All software

MIRP

MIRP is a python package for quantitative analysis of medical images. It focuses on processing images for integration with radiomics workflows. These workflows either use quantitative features computed using MIRP, or directly use MIRP to process images as input for deep learning models.

BridgeDb Java

Java library for identifier mapping

svnecR

Easily calculate precession and obliquity from an astronomical solution and assumed or reconstructed values for dynamical ellipticity (Ed) and tidal dissipation (Td). This is a translation and adaptation of the C-code in Zeebe and Lourens (2022), with further details in Zeebe (2022).

CoMOLA

CoMOLA is a python tool for optimal spatial allocation of land uses. The tool creates optimal land-use maps for up to four objectives. It takes into account constraints and can be coupled with external models to evaluate different objectives (e.g. ecosystem services/biodiversity models)

ESMValCore

ESMValTool Core: core functionalities and driver for ESMValTool, a community diagnostic and performance metrics tool for routine evaluation of Earth System Models in CMIP.

ArrayAnalysis

ArrayAnalysis provides a user-friendly solution for transcriptomic data analysis. It allows researchers, regardless of their bioinformatics expertise, to efficiently analyse, explore, and interpret RNA sequencing and microarray datasets.

ESMValCore

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.

splithalfr

Estimates split-half reliabilities for scoring algorithms of cognitive tasks and questionnaires.

DeepRank

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

Ginkgo

Ginkgo is a high-performance math library for the solution of sparse linear systems on GPUs (AMD, Intel, NVIDIA). Ginkgo is implemented using modern C++ and provides preconditioned Krylov solvers, multigrid, sparse direct solvers, mixed precision, and batched functionality.

UrbEm - Urban Emission downscaling for air quality modeling

UrbEm enables in a modular manner downscaling of gridded regional emissions with specific spatial proxies based on a variety of open access, robust, sustainable and frequently updated sources. UrbEm can be applied to any urban area in Europe and provides methodological homogeneity between cities.