MUSCLE performs multiple sequence alignments of nucleotide or amino acid sequences.

Extract Muscle Synergies from Electromyography
person("Alessandro", "Santuz", , "alessandro.santuz@gmail.com", role = c("aut", "cre"),
comment = c(ORCID = "0000-0002-6577-5101"))
Provides a framework to factorise electromyography (EMG) data.
Tools are provided for raw data pre-processing, non negative matrix factorisation,
classification of factorised data and plotting of obtained outcomes.
In particular, reading from ASCII files is supported, along with wide-used
filtering approaches to process EMG data. All steps include one or more sensible
defaults that aim at simplifying the workflow. Yet, all functions are largely
tunable at need. Example data sets are included.
FNN, ggplot2, graphics, grDevices, gridExtra, gtools, pbapply,
plyr, proxy, reshape2, signal, stats, umap
Alessandro Santuz [aut, cre] (<https://orcid.org/0000-0002-6577-5101>)

FNN, ggplot2, graphics, grDevices, gridExtra, gtools, plyr,
proxy, reshape2, signal, stats, umap

FNN, ggplot2, graphics, grDevices, gridExtra, plyr, proxy,
reshape2, signal, stats, umap

muscor is a package that solves a number of convex/non-convex sparse regularization formulations for regression or binary classification using multi-stage convex relaxation algorithm, described in the paper "Multi-stage Convex Relaxation for Learning with Sparse Regularization". Loss functions include least squares, logistic, truncated ls/huber. Regularization conditions include Lp + L2 (p in (0,1]), or capped-L1.

person(given = "Efstathios D.", family = "Gennatas", role = c("aut", "cre"), email = "Efstathios.Gennatas@ucsf.edu")
An aid for learning and using music theory. You can build chords, scales, and chord progressions using 12-note equal temperament tuning (12-ET) or user-defined tuning. Includes functions to visualize notes on a piano using ASCII plots in the console and to plot waveforms using base graphics. It allows simple playback of notes and chords using the 'audio' package.