How baksho/e2ecal works
This is a research-experiment repository accompanying a thesis on end-to-end calibration, not a packaged application. Researchers explore a synthetic known-posterior track and two GRN tracks (SERGIO simulation and DREAM5 benchmark), comparing predictive-only, end-to-end, and post-hoc calibration and evaluating predictive quality and calibration. The principal runtime implementation visible here is shared GRN experiment utility code; notebook internals are not sampled, so their connections to that code are left unverified.
Main entry points: grn_experiment_utils.py Training and recalibration · track2_grn_calibration_experiments/notebooks SERGIO track · track1_simulation_supervised/notebooks Synthetic track · data GRN analyses
Components 9
Experiment tracks
- Synthetic track
track1_simulation_supervised/notebooks - Track 1 analyses
track1_simulation_supervised/tables
Calibration methods
- GRN utilities
track2_grn_calibration_experiments/grn_experiment_utils.py - Training and recalibration
track2_grn_calibration_experiments/grn_experiment_utils.py - Metrics and evaluation
track2_grn_calibration_experiments/grn_experiment_utils.py
GRN experiments
- SERGIO track
track2_grn_calibration_experiments/notebooks - DREAM5 track
track2_grn_calibration_experiments/notebooks - GRN analyses
track2_grn_calibration_experiments/data
Other components
- Researcher
Connections 14
- Researcher → Synthetic track: runs experiments
README.md - Researcher → SERGIO track: runs experiments
README.md - Researcher → DREAM5 track: runs experiments
README.md - Synthetic track → Training and recalibration: compares methods
README.md - SERGIO track → Training and recalibration: compares methods
README.md - DREAM5 track → Training and recalibration: compares methods
README.md - SERGIO track → GRN utilities: may use
- DREAM5 track → GRN utilities: may use
- Synthetic track → Track 1 analyses: produces analyses
- SERGIO track → GRN analyses: produces analyses
- DREAM5 track → GRN analyses: produces analyses
- GRN utilities → Training and recalibration: implements training
track2_grn_calibration_experiments/grn_experiment_utils.py - GRN utilities → Metrics and evaluation: implements metrics
track2_grn_calibration_experiments/grn_experiment_utils.py - Training and recalibration → Metrics and evaluation: evaluates predictions
track2_grn_calibration_experiments/grn_experiment_utils.py