jmschrei

Use for any task involving the tangermeme library — post-training analysis of genomic sequence-to-function (S2F) deep learning models. Triggers on predictions, DeepLIFT/SHAP attributions, marginalization/ablation/spacing of motifs, saturation mutagenesis…

Use for any task involving the ledidi library — gradient-based design of minimal edits to categorical sequences (DNA/RNA/protein) so that a frozen oracle model predicts a desired output. Triggers on designing or editing a sequence, inserting or knocking out a…

Train, evaluate, and use Cherimoya sequence-to-function genomic models with the `cherimoya` command-line tools or Python API. Use when a user wants to run the end-to-end pipeline, use a trained model to do downstream tasks, or troubleshoot a run. Designed for…