Analysing and forecasting biological invasions time series with a stochastic approach that accounts for human-aided dispersal, habitat suitability and provides estimates confidence level.

Paired (pBI) and Unpaired Biomarker Identifier (uBI) including a
method to infer networks.
This package allows to rank features and infer networks
based on the Paired (pBI) and Unpaired Biomarker Identifier
(uBI).

This package allows to rank features and infer networks based on the Paired (pBI) and Unpaired Biomarker Identifier (uBI).

Identification of Impulse-Like Gene Expression Changes in Short
Genomic Series Data
Enables the user to systematically identify and visualize impulse-like gene expression changes within short genomic series experiments. In order to detect such activation peaks, the gene expression is treated as a signal that propagates along an experimental axis (time, temperature or other series conditions). Peaks are selected by exhaustive identification of local maximums and subsequent filtering based on a range of controllable parameters. Moreover, the 'Biopeak' package provides a series of data exploration tools including: expression profile plots, correlation heat maps and clustering functionalities.
cluster, dbscan, factoextra, gplots, RColorBrewer, stats,
graphics

From Biological Sequences and Simulations to Correlation
Analysis
Bruck Taddese [aut], Antoine Garnier [aut], Madeline Deniaud [aut], Julien Pele [ctb], Lea Bellenger [ctb], Jean-Michel Becu [ctb], Marie Chabbert [cre]
R (>= 3.1), bio3d, circular, bigmemory, parallel
The package is dedicated to computation and analysis of correlation/co-variation in multiple sequence alignments and in side chain motions during molecular dynamics simulations. Features include the ability to compute correlation/co-variation using a variety of scoring functions between either sequence positions in alignments or side chain dihedral angles in molecular dynamics simulations and to analyze the correlation/co-variation matrix through a variety of tools including network representation and principal components analysis.  In addition, several utility functions are based on the R graphical environment to provide friendly tools for help in data interpretation. Examples of sequence co-variation analysis and utility tools are provided in: Pele J, Moreau M, Abdi H, Rodien P, Castel H, Chabbert M. (2014) <doi:10.1002/prot.24570>. This work was supported by the Franch National Research Agency (Grant number: ANR-11-BSV2-026).