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13-24 of 99
Logo for EnrichedHeatmap

EnrichedHeatmap

Enriched heatmap is a special type of heatmap which visualizes the enrichment of genomic signals on specific target regions. The EnrichedHeatmap package provides advanced solutions for normalizing genomic signals within target regions as well as offering highly customizable visualizations.

  • Data analysis
  • Data Visualization
  • FAIR Data
  • + 2
  • R
  • CSS
  • C++
1
222
Logo for simplifyEnrichment

simplifyEnrichment

A new clustering algorithm, "binary cut", for clustering similarity matrices of functional terms is implemeted in this package. It also provides functions for visualizing, summarizing and comparing the clusterings.

  • Data analysis
  • Data Visualization
  • FAIR Data
  • + 3
  • R
  • CSS
1
217
Logo for SeisBench: A toolbox for machine learning in seismology

SeisBench: A toolbox for machine learning in seismology

SeisBench is an open-source Python toolbox for machine learning in seismology. It brings together the whole machine learning model lifecycle: datasets and benchmarks, models and training pipelines, and efficient implementations for deploying the models in production.

  • Earth & Environment
  • GPU
  • Helmholtz AI
  • + 4
  • Jupyter Notebook
  • Python
6
198
Logo for ESMValCore

ESMValCore

  • Data analysis
  • Earth & Environment
  • FAIR Software
  • + 2
  • Python
  • Jupyter Notebook
  • HTML
  • + 5
46
117

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.

  • Data analysis
  • MRI
  • open source
  • + 1
  • Python
2
113
Logo for rGREAT

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.

  • Data analysis
  • Data Visualization
  • FAIR Data
  • + 3
  • R
  • C++
1
110
Logo for alpaka

alpaka

The alpaka library is a header-only C++17 abstraction framework designed for computing accelerator development. It enables developers to implement algorithms once and execute them across a range of platforms, including x86, ARM, and RISC-V CPUs, as well as accelerators from NVIDIA, AMD, and Intel.

  • C++
  • CPU
  • CUDA
  • + 7
  • C++
  • CMake
  • Shell
  • + 1
34
87
Logo for oemof.solph

oemof.solph

oemof.solph is a model generator for energy system modelling and optimisation. It facilitates the formulation of (mixed-integer) linear programs from a generic graph-based structure, allowing to create multi-sector models on different levels of detail with user-defined time-resolution.

  • Energy
  • Energy System Analysis
  • ESD
  • + 2
  • Python
29
74
Logo for CiTYCHEM

CiTYCHEM

The CiTYCHEM extension of the EPISODE dispersion model is designed for treating complex atmospheric chemistry in urban areas and improved representation of the near-field dispersion. Applications are urban air quality studies, environmental impact assessments and sector-specific emission studies.

  • Air Pollution
  • Air quality
  • Earth & Environment
  • + 6
    6
    67
    Logo for cola

    cola

    Subgroup classification is a basic task in genomic data analysis. The cola package provides a general framework for subgroup classification by consensus partitioning.

    • Data analysis
    • Data Visualization
    • FAIR Data
    • + 3
    • R
    • C++
    1
    51
    Logo for MEmilio

    MEmilio

    MEmilio implements various models for infectious disease dynamics, from compartmental to agent-based models. Through efficient implementation and parallelization, MEmilio brings cutting edge and compute intensive models to a large scale, enabling high-resolution spatiotemporal disease dynamics.

    • Agent-based Model
    • C++
    • compartmental model
    • + 12
    • C++
    • Python
    • CMake
    • + 2
    22
    51

    FatSegNet

    A fully automated deep learning pipeline for adipose tissue (visceral and subcutaneous) segmentation on abdominal Dixon MRI.

    • Data analysis
    • MRI
    • open source
    • Python
    • Dockerfile
    • Shell
    2
    49