1 - 50 of 107 results


Connects genome-scale models to genome annotations and external databases. BiGG Models is a completely redesigned Biochemical, Genetic and Genomic knowledge base. It contains more than 75 high-quality, manually-curated genome-scale metabolic models. This software provides a comprehensive application programming interface for accessing BiGG Models with modeling and analysis tools. It can facilitate diverse systems biology studies and support knowledge-based analysis of diverse experimental data.


Constructs abstractions using information Dynamic Bayesian Network (DBN). DBNizer reduces the number of variables from 92 to 10, and accelerates numerical simulation by an order of magnitude, yet preserving essential features of cell death time distributions. It generates a large number of trajectories of the underlying biochemical model by numerical integration of the original model. The tool selects the suitable subset of variables to be used for DBN construction and infers their edge relationships.


A MATLAB environment to solve mathematical optimization problems which in dynamic modeling and control of biological systems. AMIGO2 is organized in four main modules: the pre-processor, the numerical kernel, the post-processor and the module of main tasks. It covers the iterative identification of dynamic models, it allows using optimality principles for predicting biological behavior and it deals with the optimal control of biological systems using constrained multi-objective dynamic optimization. It supports general non-linear deterministic dynamic models and black-box simulators, dealing with ordinary, partial or delay differential equations. AMIGO also offers various methods to analyze model identifiability: (i) local and global parametric sensitivities; (ii) the Fisher Information Matrix for an asymptotic analysis; (iii) cost contour plots and (iv) a robust Monte-Carlo sampling approach.

BIOCHAM / BIOCHemical Abstract Machine

Designs formal languages for describing qualitative or quantitative models of biochemical systems. BIOCHAM is based on a s rule-based language and on a temporal logic language. It permits continuous or stochastic simulations, and model validation or revision with respect to a formal qualitative or quantitative specification. This tool can be provided with various types of information, qualitative or quantitative, that can be found in the literature.

ASPASIA / Automated Simulation Parameter Alteration and SensItivity Analysis

Addresses a key deficiency in software tools for understanding the impact an intervention has on system behaviour for models specified in Systems Biology Markup Language (SBML). ASPASIA can generate and modify models using SBML solver output as an initial parameter set, allowing interventions to be applied once a steady state has been reached. Additionally, multiple SBML models can be generated where a subset of parameter values is perturbed using local and global sensitivity analysis techniques, revealing the model’s sensitivity to the intervention.

SED-ML Web Tools / Simulation Experiment Description Markup Language Web Tools

Supports users in generating, modifying, simulating, and exporting standard compliant simulation experiments. SED-ML Web Tools implement all current SED-ML specifications and, thus, support complex modifications and co-simulation of models in SBML and CellML formats. It provide an easy-to-use wizard to generate SED-ML files for a model encoded in the SBML format. SED-ML Web Tools supports researchers in developing simulation studies that comply with the SED-ML standard.

bnstruct / Bayesian Network Structure Learning from Data with Missing Values

Provides algorithms to i) learn the structure and the parameters of a Bayesian Network from data in the presence of missing values and ii) perform reasoning and inference on the learned Bayesian Networks. Bnstruct can handle both discrete and continuous variables in the dataset manipulation and imputation and infer the estimated probability distribution of some variables. It also contains methods for learning using the Bootstrap technique.

SpaceScanner / adjustable parameter solution space scanner

Allows to manage global stochastic studies. SpaceScanner supports: (1) parallel optimization runs with automated recognition of consensus and stagnation situations, (2) automatic switching between different user-selected global stochastic optimization methods in case of stagnation in the current method, (3) determination of the best sets of adjustable parameters for a pre-set range of a number of adjustable parameters in combination, and (4) search for the minimal number of adjustable parameters that can reach the requested fraction of the total optimization potential.

Microvessel Chaste

Builds spatial models of vascularized tissue growth. Microvessel Chaste can be used to simulate vessel growth and adaptation in response to mechanical and chemical stimuli, intra- and extra-vascular transport of nutrient, growth factor and drugs, and cell proliferation in complex 3D geometries. The library provides a comprehensive Python interface to solvers implemented in C++, allowing user-friendly model composition, and integration with experimental data. Such integration is facilitated by interoperability with a growing collection of scientific Python software for image processing, statistical analysis, model annotation and visualization. Microvessel Chaste is a plug-in for the Chaste C++ library.


Aims to provide an SBML parser and library that maps all SBML elements to a flexible and extended type hierarchy. JSBML is a community-driven project to create a free, open-source, pure Java library for reading, writing, and manipulating SBML files and data streams. It is an alternative to the mixed Java/native code-based interface provided in libSBML. Where possible, it strives to attain 100 per cent API compatibility with the libSBML Java API, to facilitate a switch from one library to the other.


Provides accurate and efficient algorithms for kinetic model construction. PyEMMA can read all common molecular dynamics data formats and helps in the selection of input features. It provides easy access to dimension reduction algorithms such as principal component analysis (PCA) and time-lagged independent component analysis (TICA) and clustering algorithms such as k-means, and contains estimators for Markov (state) models (MSMs), hidden Markov models, and several other models. Systematic model validation and error calculation methods are provided. PyEMMA offers a wealth of analysis functions such that the user can conveniently compute molecular observables of interest. Plotting functions to produce a manuscript-ready presentation of the results are available.

DBSolve Optimum

Allows users to develop, analyze kinetic models and visualize simulation results. DBSolve Optimum focuses on comprehensive work with kinetic model of a biological system including model development, verification, analysis and visualization. It is able to perform fitting the model to experimentally measured time dependence and dependence of steady state on parameter simultaneously. This tool offers features to animate simulation results and present them in a comprehensible mode.

