3DSpineMFE
A MATLAB® toolbox that given a three-dimensional spine reconstruction computes a set of characteristic morphological measures that unequivocally determine the spine shape.
The subcellular application was designed as a hub web based environment for creation and simulation of reaction-diffusion models integrated with the molecular repository. It allows also to import, combine and simulate existing models expressed with BNGL and SBML languages.
Two types of models are supported: rule-based models convenient and computationally efficient for modeling big protein signaling complexes and chemical reaction network models.
The subcellular application is integrated with a number of solvers for reaction-diffusion systems of equations. It supports simulation of spatially distributed systems using STEPS (stochastic engine for pathway simulation) – which provides spatial stochastic and deterministic solvers for simulation of reactions and diffusion on tetrahedral meshes.
The application provides as well a number of facilities for visualizing the models geometry and the results of the simulations.
The molecular repository is a publicly available database of biological information, relevant for brain molecular network modeling.
It accommodates several types of biological information which are not available from existing public databases, such as concentrations of proteins in different subcellular compartments of neuronal and glial cells, kinetic data on protein interactions specific for brain and synaptic signaling and plasticity, data on molecules mobility.
The repository is integrated with the subcellular application. They share the same set of entities described by BioNetGen expressions. The molecular repository can be queried from the subcellular application and the results of the query can be added to a molecular network model.
A MATLAB® toolbox that given a three-dimensional spine reconstruction computes a set of characteristic morphological measures that unequivocally determine the spine shape.
Arbor is a high-performance library for computational neuroscience simulations with multi-compartment, morphologically-detailed cells, from single cell models to very large networks. Arbor is written from the ground up with many-cpu and gpu architectures in mind, to help neuroscientists effectively use contemporary and future HPC systems to meet their simulation needs. Arbor supports NVIDIA and AMD GPUs as well as explicit vectorization on CPUs from Intel (AVX, AVX2 and AVX512) and ARM (Neon and SVE). When coupled with low memory overheads, this makes Arbor an order of magnitude faster than the most widely-used comparable simulation software. Arbor is open source and openly developed, and we use development practices such as unit testing, continuous integration, and validation.
BioExcel Building Blocks Workflows is a collection of biomolecular workflows to explore the flexibility and dynamics of macromolecules, including signal transduction proteins or molecules related to the Central Nervous System. Molecular dynamics setup for protein and protein-ligand complexes are examples of workflows available as Jupyter Notebooks. The workflows are built using the BioBB software library, developed in the framework of the BioExcel Centre of Excellence. BioBBis a collection of Python wrappers on top of popular biomolecular simulation tools, offering a layer of interoperability between the wrapped tools, which make them compatible and prepared to be directly interconnected to build complex biomolecular workflows.
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