BPNet_ChIP-seq_TBX19

A BPNet model trained with bpnet-lite on TBX19 (TPIT) ChIP-seq data from mouse pituitary cells, used to model base-resolution binding signal and to discover sequence motifs via TF-MoDISco.

TBX19 (also known as TPIT) is the transcription factor; "TPIT" is the experiment/antibody label used in the underlying ChIP-seq files from which this model was trained.

Performance

Reported metrics found in exp16_TPIT.performance.tsv.

See exp16_TPIT.evaluate.json for the full evaluation output.

Files

File	Description
exp16_TPIT.torch	Model weights (best validation checkpoint)
exp16_TPIT.bpnet.fit.json	Full training configuration (architecture, data paths, chrom split, hyperparameters)
exp16_TPIT.bpnet.attribute.json	Configuration used for computing attributions downstream
exp16_TPIT.performance.tsv	Reported performance metrics
exp16_TPIT.evaluate.json	Full evaluation output
exp16_TPIT.log	Training log