SensSB / Sensitivity analysis for Systems Biology

Allows users to develop and analyse systems biology models. SensSB’s main features are: (i) Global sensitivity analysis (GSA), (ii) Pseudo-Global a priori identifiability analysis, (iii) optimal experimental design (OED) based on GSA, (iv) Robust parameter estimation (PE), (v) Local sensitivity and identifiability analysis, (vi) Confidence intervals and (vii) OED based on local Sensitivity analysis (SA). The software can assist the modeler along the integral modeling cycle.


A tool for evolving and designing biochemical reaction networks using genetic algorithm (GA). Typically, a BioJazz user wishes to evolve or design a small network or motif which accomplishes a specific function, such as a switch or an oscillator module. The network comprises a set of proteins whose attributes are encoded in a network's ''genome''. The ''genome'' is a binary string which contains all the information necessary to determine how many proteins are present in the network, their structure, which proteins interact and the biochemical parameters of their interaction.

PhysiCell / Physics-based multiCellular simulator

An agent-based model for 3-D multicellular simulations. PhysiCell provides both the stage and the players for studying many interacting cells in dynamic tissue microenvironments. It includes biologically-driven sub-models for cell cycling, apoptosis, necrosis, solid and fluid volume changes, mechanics, and motility outof the box, allowing modelers to concentrate on microenvironment-driven hypotheses. PhysiCell to help the scientific community tackle multicellular systems biology problems involving many interacting cells in multi-substrate microenvironments.

MOCCASIN / Model ODE Converter for Creating Automated SBML INteroperability

Takes ordinary differential equation (ODE) models written in MATLAB and export them as SBML files. MOCCASIN aims to facilitate scripting and automation. The tool offers (1) a module that parses MATLAB files; (2) a module that extracts the ODE-based model and produces a model with explicit ODEs; (3) a module that infers the biochemical reactions implied by the ODEs and produces SBML output with biochemical reactions for kinetics; (4) a command line interface and (5) a graphical user interface (GUI).


It is designed for computationally efficient and user-friendly integration of complex experimental data into models consisting of coupled non-linear ordinary differential equations (ODE). The numerically expensive parts of the calculations such as the solving of the differential equations and of the associated sensitivity system are parallelized and automatically compiled into efficient C code. A variety of parameter estimation algorithms as well as frequentist and Bayesian methods for uncertainty analysis have been implemented and used on a range of applications that lead to publications.

COSMOS / Computation of Sensitivities in Model ODE Systems

Allows sensitivity analyses of metabolic reaction systems. COSMOS is a program that automates assessments of model stability and sensitivity for essentially arbitrary pathway models. A key feature of the software is its highly accurate strategy of numerical differentiation, which is unavoidably involved in the calculation of sensitivities and eigenvalues. Its accuracy is guaranteed by the use of the so-called complex-step Taylor method for all numerical differentiation steps.


Quantifies the analgesic-like effects of chemical stimuli or genetic mutations. C-elegans has been designed to build a statistical model of the heat stimulus and infer the changes in the perceived level of the stimulus felt by the organism due to perturbation in the sensory transduction pathway. The existence of this template allows to solve one of the hard questions in pain research: disambiguating analgesic-like effects of drugs or genetic perturbations from their other effects on animal behavior.


Aims to overcome the challenges of modelling spatio-temporal Ca2+ dynamics. This tool uses the experimentally reconstructed 3-D structures for the transverse-tubule (TT) and sarcoplasmic reticulum (SR) at the whole-cell scale. It can capture spatio-temporal calcium dynamics with a realistic network SR structure and membrane fluxes distributed according to the sarcolemma/TTs. The tool permits users to understand structure-function relationships in physiological and pathophysiological cardiac electro-mechanics.


An extensible, high-performance, cross-platform, open-source software library for the simulation and analysis of models expressed using Systems Biology Markup Language (SBML). SBML is the most widely used standard for representing dynamic networks, especially biochemical networks. libRoadRunner is fast enough to support large-scale problems such as tissue models, studies that require large numbers of repeated runs and interactive simulations. libRoadRunner is a self-contained library, able to run both as a component inside other tools via its C++ and C bindings, and interactively through its Python interface. libRoadRunner’s speed and ease of integration allow researchers to solve very large models, include models embedded in multi-scale systems and run large ensembles of smaller models.

saCeSS / self-adaptive Cooperative enhanced Scatter Search

Accelerates the solution of the problem of parameter estimation in nonlinear dynamic models. saCeSS is based on the scatter search optimization metaheuristic and incorporates several key new mechanisms: (i) asynchronous cooperation between parallel processes, (ii) coarse and fine-grained parallelism, and (iii) self-tuning strategies. It allows very significant reduction of computation times with respect to several previous state of the art methods (from days to minutes, in several cases) even when only a small number of processors is used.

VCell / Virtual Cell

A problem solving environment, built on a central database, for analysis, modelling and simulation of cell biological processes. VCell integrates a growing range of molecular mechanisms, including reaction kinetics, diffusion, flow, membrane transport, lateral membrane diffusion and electrophysiology, and can associate these with geometries derived from experimental microscope images. It has been developed and deployed as a web-based, distributed, client-server system, with more than a thousand world-wide users.


Assists in modeling the dynamically evolving somatic response of neurons receiving complex spatio-temporal synaptic input patterns. This method is a model-based approach for analyzing dendritic integration. It also describes the input-output transformation of single neurons with complex dendritic trees. It was developed with a hierarchical cascade of linear-nonlinear subunits (hLN) that predicts the membrane potential of a detailed biophysical model of a L2/3 pyramidal cell receiving in vivo-like synaptic input and reproducing in vivo dendritic recordings.