MLEssential is a computational toolbox to predict essential genes for yeast species using machine learning based on multi-scale information, including sequence features and evolution-based features.
- Python==3.7.4
- biopython==1.75
- scikit-learn==0.22.1
- numpy==1.17.2
- scipy==1.3.1
- pandas==0.25.1
- seaborn==0.9.0
Please cite this paper: Lu, H. et al. Yeast metabolic innovations emerged via expanded metabolic network and gene positive selection. Molecular Systems Biology 2021(17):e10427. https://www.embopress.org/doi/full/10.15252/msb.202110427.
- Le Yuan (@leyuan), Chalmers University of Technology, Sweden
- Hongzhong Lu (@hongzhonglu), Chalmers University of Technology, Sweden
- Feiran Li (@feiranl), Chalmers University of Technology, Sweden
- Eduard J. Kerkhoven (@edkerk), Chalmers University of Technology, Sweden