Using explainable AI to crack open the black box of SpliceAI
- motif_distillation/: Code to reproduce activation maximization
- motif_characterization/: Code to train surrogate multinomial model and localize motifs
- data-in/: Raw input data used by scripts
- data-out/: Intermediate processed data generated by scripts
- results/: Intermediate results generated by scripts
- SpliceAI-master/: SpliceAI model used by scripts
PWMs generated using activation maximization by gradient ascent are stored in results/A-ascend/
Sullivan et al, Manuscript in Prep
- Patricia Sullivan: splicing expertise, data analysis, software development
- Dr Thom Quinn: ML/AI expertise, methods development, data analysis
- Dr Mark Pinese: splicing expertise, ML/AI expertise, genomic expertise, supervision
- A/Prof Mark Cowley: splicing expertise, genomic expertise, supervision