Supplementary Code for: Modeling the Binding-Site Barrier in Tumor Spheroids: Arithmetically Stable Admittance Mapping
收藏DataCite Commons2026-04-22 更新2026-05-04 收录
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https://data.mendeley.com/datasets/ch6wr298dv/1
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资源简介：
This repository contains the complete Python codebase required to reproduce the numerical benchmarks and Bayesian inference pipelines presented in the associated manuscript. It includes:
The O(N) steady-state admittance propagator.
The hybridized Picard-Admittance solver for non-linear Michaelis-Menten kinetics.
The Laplace-domain Gaver-Stehfest transient solver.
Continuous FEM collocation algorithms used for ground-truth generation.
Scripts generating the arithmetic viability maps and MCMC posterior predictive checks.
本仓库包含用于复现相关研究手稿中所呈现的数值基准测试与贝叶斯推断流水线所需的完整Python代码库。具体涵盖以下内容：
1. 复杂度为O(N)的稳态导纳传播子（steady-state admittance propagator）
2. 面向非线性米氏动力学（Michaelis-Menten kinetics）的混合皮卡-导纳求解器（hybridized Picard-Admittance solver）
3. 拉普拉斯域盖弗-施特费斯瞬态求解器（Laplace-domain Gaver-Stehfest transient solver）
4. 用于生成基准真值的连续有限元配点算法（continuous FEM collocation algorithms）
5. 用于生成算术可行性映射图与马尔可夫链蒙特卡洛（MCMC, Markov Chain Monte Carlo）后验预测检验的脚本
提供机构：
Mendeley Data
创建时间：
2026-04-22
