Showing 5 of total 5 results (show query)
metrumresearchgroup
mrgsolve:Simulate from ODE-Based Models
Fast simulation from ordinary differential equation (ODE) based models typically employed in quantitative pharmacology and systems biology.
Maintained by Kyle T Baron. Last updated 12 days ago.
138 stars 10.90 score 1.2k scripts 3 dependents
insightrx
PKPDsim:Tools for Performing Pharmacokinetic-Pharmacodynamic Simulations
Simulate dose regimens for pharmacokinetic-pharmacodynamic (PK-PD) models described by differential equation (DE) systems. Simulation using ADVAN-style analytical equations is also supported (Abuhelwa et al. (2015) <doi:10.1016/j.vascn.2015.03.004>).
Maintained by Ron Keizer. Last updated 1 months ago.
odepharmacodynamicspharmacokineticspharmacometricscpp
36 stars 9.44 score 100 scripts
sciml
diffeqr:Solving Differential Equations (ODEs, SDEs, DDEs, DAEs)
An interface to 'DifferentialEquations.jl' <https://diffeq.sciml.ai/dev/> from the R programming language. It has unique high performance methods for solving ordinary differential equations (ODE), stochastic differential equations (SDE), delay differential equations (DDE), differential-algebraic equations (DAE), and more. Much of the functionality, including features like adaptive time stepping in SDEs, are unique and allow for multiple orders of magnitude speedup over more common methods. Supports GPUs, with support for CUDA (NVIDIA), AMD GPUs, Intel oneAPI GPUs, and Apple's Metal (M-series chip GPUs). 'diffeqr' attaches an R interface onto the package, allowing seamless use of this tooling by R users. For more information, see Rackauckas and Nie (2017) <doi:10.5334/jors.151>.
Maintained by Christopher Rackauckas. Last updated 4 months ago.
daeddedelay-differential-equationsdifferential-algebraic-equationsdifferential-equationsodeordinary-differential-equationsscientific-machine-learningscimlsdestochastic-differential-equations
143 stars 8.42 score 31 scripts
jranke
mkin:Kinetic Evaluation of Chemical Degradation Data
Calculation routines based on the FOCUS Kinetics Report (2006, 2014). Includes a function for conveniently defining differential equation models, model solution based on eigenvalues if possible or using numerical solvers. If a C compiler (on windows: 'Rtools') is installed, differential equation models are solved using automatically generated C functions. Non-constant errors can be taken into account using variance by variable or two-component error models <doi:10.3390/environments6120124>. Hierarchical degradation models can be fitted using nonlinear mixed-effects model packages as a back end <doi:10.3390/environments8080071>. Please note that no warranty is implied for correctness of results or fitness for a particular purpose.
Maintained by Johannes Ranke. Last updated 2 months ago.
degradationfocus-kineticskinetic-modelskineticsodeode-model
11 stars 8.18 score 78 scripts 1 dependents
glasgowcompbio
shinyKGode:An Interactive Application for ODE Parameter Inference Using Gradient Matching
An interactive Shiny application to perform fast parameter inference on dynamical systems (described by ordinary differential equations) using gradient matching. Please see the project page for more details.
Maintained by Joe Wandy. Last updated 7 years ago.
differential-equationsgradient-matchinginferenceodesbml
2 stars 3.00 score 2 scripts