All software

ESMValCore

Materials Learning Algorithms

MALA (Materials Learning Algorithms) is a data-driven framework to accelerate electronic structure calculations based on machine learning. Its purpose is to construct neural-network surrogate models for bypassing computationally expensive steps in state-of-the-art density functional simulations.

BrainPrint

Our BrainPrint tools provide shape descriptors of neuroanatomical structures and require a FreeSurfer or FastSurfer segmentation as a pre-processing step. BrainPrint is based on “ShapeDNA” a spectral shape descriptor.

Paired omics data platform

If you do metabolomics experiments with mass spectra and have sequenced the genomes of the samples, then the platform can help you link them.

DeepRank

Deep learning framework for data mining protein-protein interactions using CNN

rGREAT

GREAT is a type of functional enrichment analysis directly performed on genomic regions. This package implements the GREAT algorithm, also it supports directly interacting with the GREAT web service (the online GREAT analysis). Both analysis can be viewed by a Shiny application.

RiboDetector

RiboDetector is designed to rapidly and accurately detect rRNA sequences from metagenomic, metatranscriptomic, and ncRNA sequencing data. It has been optimized for use with both CPUs and GPUs. It outperforms existing software by delivering 10-50x faster runtime and ~10x fewer false classifications.

Scalasca

The Scalasca Trace Tools support performance optimization of parallel programs with a collection of highly scalable trace-based tools for in-depth analyses of concurrent behavior, in particular with respect to communication and synchronization, and offers guidance in exploring their causes.

TraP: The LOFAR Transients Pipeline

The LOFAR Transients Pipeline (or "TraP") is a Python and SQL based system for detecting and responding to transient and variable sources in a stream of astronomical images.

BornAgain

Software to simulate and fit neutron and x-ray reflectometry and grazing-incidence small-angle scattering. The latter is computed as usual, using the distorted-wave Born approximation, hence the name. Users can set up arbitrary multilayer samples with interface roughness and embedded nanoparticles.

MAGMa

MAGMa is an online application for the automatic chemical annotation of mass spectrometry data.

GrainLearning

Unsure about the parameters of your grains in a computer simulation? Use Iterative Bayesian Filtering to learn parameter distributions from limited data. Is your model running slowly? Speed up your simulations with machine-learning surrogates. All these features are integrated within GrainLearning.