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11 to 20 of 22 Results
Python Source Code - 10.1 KB - MD5: 799aec9a1f707be058aceb3aee3f3bed
Python script to perform MCMC sampling on the CBSD model using the PEtab files
Python Source Code - 3.4 KB - MD5: 7c6b8e987ef2a9a70be164d7cc7473de
Python script to calibrate the CBSD model using the PEtab files
Python Source Code - 3.2 KB - MD5: 069279f5c3f88174e068fb86fead4956
Tabular Data - 975.4 KB - 5 Variables, 22145 Observations - UNF:6:sQocf/P7vdAmWMQR6rEEJw==
ZIP Archive - 253.7 KB - MD5: ab623a378ff0a0b286e75ed76379cc92
ZIP Archive - 810.7 MB - MD5: 71bbc489782cf6c1cde7d22ad272167a
BayModTS results of the steatosis application using a broader prior for validation.
ZIP Archive - 794.7 MB - MD5: 59ebfc89816bc3c3ce5c5dcea77237b4
PEtab files and results of the BayModTS steatosis application.
ZIP Archive - 279.0 MB - MD5: bb20d18e0d920146e7e17cf273efc286
Application of the BayModTS workflow to the steatosis data, replacing the Retarded Transient Functions (RTFs) with a mechanistic pharmacokinetic model.
ZIP Archive - 228.2 MB - MD5: d0d04b3f5de2c6beb86e0ec050f9f87c
BayModTS results of the liver regeneration example using a broader prior for validation. The data was generated under the ZeLeR-study (ethical vote: 2018- 1246-Material).
ZIP Archive - 235.3 MB - MD5: a773c2789331928ce36e310682da4360
PEtab files and results of the BayModTS liver regeneration example. The data was generated under the ZeLeR-study (ethical vote: 2018- 1246-Material).
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