Implements the demographic model for the EA population of Tennessen et al. TennessenEAonly was used in a study that explores the impact of genetic model and population growth on distribution of genetic variance across the allele frequency spectrum underlying risk for a complex disease. This package has been implemented in Python and is available for local use.
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Performs models definition, simulators and formats. pLinguaCore is a library designed for cell-like, tissue-like and spiking neural-like P system simulators. The software provides several services, including parsers for input files and built-in simulators for cell-like P systems. It intends to cover as many variants of P systems as possible. pLinguaCore includes a built-in simulator for tissue P systems with cell separation rules.
Allows users to model, simulate and analyze complex, heterogeneous and multi-scale systems like a cell. E-Cell is a generic software package for cell simulation, based on structured Substance–Reactor Model (SRM), an object-oriented modeling theory. The software accepts multi-algorithms, multi-timescales and multi-spatial-representations as its central feature. It includes ordinary differential equations, Gillespie algorithm (the direct method), and spatial Gillespie algorithm.
Permits to automate the selection of a partitioning scheme given a set of user-defined data blocks as input. PartitionFinder can be used to compare millions of partitioning schemes in a single run and to select good and often optimal partitioning schemes for a large range of DNA data sets. It was developed to simplify the selection of partitioning schemes and lead to concomitant improvements in phylogenetic analyses.
An extension of SGNS, the stochastic simulator of SGNSim. SGNS contains all the features of SGNS, such as reactions with multi-delayed events. The two key additions in SGNS2 are (i) it supports dynamic, interlinked, hierarchical compartments and (ii) it supports multiple molecule and compartment partitioning schemes, applicable on a per-molecule-type basis. The novel features considerably extend the class of models that can be simulated. SGNS2 enables the modeling of stochastic processes in live cells that require compartmentalization, multi-delayed complex processes and complex stochastic partitioning schemes at a per-molecule type in cell division. These features are necessary to study in silico, among other phenomena, phenotypic diversity in cell populations.
Overcomes the limitations of parametric growth modelling. B-GREAT is based on a Gaussian process (GP) regression model of microbial growth. It is able to model growth curves that deviate from a sigmoid form. This tool was applied to yeast population growth data under diverse stress conditions and genetic backgrounds. It can recapitulate known differential growth phenotypes and enables discovery of novel phenotypes.
Allows the design, simulation and analysis of multicellular systems. Simbiotics is focused on modeling of bacterial populations, cellular species with individual behavior and interactions with their environment can be defined. It permits the simulation of large populations of multispecies communities. This tool provides a standard modeling library of processes typical to bacteria, such as growth, motility, gene regulation, metabolic activity and cell-surface appendages such as receptors and adhesins.
Proposes an autoregressive model using queries made through Google to evaluate influenza-like illnesses (ILI) activity. ARGO is a flu-tracking model that considers flu-related Google search frequencies, electronic health records and historical flu of multiple Google Flu Trends (GFT) engines. This application can be used to study the dynamics of various events with modulable parameters of space and time.
Allows to build and characterize agent based models of bacterial populations. BSim permits users to take multiple levels of detail and scale into account throughout modeling and simulation. It can predict the consequences of competition between the induced and uninduced sub-populations of bacteria. The tool allows for historic models to readily make use of improved knowledge and can be customized by users.
Performs semi-automatic spike sorting on large extra-cellular recordings. SpyKING CIRCUS is a method that assists in overlapping spikes. It works in two main steps: a clustering followed by a template matching step. First, spikes are detected as threshold crossings and then, the algorithm isolated the extracellular waveforms for a number of randomly chosen spike times.
Provides a demographic and genetic simulation framework for populations of species with overlapping generations. NeOGen is a point-and-click software package that gives an understanding of the sample numbers and genetic marker quantities that supply sufficient power to estimate Ne.LD for a focal population. It can guide genetic linkage disequilibrium Ne (Ne.LD) studies of iteroparous species and is useful throughout a study’s lifecycle.
Simulates and analyses stochastic models of population phylodynamics and chemical kinetics. MASTER supports the simulation of inheritance trees and networks under these same models. It allows user to specify a stochastic model in terms of a collection of individual reactions of this form, using a simple syntax. The tool can generate phylogenetic trees or networks alongside the histories they correspond to. It enables investigations into the interplay between genealogies and population dynamics.
Provides algorithms for the analysis of ecological networks. enaR uses a branch of network ecology: Ecosystem Network Analysis (ENA). ENA is a set of algorithms developed to analyze network models of energy or matter movement in ecosystems. This R package gathers workflow management functions and is customizable to support individual needs. It permits users to address relational questions at the core of ecology.
Provides a common platform for development of all individual-based models of microbial biofilms and such like. The iDynoMiCS software simulates the growth of microbial communities. iDynoMiCS is written in Java, and uses XML protocol files that allow one to specify easily many different types of simulations. iDynoMiCS writes plain-text XML files as output, and these may be processed using any number of software tools (though we provide some general post-processing routines that run in Matlab and R). In addition to XML files, iDynoMiCS also writes files for POV-Ray, which is used to render 3-D images of the simulation.
A set of mathematical models describing the induction of Epithelial to Mesenchymal Transition (EMT) by TGF-β isoforms in the presence or absence of vascular endothelial growth factor-A (VEGF-A). Reduced-EMT-Model allows the description of complex regulatory interactions in the absence of specific mechanistic information, it also allowed to build a predictive yet compact model. It also reveals a signaling axis, which possibly regulates carcinoma progression through an EMT versus tubulogenesis response.
Allows researchers to use existing biological knowledge in order to model the dynamics of a developmental process and analyze its behavior throughout the historical events. Simulated lineage trees can be used to validate various hypotheses in silico and to predict the behavior of dynamical systems under various conditions. Written under MATLAB environment, the tool also enables to easily integrate the output data within the user’s downstream analysis. eSTGt is an environment-dependent Stochastic Tree Grammars (eSTG) programming and simulation environment. When executing a program, the tool generates the corresponding lineage trees as well as the internal states values, which can then be analyzed either through the tool’s GUI or using MATLAB’s command-line environment.
Implements the Stochastic Process Model (SPM) methodology. stpm can be used not only for stochastic modeling of probabilities of endpoints but in many other applied areas, e.g., life science applications including biologically based modeling. The package was validated through simulation studies. The stpm R package can be extended by including: (i) SPM with several health states, (ii) SPM with hidden heterogeneity, (iii) SPM with competing risks, and (iv) SPM for partially observed covariates.
Provides a platform dedicated to the analysis, quantification, and sharing of phenotypic data. CellPD is a standalone software intended for both data quality control and a quantitative description and analysis of cell population dynamics. The application permits users to integrate experimental data into computational models. However, except via a source code modification, the software can only estimate parameters for predefined models.
Highlights differences between bacterial populations. DirtyGenes is useful with different types of data, such as metagenomics data, or quantitative polymerase chain reaction (qPCR) data. This tool is useful for computation number of samples needed in experiments.
Performs mathematical modeling for cell organisms. SimBio is an open source biological simulation platform that consists of five modules – two databases related to three different items for instantiation, calculation and steering – which have been developed independently for being adjusted to user needs. This program aims to ease the conception of models composed of functional modules and their complete or partly sharing.
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