849 · p90 0.07199

+ 4 more measured columns