Micromonospora okii TP-A0468 is a prokaryote of the family Micromonosporaceae.
| @ref 20215 |
|
|
| Domain Bacillati |
| Phylum Actinomycetota |
| Class Actinomycetes |
| Order Micromonosporales |
| Family Micromonosporaceae |
| Genus Micromonospora |
| Species Micromonospora okii |
| Full scientific name Micromonospora okii Komaki et al. 2022 |
| @ref | Trait | Model | Prediction | Confidence in % | In training data |
|---|---|---|---|---|---|
| 125439 | oxygen_tolerance | BacteriaNetⓘ | obligate aerobe | 99.70 | no |
| 125439 | gram_stain | BacteriaNetⓘ | positive | 99.90 | no |
| 125439 | motility | BacteriaNetⓘ | no | 92.20 | no |
| 125439 | spore_formation | BacteriaNetⓘ | yes | 97.10 | no |
| @ref | Trait | Model | Prediction | Confidence in % | In training data |
|---|---|---|---|---|---|
| 125438 | gram-positive | gram-positiveⓘ | yes | 86.98 | no |
| 125438 | anaerobic | anaerobicⓘ | no | 96.38 | no |
| 125438 | spore-forming | spore-formingⓘ | yes | 92.41 | no |
| 125438 | aerobic | aerobicⓘ | yes | 90.29 | no |
| 125438 | thermophilic | thermophileⓘ | no | 94.00 | no |
| 125438 | flagellated | motile2+ⓘ | no | 90.00 | no |
| Topic | Title | Authors | Journal | DOI | Year | |
|---|---|---|---|---|---|---|
| Phylogeny | In Silico Analysis of PKS and NRPS Gene Clusters in Arisostatin- and Kosinostatin-Producers and Description of Micromonospora okii sp. nov. | Komaki H, Ichikawa N, Hosoyama A, Hamada M, Igarashi Y. | Antibiotics (Basel) | 10.3390/antibiotics10121447 | 2021 |
| #20215 | Parte, A.C., Sardà Carbasse, J., Meier-Kolthoff, J.P., Reimer, L.C. and Göker, M.: List of Prokaryotic names with Standing in Nomenclature (LPSN) moves to the DSMZ. IJSEM ( DOI 10.1099/ijsem.0.004332 ) |
| #66792 | Julia Koblitz, Joaquim Sardà, Lorenz Christian Reimer, Boyke Bunk, Jörg Overmann: Automatically annotated for the DiASPora project (Digital Approaches for the Synthesis of Poorly Accessible Biodiversity Information) . |
| #125438 | Julia Koblitz, Lorenz Christian Reimer, Rüdiger Pukall, Jörg Overmann: Predicting bacterial phenotypic traits through improved machine learning using high-quality, curated datasets. 2024 ( DOI 10.1101/2024.08.12.607695 ) |
| #125439 | Philipp Münch, René Mreches, Martin Binder, Hüseyin Anil Gündüz, Xiao-Yin To, Alice McHardy: deepG: Deep Learning for Genome Sequence Data. R package version 0.3.1 . |
| #126262 | A. Lissin, I. Schober, J. F. Witte, H. Lüken, A. Podstawka, J. Koblitz, B. Bunk, P. Dawyndt, P. Vandamme, P. de Vos, J. Overmann, L. C. Reimer: StrainInfo—the central database for linked microbial strain identifiers. ( DOI 10.1093/database/baaf059 ) |
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https://doi.org/10.13145/bacdive169826.20251217.10
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BacDive in 2025: the core database for prokaryotic strain data