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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.
Microorganism, Proteomes, Machine learning, Optimal growth temperature
Microorganism, Proteomes, Machine learning, Optimal growth temperature
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