Microbial Proteomes with/without experimental optimal growth temperature
Description
This repository contains proteomes of microorganisms with/without experimentally determined optimal growth temperature (OGT), used in the paper 'Li G, Rabe KS, Nielsen J & Engqvist MKM (2019) Machine learning applied to predicting microorganism growth temperatures and enzyme catalytic optima. ACS Synth. Biol. 8: 1411–1420'. There are two .tar.gz files: (1) classified.tar.gz. It contains 5761 proteomes with experimental OGT. The name format of each proteome is '{ogt}_{organism_name}_{organism domain}.fasta'. For example, '36_escherichia_coli_bacteria.fasta' for Escherichia coli. (2) not_classified.tar.gz. It contains 1803 proteomes without experimental OGT. The name format is similar as in classified.tar.gz. The only different is to use 'tt' to represent the unknown OGT value. For example, 'tt_candidatus_azobacteroides_bacteria.fasta'. All proteomes are in fasta format. If you used the dataset, please kindly cite the paper mentioned above.
Resources
| Name |
Format |
Description |
Link |
|
0 |
|
http://data.europa.eu/88u/dataset/oai-zenodo-org-3268640 |
|
0 |
|
http://data.europa.eu/88u/dataset/oai-zenodo-org-3268640 |
|
0 |
|
http://data.europa.eu/88u/dataset/oai-zenodo-org-3268640 |
Tags
- proteomes
- microorganism
- optimal-growth-temperature
- machine-learning