Most biological processes are controlled by regulatory networks, which involve various kinds of molecular interactions, including protein-mediated transcriptional regulations, polypeptide receptor–ligand associations, protein modifications by specific enzymes, etc. Decades of genetic and molecular analyses, more recently complemented by high-throughput functional genomic experiments, have progressively uncovered many of the numerous interactions controlling several crucial biological processes (including cell cycle and various developmental pathways). The complexity of the networks delineated often defies intuitive reasoning, consequently calling for the development of proper computational tools. Different mathematical approaches have been proposed to model such genetic networks and to simulate their dynamical behaviour, ranging from quantitative formalisms to crude Boolean models.
Allows to perform structural and qualitative analysis of both mass-flow- and signal-flow-based cellular networks. CellNetAnalyzer is a toolbox for analyzing structure and function of biological networks on the basis of topological, stoichiometric, qualitative (logical) and semi-quantitative modeling approaches requiring no or only few parameters. Metabolic networks can be studied based on stoichiometric and constraint-based modeling approaches whereas signaling and regulatory networks can be explored by qualitative and semi-quantitative modeling approaches.
Extracts bifurcation transitions from discrete models of large interaction networks. Pint is a scalable method for automata networks (ANs) identification that relies on declarative programming with Answer-Set Programming (ASP). This approach is focused on non-deterministic discrete dynamics, in opposition to deterministic systems, such as piecewise-affine systems on which differentiation is determined by the initial state in a continuous space.
Supports the definition, the simulation and the analysis of regulatory graphs, based on the logical formalism. GINsim is a software that displays a window enabling the creation of a new model, the import of a model in a supported format, or the opening of a previously defined model. This tool leans on two main types of graphs: Logical Regulatory Graphs, which model regulatory networks, and State Transition Graphs, which represent their dynamical behavior.
Allows users to model and simulate genetic regulatory networks. GNA is specifically developed for the analysis of gene regulatory networks by means of piecewise-linear (PL) models. Users can define a regulatory network, build a model of this network, determine the steady states of the system, generate a state transition graph starting from an initial state and analyse the latter graph using model-checking tools. The software has been used to analyse a number of bacterial regulatory networks.
Assists in modeling signaling networks based on untargeted phosphoproteomics mass spectrometry (MS) data and kinase/phosphatase-substrate interactions. PHONEMeS is able to resume known relationships between distinct perturbed kinases and their substrates. It allows users to access the results data as a network of regulatory relationships. The software also offers the feature to rebuild paths from kinases inhibited on drug treatment to sites perturbed by these inhibitions.
Allows modeling of complex biological networks. Cell Collective is an online community modeling system based on understanding of the logic of the interactions of the individual components. The software allows scientists to deposit and track dynamical information about biological processes and integrate and interrogate this knowledge in the context of the biological process as a whole. It has a potential as an educational tool for undergraduate and graduate biology students with diverse mathematical/computer science skills.
Converts Boolean models into systems of ordinary differential equations (ODE). Odefy is a user-friendly implementation of the HillCube technique suitable for large-scale networks. The software provides access to different models sources, the conversion process and various analysis and export methods. A discrete model converted to an ODE by Odefy displays similar dynamical properties as a mechanistically derived ODE model of the same system.Converts Boolean models into systems of ordinary differential equations (ODE). Odefy is a user-friendly implementation of the HillCube technique suitable for large-scale networks. The software provides access to different models sources, the conversion process and various analysis and export methods. A discrete model converted to an ODE by Odefy displays similar dynamical properties as a mechanistically derived ODE model of the same system.
Integrates methods for synchronous, asynchronous and probabilistic (Boolean networks) BNs. This includes reconstructing networks from time series, generating random networks, robustness analysis via perturbation, Markov chain simulations, and identification and visualization of attractors.
A Cytoscape plugin to simulate the dynamics of signaling transduction using Boolean networks. SimBoolNet simulates the dynamics of signaling transduction using Boolean networks. Given a user-specified level of stimulation to signal receptors, SimBoolNet simulates the response of downstream molecules and visualizes with animation and records the dynamic changes of the network. It can be used to generate hypotheses and facilitate experimental studies about causal relations and crosstalk among cellular signaling pathways.
