A reproducible workflow for binning and visualizing NMR (nuclear magnetic resonance) spectra from environmental samples. The 'nmrrr' package is intended for post-processing of NMR data, including importing, merging and, cleaning data from multiple files, visualizing NMR spectra, performing binning/integrations for compound classes, and relative abundance calculations. 
    This package can be easily inserted into existing analysis workflows by users to help with analyzing and interpreting NMR data.

A complete and seamless 'Nonmem' simulation interface from within R. Turns 'Nonmem' control streams into simulation control streams, executes them with specified simulation input data and returns the results. The simulation is performed by 'Nonmem', eliminating time spent and risks of re-implementation of models in other tools.

A Non-Metric Space Library ('NMSLIB' <https://github.com/nmslib/nmslib>) wrapper, which according to the authors "is an efficient cross-platform similarity search library and a toolkit for evaluation of similarity search methods. The goal of the 'NMSLIB' <https://github.com/nmslib/nmslib> Library is to create an effective and comprehensive toolkit for searching in generic non-metric spaces. Being comprehensive is important, because no single method is likely to be sufficient in all cases. Also note that exact solutions are hardly efficient in high dimensions and/or non-metric spaces. Hence, the main focus is on approximate methods". The wrapper also includes Approximate Kernel k-Nearest-Neighbor functions based on the 'NMSLIB' <https://github.com/nmslib/nmslib> 'Python' Library.

Perform an exploration and a preliminary analysis on the dose-
    response relationship of nanomaterial toxicity. Several functions are
    provided for data exploration, including functions for creating a subset of
    dataset, frequency tables and plots. Inference for order restricted dose-
    response data is performed by testing the significance of monotonic
    dose-response relationship, using Williams, Marcus, M, Modified M and 
    Likelihood ratio tests. Several methods of multiplicity adjustment 
    are also provided. Description of the methods can be found in <https://github.com/rahmasarina/dose-response-analysis/blob/main/Methodology.pdf>.