Title: Package to identify and sort genes overexpressed
Description: Identify and sort genes overexpressed and associated to transmembrane protein in Affymetrix expression set.
Packaged: 2014-03-18 17:40:56 UTC; Noemie.Robil

Description: Identify and sort genes overexpressed and associated to transmembrane protein in Affymetrix expression set or any other results of microarray experiment.
Packaged: 2014-07-30 10:48:54 UTC; Noemie.Robil

Title: Kinetic analysis and visualization of DCE-MRI data.
Description: Package for kinetic analysis of longitudinal voxel-wise Dynamic Contrast Enhanced MRI data. Includes tools for visualization and exploration of voxel-wise parametric maps.

Title: Kinetic Analysis and Visualization of DCE-MRI Data
Authors@R: c(person("Gregory Z.", "Ferl", role = c("aut", "cre"),
email = "ferl.gregory@gene.com"), person("Georges", "Hankov", role = "aut",
Description: Provides kinetic analysis of Dynamic Contrast Enhanced Magnetic Resonance Imaging (DCE-MRI) data. Includes tools for fitting the Tofts (described in Tofts, Kermode (1991) <DOI:10.1002/mrm.1910170208>) and extended Tofts (described in Tofts et al. (1999) <https://www.ncbi.nlm.nih.gov/pubmed/10508281>) mathematical models to dynamic (signal vs. time) data associated with each voxel of an image and a Graphical User Inferface (GUI) for visualization and exploration of fitted model parameters over the volume of the image.

Maintainer: Karne Chaithanya Sai <karnechaithanyasai@gmail.com>
Description: It predicts any attribute (categorical) given a set of input numeric predictor values. Note that only numeric input predictors should be given.
The k value can be chosen according to accuracies provided. The attribute to be predicted can be selected from the dropdown provided (select categorical attribute).
This is because categorical attributes cannot be given as inputs here. A 'handsontable' is also provided to enter the input predictor values.
Imports: shiny, rhandsontable, dplyr, caret, FNN

Description: Predicts any variable in any categorical dataset for given values of predictor variables.
If a dataset contains 4 variables, then any variable can be predicted based on the values of the other three variables given by the user.
The user can upload their own datasets and select what variable they want to predict.
A 'handsontable' is provided to enter the predictor values and also accuracy of the prediction is also shown.
Imports: shiny, rhandsontable, dplyr, caret, e1071,