Is designed to make easier printing summary statistics (for continues and factor level) tables in Latex, and plotting by factor.

Designed for prediction error estimation
        through resampling techniques, possibly accelerated by parallel
        execution on a compute cluster. Newly developed model fitting
        routines can be easily incorporated. Methods used in the package are detailed in
        Porzelius Ch., Binder H. and Schumacher M. (2009) <doi:10.1093/bioinformatics/btp062>
        and were used, for instance, in
        Porzelius Ch., Schumacher M. and Binder H. (2011) <doi:10.1007/s00180-011-0236-6>.

A versatile R visualization package that empowers 
    researchers with comprehensive visualization tools for seamlessly mapping peptides 
    to protein sequences, identifying distinct domains and regions of interest, 
    accentuating mutations, and highlighting post-translational modifications, 
    all while enabling comparisons across diverse experimental conditions. 
    Potential applications of 'PepMapViz' include the visualization of cross-software 
    mass spectrometry results at the peptide level for specific protein and domain 
    details in a linearized format and post-translational modification coverage 
    across different experimental conditions; unraveling insights into disease 
    mechanisms. It also enables visualization of Major histocompatibility 
    complex-presented peptide clusters in different antibody regions predicting 
    immunogenicity in antibody drug development.

Fits the Piecewise Exponential distribution with random time grids using the clustering structure of the Product Partition Models. Details of the implemented model can be found in Demarqui et al. (2008) <doi:10.1007/s10985-008-9086-0>.

An implementation of the data processing and data analysis portion
    of a pipeline named the PepSAVI-MS which is currently under development by
    the Hicks laboratory at the University of North Carolina.  The statistical
    analysis package presented herein provides a collection of software tools
    used to facilitate the prioritization of putative bioactive peptides from a
    complex biological matrix.  Tools are provided to deconvolute mass
    spectrometry features into a single representation for each peptide charge
    state, filter compounds to include only those possibly contributing to the
    observed bioactivity, and prioritize these remaining compounds for those
    most likely contributing to each bioactivity data set.