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
pyGAlib
GAlib works on adjacency matrices, represented as 2D numpy arrays. This choice certainly limits the size of the networks that the library can handle but it also allows to exploit the powers of numpy to manipulate arrays and boost the performance far beyond pure Python code. As a result, GAlib is simple to use and to extend; easy to read, access and modify. It has no hidden code, so you always know what every function actually does.
GAlib includes I/O and statistics tools, and a large set of functions for the analysis of graphs including clustering, distances and paths, matching index, assortativity, roles of nodes in modular networks, rih-club coefficients, K-core decomposition, etc. It also includes functions to generate random networks of different types, randomizing networks, as-well-as many examples and ready-to-use scripts useful also for complete beginners.
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