All Tools

This is a jupyter lab extension which offers a UI component to monitor HPC jobs through Unicore interface. It allows users to easily switch between computing sites, retrieve details about the jobs, and also cancel them.

This is a jupyterlab extension built as a prototype for building EBRAINS (including TVB simulator, Siibra API) workflows in a visual and interactive manner. It extends the already existent Xircuits jupyterlab extension by adding new components and new features on top.

TVB-HPC provides a framework for generating high-performance computational kernels which can be run on HPC systems with or without hardware accelerators for large scale parameter fitting of brain models An overview over TVB-on-EBRAINS services is provided in the preprint https://arxiv.org/abs/2102.05888

TheVirtualBrain - Widgets is a package with somehow generic GUI components, but developed for EBRAINS Showcases in particular. The showcases developed in the last phase of the HBP are meant to illustrate the full potential of technical and scientific features offered by EBRAINS.

UG4 (Unstructured Grids 4) is an extensive, flexible, cross-platform open source simulation framework for the numerical solution of systems of partial differential equations. Using Finite Element and Finite Volume methods on hybrid, adaptive, unstructured multigrid hierarchies, UG4 allows for the simulation of complex real world models (physical, biological etc.) on massively parallel computer architectures. UG4 is implemented in the C++ programming language and provides grid management, discretization and (linear as well as non-linear) solver utilities. It is extensible and customizable via its plugin mechanism. The highly scalable MPI based parallelization of UG4 has been shown to scale to hundred thousands of cores. Simulation workflows are defined either using the Lua scripting language or the graphical VRL interface https://vrl-studio.mihosoft.eu/. Besides that, UG4 can be used as a library for third-party code. Several examples are provided in the Examples application that can be used for simulations of the corresponding phenomena but also serve as demonstration modules for implementing user-defined plugins and scripts. By developing custom plugins, users can extend the functionality of the framework for their particular purposes. The framework provides coupling facilities for the models implemented in different plugins. Key elements of UG4 are: Efficient solvers on distributed, adaptive multigrid hierarchies. A flexible component based discretization system. Efficient support for massively parallel computer architectures. Full scripting support. A modular plugin based architecture.

UNICORE (UNiform Interface to COmputing REsources) provides tools and services for building federated systems, making high-performance computing and data resources accessible in a seamless and secure way for a wide variety of applications in intranets and the internet. UNICORE's server components are installed at the resource provider site (e.g. JSC or CSCS) to provide a set of REST APIs for submitting and managing HPC jobs and related tasks like data access and data movement. UNICORE handles security aspects like federated authentication, user mapping and authorization.

Uncertainty quantification via ABC-MCMC with copulas as well as global sensitivity analysis for ODE models in systems biology. This R package can approximate the posterior probability density of Parameters for Ordinary Differential Equation models. The ABC sampler used here is developed to be fairly model agnostic, but the supplied tool set and R functions specifically target ODEs as they are fast enough to simulate to permit Bayesian methods. Bayesian methods for parameter estimation are resource intensive and therefore require some consideration of efficiency in simulation. Other modeling frameworks exist, with benefits of higher accuracy in specific scenarios (e.g. low molecule count), or reduced complexity (rule based models). We have written a sibling library for R that facilitates the simulation of systems biology specific models using the GNU scientific library solvers (and models written in C). With powerful enough computing hardware, or small enough models, these frameworks can be combined with this package. We write models using the SBtab format and automatically generate C-code as well as R-code for them, the R-code can be used with deSolve (an R package) while the C-code is compatible with gsl_odeiv2 solvers. Code generation is done via SBtabVFGEN (an R package) and vfgen (a standalone software). In addition, we are writing our own substitution for vfgen, to avoid single points of failure. But the model setup phase can be completely sidestepped by writing the C-code manually (or generating it in any other way).

Vaa3D is a handy, fast, and versatile 3D/4D/5D Image Visualization and Analysis System for Bioimages and Surface Objects. It also provides many unique functions that you may not find in other software. It is Open Source, and supports a very simple and powerful plugin interface and thus can be extended and enhanced easily. Vaa3D is cross-platform (Mac, Linux, and Windows). This software suite is powerful for visualizing large- or massive-scale (giga-voxels and even tera-voxels) 3D image stacks and various surface data. Vaa3D is also a container of powerful modules for 3D image analysis (cell segmentation, neuron tracing, brain registration, annotation, quantitative measurement and statistics, etc) and data management. This makes Vaa3D suitable for various bioimage informatics applications, and a nice platform to develop new 3D image analysis algorithms for high-throughput processing. In short, Vaa3D streamlines the workflow of visualization-assisted analysis. Vaa3D can render 5D (spatial-temporal) data directly in 3D volume-rendering mode; it supports convenient and interactive local and global 3D views at different scales... it comes with a number of plugins and toolboxes. Importantly, you can now write your own plugins to take advantage of the Vaa3D platform, possibly within minutes!

The Virtual Brain Inference (VBI) toolkit is an open-source, flexible solution tailored for probabilistic inference on virtual brain models. It integrates computational models with personalized anatomical data to deepen the understanding of brain dynamics and neurological processes. VBI supports fast simulations, comprehensive feature extraction, and employs deep neural density estimators to handle various neuroimaging data types. Its goal is to bridge the gap in solving the inverse problem of identifying control parameters that best explain observed data, thereby making these models applicable for clinical settings. VBI leverages high-performance computing through GPU acceleration and C++ code to ensure efficiency in processing.

