3DSpineMFE
A MATLAB® toolbox that given a three-dimensional spine reconstruction computes a set of characteristic morphological measures that unequivocally determine the spine shape.
Modelling and simulation
PyCOMPSs
PyCOMPSs is the Python binding of COMPSs, a programming model and runtime which aims to ease the development of parallel applications for distributed infrastructures, such as Clusters and Clouds. The Programming model offers a sequential interface but at execution time the runtime system is able to exploit the inherent parallelism of applications at task level. The framework is complemented by a set of tools for facilitating the development, execution monitoring and post-mortem performance analysis.
A PyCOMPSs application is composed of tasks, which are methods annotated with decorators following the PyCOMPSs syntax. At execution time, the runtime builds a task graph that takes into account the data dependencies between tasks, and from this graph schedules and executes the tasks in the distributed infrastructure, taking also care of the required data transfers between nodes.
Other software
All softwareArbor
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.
Modelling and simulationCellular level simulation
BioExcel Building Blocks
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.
Modelling and simulationMolecular and subcellular simulation