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MuMoT (Multiscale Modelling Tool) is computational software running under Jupyter notebooks to provide interactive advanced mathematical and numerical analysis techniques to non-expert and expert users, without the need to write code or equations.
Data Types:
  • Software/Code
The file contains the codes and algorithms for the Mech-ABM. These include the descriptions of the algorithm to execute the mechanical model (Mech-), which deals with the biomechanics of the bone tissue; and the agent-based model (-ABM) which simulates the intercellular events of mechanotransduction after the activation of integrins (the predominant mechanoreceptors). The mechanical model is the .cpp with its application compute. The ABM files are file transition function code (.c), the agent-memory parameters (.xml) and 0.xml which include the initial state at t0. 0.xml include those for the homogeneous sensitive and ultrasensitive models and the heterogeneous models (10%-HM and 1%-HM). The files necessary for coupling the Mech- and the ABM models were included in the file "Essential Files to run hybrid model"
Data Types:
  • Software/Code
Interactive web application accompanying paper "Quantifying the benefits of using decision models with response time and accuracy data" The code associated with the application is contained in the `app.R` script. Dependencies are specified in `install.R` and can be installed by sourcing the script. The data powering the app is a subset of the data presented in the paper and can be found in `data/powersim.rda`. The raw subset of the data is contained in `raw-data/summary.csv` and the processing code into the tidied `.rda` format can be found in `raw-data/create-app-data.R`. Licenses Code See the LICENSE file Data : CC-BY-4.0 Copyright (c) 2018 Tom Stafford.
Data Types:
  • Software/Code
The Jupyter notebook in this repository generates the graphs for the paper, "Sensitivity Calculations of High-Speed Optical Receivers based on Electron-APDs" published in the IEEE Journal of Lightwave Technology. The file to generate the figures is the Jupyter notebook file "Figures for Sensitivity Calculations of High-Speed Optical Receivers based on Electron-APDs.ipynb". This generates all the figures. The notebook must be used in conjunction with the data in the corresponding data archive "Data for paper: "Sensitivity Calculations of High-Speed Optical Receivers based on Electron-APDs"" (DOI: 10.15131/shef.data.9959468)
Data Types:
  • Software/Code
This is a MATLAB package for inferring growth related parameters describing the shape and development of mollusc shells. It has an interactive fitting procedure and gives 3D models of the shells as part of the output.
Data Types:
  • Software/Code
MuMoT (Multiscale Modelling Tool) is computational software running under Jupyter notebooks to provide interactive advanced mathematical and numerical analysis techniques to non-expert and expert users, without the need to write code or equations.
Data Types:
  • Software/Code
The file contains the codes and algorithms for the Mech-ABM. These include the descriptions of the algorithm to execute the mechanical model (Mech-), which deals with the biomechanics of the bone tissue; and the agent-based model (-ABM) which simulates the intercellular events of mechanotransduction after the activation of integrins (the predominant mechanoreceptors). The mechanical model is the .cpp with its application compute. The ABM files are file transition function code (.c), the agent-memory parameters (.xml) and 0.xml which include the initial state at t0. 0.xml include those for the homogeneous sensitive and ultrasensitive models and the heterogeneous models (10%-HM and 1%-HM). The files necessary for coupling the Mech- and the ABM models were included in the file "Essential Files to run hybrid model"
Data Types:
  • Software/Code
Interactive web application accompanying paper "Quantifying the benefits of using decision models with response time and accuracy data" The code associated with the application is contained in the `app.R` script. Dependencies are specified in `install.R` and can be installed by sourcing the script. The data powering the app is a subset of the data presented in the paper and can be found in `data/powersim.rda`. The raw subset of the data is contained in `raw-data/summary.csv` and the processing code into the tidied `.rda` format can be found in `raw-data/create-app-data.R`. Licenses Code See the LICENSE file Data : CC-BY-4.0 Copyright (c) 2018 Tom Stafford.
Data Types:
  • Software/Code
This is a MATLAB package for inferring growth related parameters describing the shape and development of mollusc shells. It has an interactive fitting procedure and gives 3D models of the shells as part of the output.
Data Types:
  • Software/Code
Code used to analyse the dataset "Data.Rda" provided in this project. Produces extrapolations, estimates of lifetime mean survival and a hypothetical cost-effectiveness analysis. These are summarised via figures and tables, as presented in the manuscript "How uncertain is the survival extrapolation? A study of the impact of different parametric survival models on extrapolated uncertainty about hazard functions, lifetime mean survival and cost-effectiveness." To use this code, the libraries loaded at the start of the script need to be pre-installed, and Data.Rda should be placed in the same folder as this script. To visualise the hazard function, the functions 'pehaz' and 'muhaz' are used from the 'muhaz' library, giving noisy (piece-wise) and smooth estimates, respectively. Uncertainty about these estimates is obtained via bootstrapping. The package 'flexsurv' is used to fit seven standard parametric survival models (exponential, Weibull, Gompertz, Gamma, log-normal, loglogistic and generalised gamma). Also included is code for a simple two-state (well-death) markov model and corresponding health economic evaluation (cost-effectiveness analysis). Probabilistic sensitivity analysis (PSA) is carried out - this uses 10,000 samples. Only uncertainty in the survival models is considered. To output the results of this PSA it is assumed that a folder exists called 'SAVI' - data are exported into this folder, ready for analysis at http://savi.shef.ac.uk/SAVI/ (note the results of this further analysis are not reported as most value of information estimates were zero).
Data Types:
  • Software/Code