{"id": "package:8e790f7d-3f06-4c0c-95c2-23285c5ad7a6", "name": "Naplot.py", "self_uri": "https://services.scicrunch.io/sparc/drs/v1/objects/8e790f7d-3f06-4c0c-95c2-23285c5ad7a6", "size": 4990, "created_time": "2024-12-19T19:10:07,226002Z", "updated_time": "2024-12-19T19:11:51,417261Z", "version": "1", "mime_type": "text/x-python", "checksums": [{"checksum": "9e29adc2c7f56aaec9ba07b070b90eb0", "type": "sha256"}], "access_methods": [{"type": "s3", "access_url": {"url": "s3://sparc-prod-aod-discover-publish50-use1/453/files/code/IC_comp/Naplot.py"}, "region": "us-east-1"}], "dataset": {"id": "453", "doi": "DOI:10.26275/cy9w-ttjn", "title": "Biophysical modeling of neuronal phenotypes of the right atrial ganglionic plexus from single-neuron transcriptomics", "description": "Parallel conductance models using the Hodgkin-Huxley formalism informed by single-neuron transcriptomic data to select ion channel combinations.", "abstract": "The primary objective of the modeling study was to connect single-neuron RAGP transcriptomic data to cellular electrophysiology to understand the activity of neurons contributing to heart rate regulation. Not applicable (computational study) Single-neuron transcriptomic data can be used to construct a library of biophysical neuronal models that produce the range of electrophysiological behavior observed experimentally"}}