Unified and user-friendly framework for using new 
             distributional representations of biosensors data in different statistical modeling 
             tasks: regression models, hypothesis testing, cluster analysis, visualization, and 
             descriptive analysis. Distributional representations are a functional extension of 
             compositional time-range metrics and we have used them successfully so far in modeling 
             glucose profiles and accelerometer data. However, these functional representations can 
             be used to represent any biosensor data such as ECG or medical imaging such as fMRI.
             Matabuena M, Petersen A, Vidal JC, Gude F. "Glucodensities: A new representation of 
             glucose profiles using distributional data analysis" (2021) 
             <doi:10.1177/0962280221998064>.

Classes and functions to work with biological sequences (DNA, RNA and amino acid sequences).
    Implements S3 infrastructure to work with biological sequences as described in Keck (2020) <doi:10.1111/2041-210X.13490>.
    Provides a collection of functions to perform biological conversion among classes
    (transcription, translation) and basic operations on sequences
    (detection, selection and replacement based on positions or patterns).
    The package also provides functions to import and export sequences from and to other package formats.

Data processing tools to compute the rectified, integrated and the averaged EMG. Routines for automatic detection of activation phases. A routine to compute and plot the ensemble average of the EMG. An EMG signal simulator for general purposes.

A beginners toolbox to help those in ecology who want to deepen their understanding or utilize Bioacoustics in their work. The package has a number of utilizations from calculating frequency from waveform, performing operations in dB, and determining acoustic range of recorders. The majority of this package is based on key concepts learned from the K. Lisa Yang Center for Conservation Bioacoustics at Cornell University and their associated course: Introduction to Bioacoustics course. More information can be found within the walk through vignettes at <https://github.com/MattyD797/bioSNR/tree/main/vignettes>.