DLKcat
Introduction
The DLkcat toolbox is a Matlab/Python package for prediction of
kcats and generation of the ecGEMs. The repo is divided into two parts:
DeeplearningApproach
and BayesianApproach
. DeeplearningApproach
supplies a deep-learning based prediction tool for kcat prediction,
while BayesianApproach
supplies an automatic Bayesian based pipeline
to construct ecModels using the predicted kcats.
Usage
-
Please check the instruction
README
file under these two sectionBayesianapproach
andDeeplearningApproach
for reporducing all figures in the paper. -
For people who are interested in using the trained deep-learning model for their own kcat prediction, we supplied an example. please check usage for detailed information in the file DeeplearningApproach/README under the
DeeplearningApproach
.input
for the prediction is theProtein sequence
andSubstrate SMILES structure/Substrate name
, please check the file in DeeplearningApproach/Code/example/input.tsvoutput
is the correpondingkcat
value
Citation
- Currently, please cite the preprint paper Deep learning based kcat prediction enables improved enzyme constrained model reconstruction""
Contact
- Feiran Li (@feiranl), Chalmers University of Technology, Gothenburg, Sweden
- Le Yuan (@le-yuan), Chalmers University of Technology, Gothenburg, Sweden
Last update: 2022-04-09