A nascent Jax-based package for virtual brain modeling.

This software package offers a solution for epileptogenic zone network (EZN) diagnosis based on stimulation-induced seizures. Estimating the epileptogenic zone network (EZN) is an important part of the diagnosis of drug-resistant focal epilepsy and plays a pivotal role in treatment and intervention. Both invasive SEEG stimulation and non-invasive temporal interference (TI) stimulation are considered as a complementary approach. Inference step is based on STAN.

VIOLA (Visualization Of Layer Activity) is a lightweight, open-source, web-based, and platform-independent application combining and adapting modern interactive visualization paradigms, such as coordinated multiple views, for massively parallel neurophysiological data. It gives an insight into spatially resolved time series such as simulation results of neural networks with 2D geometry. With the multiple coordinated views, an explorative and qualitative assessment of the spatiotemporal features of neuronal activity can be performed upfront of a detailed quantitative data analysis of specific aspects of the data.

DC Explorer, Pyramidal Explorer and Clint Explorer are the core of an application suite designed to help scientists to explore their data. Vishnu is a communication framework that allows them to interchange information and cooperate in real-time. It provides a unique access point to the three applications and manages a database with the users’ data sets.

ViSimpl involves two components: SimPart and StackViz. SimPart is a three-dimensional visualizer for spatio-temporal data that allow spatio/temporal analysis of the simulation data, using particle-based rendering. StackViz illustrates how the electrophysiological variables evolve over time and provides a temporal representation of the data at different aggregation levels. They allow users to visually discriminate the activity of different groups of neurons, and provide detailed information about individual neurons of interest. These components share synchroniszed playback control of the simulation being analyzsed and work together as linked views, although they are loosely coupled and can also be used independently. They are ready to be used with BlueConfig Datasets among other file formats such as specific HDF5 and CSV. VisSimpl can be coupled with NeuroScheme for adding functionality such as navigate through the underlying structure of the data using symbolic representations and different levels of abstraction.

VisuAlign is one of several tools developed by the Human Brain Project (HBP) with the aim of facilitating brain atlas based analysis and integration of experimental data and knowledge about the human and rodent brain. VisuAlign is a tool for applying user-guided nonlinear refinements (inplane) to an existing, affine 2D-to-3D registration, such as created using QuickNII.

Viziphant is a Python module for easy visualization of Neo objects and Elephant results. It provides a high-level API to easily generate plots and interactive visualizations of neuroscientific data and analysis results. This API uses and extends the same structure as in Elephant to ensure intuitive usage for scientists that are used to Elephant.

voluba is an interactive web application which allows anchoring of volumetric image data to large reference image volumes at microscopic resolutions. The application is implemented around a 3D image viewer, and provides multiple reference brain templates as anchoring targets. Users can upload data from their own imaging experiments to a private working space to perform the alignment. The anchoring process includes interactive manipulation of image position, scale, and orientation, flipping of coordinate axes, as well as entering of anatomical point landmark pairs in 3D. From given landmarks, voluba calculates a 4x4 transformation matrix between the source and target image volumes. The transformation can be chosen with different degrees of freedom, including rigid, similarity and affine types. The result can be downloaded in a predefined json format which includes unique coordinate space identifiers. Furthermore, the aligned volume can be opened in the interactive atlas viewer siibra-explorer to link it to brain regions and related informations of the EBRAINS reference atlases.

voluba-mriwarp is a desktop application that integrates whole brain T1-weighted MRI scans into the anatomical context of the Julich Brain Atlas. It incorporates all required components like skull stripping, registration to ICBM MNI152 2009c nonlinear asymmetric space, and detailed analysis with the siibra toolsuite. The corresponding functionalities are provided via open-source tools like HD-BET, ANTs and siibra-python. voluba-mriwarp is primarily designed for Windows 10 but can also be executed on Linux.

VTK is an open-source software system for image processing, 3D graphics, volume rendering and visualization. VTK includes many advanced algorithms (e.g., surface reconstruction, implicit modelling, decimation) and rendering techniques (e.g., hardware-accelerated volume rendering, LOD control). VTK is used by academicians for teaching and research; by government research institutions such as Los Alamos National Lab in the US or CINECA in Italy; and by many commercial firms who use VTK to build or extend products. The origin of VTK is with the textbook "The Visualization Toolkit, an Object-Oriented Approach to 3D Graphics" originally published by Prentice Hall and now published by Kitware, Inc. (Third Edition ISBN 1-930934-07-6). VTK has grown (since its initial release in 1994) to a world-wide user base in the commercial, academic, and research communities.

One of the biggest recent changes in high-performance computing is the increasing use of accelerators. Accelerators contain processing cores that independently are inferior to a core in a typical CPU, but these cores are replicated and grouped such that their aggregate execution provides a very high computation rate at a much lower power. Current and future CPU processors also require much more explicit parallelism. Each successive version of the hardware packs more cores into each processor, and technologies like hyperthreading and vector operations require even more parallel processing to leverage each core’s full potential. VTK-m is a toolkit of scientific visualization algorithms for emerging processor architectures. VTK-m supports the fine-grained concurrency for data analysis and visualization algorithms required to drive extreme scale computing by providing abstract models for data and execution that can be applied to a variety of algorithms across many different processor architectures.