Title: Perform Analysis and Create Visualizations of Proteins
Description: Read Protein Data Bank (PDB) files, performs its analysis, and
presents the result using different visualization types including 3D. The
package also has additional capability for handling Virus Report data from
the National Center for Biotechnology Information (NCBI) database.
US National Library of Medicine (2021) <https://www.ncbi.nlm.nih.gov/datasets/docs/reference-docs/data-reports/virus/>.
Imports: pryr, lattice, methods, magick, dplyr, grid, gridExtra,

Title: Optimization of a multi-stage proteomic study
Description: This package provides functions to identify the optimal
solution that maximizes numbers of detectable differentiated
proteins from a multi-stage clinical proteomic study.

Title: Statistical Analysis of High Throughput Proteomics Data
Description: Provides methods for making inference in isobaric labelled
LC-MS/MS experiments, i.e. iTRAQ experiments. It provides a function that
reasonably parses a CSV-export from Proteome Discoverer(TM) into a data
frame that can be easily handled in R. Functions and methods are provided
for quality control, filtering, norming, and the calculation of response
variables for further analysis. The merging of multiple iTRAQ experiments
with respect to a reference is also covered.
Imports: plyr, reshape2, ggplot2, foreach
Packaged: 2014-11-21 13:33:54 UTC; thomas.moebius

Title: Multiform Seq2Seq Model for Time-Feature Analysis
Description: Seq2seq time-feature analysis based on variational model, with a wide range of distributions available for the latent variable.
Packaged: 2021-06-24 05:46:52 UTC; gvercellino

Title: Protein (identification and) quantification based on peptide
Author: Sarah Gerster and Peter Buehlmann
Description: Method for protein quantification based on identified and
quantified peptides. protiq can be used for absolute and
relative protein quantification. Input peptide abundance scores
can come from various sources, including SRM transition areas
and intentisites or spectral counts derived from shotgun
experiments. The package is still being extended to also
include the model for protein identification, MIPGEM, presented
in Gerster, S., Qeli, E., Ahrens, C.H. and Buehlmann, P.
(2010). Protein and gene model inference based on statistical
modeling in k-partite graphs. Proceedings of the National