Published July 4, 2019 | Version 1.0.0

Microbial Proteomes with/without experimental optimal growth temperature

  • 1. Chalmers University of Technology

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.

Files

Files (7.0 GB)

Name Size
md5:4bc90f2e6cb52d14065fbfeb0d7bc578
5.5 GB Download
md5:6e3a99d78cd59fd72b2218094cfa684a
1.5 GB Download

Additional details

Related works

Is supplement to
10.1101/522342 (DOI)

Funding

European Commission
PAcMEN - Predictive and Accelerated Metabolic Engineering Network 722287