Model selection and parameter inference software tools

The growing field of systems biology has driven demand for flexible tools to model and simulate biological systems. Two established problems in the modeling of biological processes are model selection and the estimation of associated parameters. A…

The growing field of systems biology has driven demand for flexible tools to model and simulate biological systems. Two established problems in the modeling of biological processes are model selection and the estimation of associated parameters. A number of statistical approaches, both frequentist and Bayesian, have been proposed to answer these questions.

Implements parameter inference and model selection for dynamical systems in an…

Implements parameter inference and model selection for dynamical systems in an approximate Bayesian computation (ABC) framework. ABC-SysBio combines three algorithms: ABC rejection sampler, ABC SMC…

Reads a model of a biochemical reaction network in SBML format and produces a…

Reads a model of a biochemical reaction network in SBML format and produces a range of diagrams showing different levels of detail. sbml-diff can be used as a python package, allowing it to be…

Automates repetitive tasks in model building and simulation. SBpipe builds a…

Automates repetitive tasks in model building and simulation. SBpipe builds a sequence of repeated model simulations or parameter estimations, performs analyses from this generated sequence, and…

Provides a MATLAB interface for the SUNDIALS solvers CVODES and IDAS. AMICI…

Provides a MATLAB interface for the SUNDIALS solvers CVODES and IDAS. AMICI allows the user to specify differential equation models in terms of symbolic variables in MATLAB and automatically compiles…

A diffusive transport solver tailored to biological problems. BioFVM can…

A diffusive transport solver tailored to biological problems. BioFVM can simulate release and uptake of many substrates by cell and bulk sources, diffusion and decay in large 3D domains. It has been…

Allows the automated integration of experimental data into theoretical models…

Allows the automated integration of experimental data into theoretical models without requiring programming knowledge from the user. SBMLmod allows data integration and analysis with a minimal number…

Quantifies unknown model parameters of biological networks. SIOOR strategy…

Quantifies unknown model parameters of biological networks. SIOOR strategy allows users to identify a minimum number of unobserved nodes, for which the associated node variables should be observed in…

Facilitates the simulation and analysis of complex network models. Epigrass…

Facilitates the simulation and analysis of complex network models. Epigrass aims to help designing and simulating network-epidemic models with any kind of node behavior. It enables researchers to…

Assists users in identification of potential outbreaks of infectious diseases.…

Assists users in identification of potential outbreaks of infectious diseases. Netabc is a model-based parametric clustering method that can recover clusters of rapid transmission in simulated data.…

Provides a R package introducing a statistical method for modeling disease…

Provides a R package introducing a statistical method for modeling disease transmission. The package allows users to settle individual-level spatiotemporal data, in a mechanistic manner or accounting…

Promotes systematic searches within the study design space. LIFESPAN generates…

Promotes systematic searches within the study design space. LIFESPAN generates a set of alternative models with equal statistical power to detect hypothesized effects, and delineates trade-off…

Provides highly parallelized algorithms for the repeated simulation of…

Provides highly parallelized algorithms for the repeated simulation of biochemical network models on NVIDIA CUDA GPUs. Algorithms are implemented for the three popular types of model formalisms: the…

A graphical Java Bayesian evidence analysis tool implementing nested sampling - an algorithm yielding an estimate of the log of the Bayesian evidence Z and the moments of model parameters, thus…

A computational tool for model selection and parameter inference using nested…

A computational tool for model selection and parameter inference using nested sampling. SYSBIONS follows a standard routine with optional extensions and additional features.

A network inference model based on nested effects models (NEMs). NEMix learns…

A network inference model based on nested effects models (NEMs). NEMix learns networks from single cell observations, accounting for noisy pathway activation in the data.

Enables generation of networks with a specified degree distribution, measuring…

Enables generation of networks with a specified degree distribution, measuring fundamental network characteristics. EpiFire is an application programming interface (API) allowing user to perform…

Generates and discriminates model alternatives. modelIMaGe generates SBML or…

Generates and discriminates model alternatives. modelIMaGe generates SBML or Copasi candidate models by removing specified model components from a given master model and automatically documents them.…

Allows user to make simulation and graphical model design. The Narrator purpose…

Allows user to make simulation and graphical model design. The Narrator purpose is to simplify development of biological systems. Its configuration is useful to create maps available with different…

Provides functions to develop tool, or execute simulation. Xholon is a…

Provides functions to develop tool, or execute simulation. Xholon is a multi-paradigm modeling, transformation and simulation tool, in which applications are constructed using XML and Java. This tool…

Performs optimal experiment design (OED) for models that cope with large…

Performs optimal experiment design (OED) for models that cope with large parameter uncertainty. PUA is not limited to any specific error model or assumption regarding the parameter distribution. It…

A software package for applying the Bayesian inferential methodology to…

A software package for applying the Bayesian inferential methodology to problems in systems biology. BioBayes provides a framework for Bayesian parameter estimation and evidential model ranking over…

Uses variational Bayesian inference to learn hidden Markov models from…

Uses variational Bayesian inference to learn hidden Markov models from individual, single-molecule fluorescence resonance energy transfer efficiency (EFRET) versus time trajectories. VBFRET…

Calculates the marginal state occupation probabilities, the state entry and…

Calculates the marginal state occupation probabilities, the state entry and exit time distributions, and the marginal integrated transition hazard for a general, possibly non-Markov, multistate…

A statistical approach to computing the Bayesian evidence Z, to the inference…

A statistical approach to computing the Bayesian evidence Z, to the inference of parameters, and the estimation of log Z in an established model of circadian rhythms. NestedSamplingRCode improves the…

Allows communication between heterogeneous application components. SBW is a…

Allows communication between heterogeneous application components. SBW is a computational resource sharing framework that allows applications to communicate with each other efficiently and without…

Furnishes a customizable structure for systems’ simulation, modeling and…

Furnishes a customizable structure for systems’ simulation, modeling and analytics. WOLFRAM SystemModeler gives access to wide range of modeling libraries, based on Modelica standard, for…

Allows access to all Schrödinger's computational technology. Maestro 11…

Allows access to all Schrödinger's computational technology. Maestro 11 tries to help researchers in the organization and the analysis of data. This tool uses a modern, intuitive environment…

A trajectory-based Bayesian experiment design approach. BayesFisher is…

A trajectory-based Bayesian experiment design approach. BayesFisher is successfully applied to reduce prediction uncertainty of an optimal experiment design (OED) model of secretory pathway control…