Stochastic IP3R Channel Dynamics and Calcium Oscillations¶
- Task ID:
biology.calcium_ip3_dyk_oscillations - Domain:
biology - Subdomain:
systems_biology - Status:
final - Benchmark set:
seed42(60tasks) - Tags:
calcium_signaling,ip3r,stochastic_simulation,gillespie,coherence_resonance,cellular_signaling
Runtime and requirements¶
- Estimated time:
30-60minutes - Python:
>=3.11 - Packages:
numpy>=2.0,scipy>=1.11,matplotlib>=3.7 - GPU required:
no - Network required:
no
Public input and output contract¶
Inputs¶
system_info.json(data): Public receptor state model, binding-interaction constants, compartment volumes, pump/leak parameters, and observation window settingsscan_spec.json(data): IP3 concentrations (ip3_levels) and channel counts (channel_counts) to sweep, T_obs, dt_out, n_replicatesexample_trajectory.npy(data): One example [Ca2+]_cytosol trace at a mid-range IP3 and mid-range channel count, for sampling-format sanity check
Outputs¶
simulate.py(code): Simulation script implementing the IP3R channel dynamics + calcium balanceca_traces.npz(data): Calcium traces for all (ip3_idx, N_idx) combinations; keys format 'ip3{i}_N{j}' with shape [n_replicates, n_samples]summary_stats.json(data): period_vs_ip3 (seconds), cv_isi_vs_N, p_open_vs_ip3, conservation_error_max, cr_ip3_idx_usedcalcium_summary.png(image): Multi-panel diagnostic figure combining representative Ca traces, period-vs-IP3, CV-vs-N, and P_open-vs-IP3.
Public repository files¶
Formal benchmark task directories in the public repository are metadata-only. Versioned prompts and inputs are distributed through the pinned benchmark dataset.
Provenance¶
This task is included in the current seed42 benchmark set at dataset revision f11a199f71fb4b854ac43a1bf548d5df519141a9.
This page is generated only from files tracked in the public ASI-Bench repository at commit f18382f03faf.
Submission bundles, run logs, private scoring configuration, and private reference answers are not read by this page generator.