A tool for GUI-based modeling of Boolean Networks. ViSiBooL supports an extended version of synchronous Boolean Networks with temporal predicates. ViSiBooL allows user-friendly modeling, organization and visualization of these networks as well as attractor simulation for different experimental setups like e.g. knock-out experiments. ViSiBooL supports SBML-qual as well as BoolNet-syntax (BoolNet).
A Python package for the generation, modification and analysis of Boolean networks. The motivation for developing PyBoolNet was to offer a simple, well-documented interface to manipulating Boolean networks, model checking, standard graph algorithms, visualisation and state of the art attractor detection.
Performs Boolean modeling of Systems Biology/Pharmacology networks. SPIDDOR is based on a model for immune response to autoantigens and gives a feel of what can be done with its use. The resulting models can be used to analyze the dynamics of signaling networks associated to diseases to predict the pathogenesis mechanisms and identify potential therapeutic targets. SPIDDOR also includes an attractor search algorithm that searches the attractors for networks with less than 20 nodes, as the number of initial conditions to test grow exponentially with the number of nodes.
Supports systems biologists in the process of creation and analysis models of biological systems. More particularly, Holmes allows to create, simulate and analyze models based on various types of Petri nets. It offers means for drawing various types of nets and depending on a net type provides tools for the analysis and graphical representation of the results.
Offers a platform for studying whole cell population dynamics, cellular signaling mechanisms and cells and their environment interactions. PhysiBoSS is a combination of the MaBoSS and PhysiCell software that merges an agent-based method with a Boolean representation of biochemical events occurring in each cell. It can be used for investigating isomorphic morphogenesis events, response to treatment or cell modes of invasion.
Computes and displays in silico knockouts in mathematical models of biochemical systems. isiKnock displays predicted knockouts as color-coded matrix, red for affected and green for unaffected parts. It furnishes functionalities to custom the colors, the names of the reaction and species, or the order of the matrix entries. This tool assists users to detect potential targets for drug treatment and determine unknown effects of perturbations.
Conducts data evaluations and computes the inhibitory concentration 50% (IC50). Cheburator is able to perform data from sulforhodamine B (SRB) or tetrazolium dye (MTT) assays and can be used with any absorbance or luminescence-based assays. It is designed to analyze the results of assays performed on 96-well plates. To ensure good data quality and to minimize the impact of pipetting errors, each particular compound concentration is assessed based on the absorbance values from 3 separate wells.
Assists in simulation of brain circulation. Braincirc allows investigation of autoregulation and it includes equations representing blood flow, ion channel activity in the vascular smooth muscle and respiration from glycolysis to the electron transport chain.
A software for the dynamic modelling of regulatory networks using the Standardized Qualitative Approach. SQUAD has three novel aspects with respect to other approaches. First, the user needs to provide only the connectivity of a regulatory network; no rate values, interaction strengths, or kinetic data is needed as input. Second, the stable steady states of activation of the continuous model are automatically found, without the need of running the system from several initial states. And third, the resulting equations have diverse tunable parameters so as to provide the possibility to fit the continuous model to existing experimental data.
A Boolean regulatory network reconstruction using literature based knowledge. optimusqual has been implemented with a method which contextualized models from generic Prior knowledge networks (PKNs). Using a genetic algorithm, a model network is built as a sub-network of the PKN and trained against experimental data to reproduce the experimentally observed behaviour in terms of attractors and the transitions that occur between them under specific perturbations. The resulting model network is therefore contextualized to the experimental conditions and constitutes a dynamical Boolean model closer to the observed biological process used to train the model than the original PKN. These contextualized models have improved utility for hypothesis generation and experimental design.
Allows network simulation and analysis. ChemChains is a simulation and analysis suite allowing to visualize the dynamics of biological processes using non-mathematical, parameter-free logical models. The software allows biologists to perform simulations of their model under thousands of varying stimuli and learn how the models respond to different combinations of conditions. Users can also interact with mathematical models in a way which resembles laboratory experiments.