Tools for 4D nucleome imaging. 
    Quantitative analysis of the 3D nuclear landscape recorded with super-resolved fluorescence microscopy. 
    See Volker J. Schmid, Marion Cremer, Thomas Cremer (2017) <doi:10.1016/j.ymeth.2017.03.013>.

Modelling the vegetation, carbon, nitrogen and water dynamics of undisturbed open bog ecosystems in a temperate to sub-boreal climate. The executable of the model can downloaded from <https://github.com/jeroenpullens/NUCOMBog>.

A comprehensive toolkit for calculating and visualizing Nitrogen Use Efficiency (NUE) indicators in agricultural research. The package implements 23 parameters categorized into fertilizer-based, plant-based, soil-based, isotope-based, ecology-based, and system-based indicators based on Congreves et al. (2021) <doi:10.3389/fpls.2021.637108>. Key features include vectorized calculations for paired-plot experimental designs, batch processing capabilities for handling large datasets, and built-in visualization tools using 'ggplot2'. Designed to streamline the workflow from raw agronomic data to publication-ready metrics and plots.

A framework for systematic exploration of
    association rules  (Agrawal et al., 1994, <https://www.vldb.org/conf/1994/P487.PDF>), 
    contrast patterns  (Chen, 2022, <doi:10.48550/arXiv.2209.13556>),
    emerging patterns  (Dong et al., 1999, <doi:10.1145/312129.312191>),
    subgroup  discovery (Atzmueller, 2015, <doi:10.1002/widm.1144>),
    and conditional correlations (Hájek, 1978,  <doi:10.1007/978-3-642-66943-9>).
    User-defined functions may also be supplied to guide custom pattern searches.
    Supports both crisp (Boolean) and fuzzy data. Generates candidate conditions
    expressed as elementary conjunctions, evaluates them on a dataset, and
    inspects the induced sub-data for statistical, logical, or structural
    properties such as  associations, correlations, or contrasts. Includes methods 
    for visualization of logical structures and supports interactive exploration
    through integrated Shiny applications.