Title: Interface to the LSF Queuing System
Author: Chris Smith <csmith@platform.com> and
Description: This package provides functions for using R with the
SystemRequirements: Platform LSF development libraries
Packaged: Mon Oct  3 11:06:29 2005; warneg

Packaged: Tue Aug  8 19:53:41 2006; warnes

Packaged: Fri Sep 29 10:43:04 2006; csmith

Packaged: Wed Apr 11 12:35:53 2007; kuhna03

Packaged: Fri Apr 13 19:12:35 2007; kuhna03

Description: An R <-> mSQL database interface
License: GPL (interface-code) and mSQL-Licence

Packaged: Wed Aug 11 11:03:23 2004; leisch

Depends: mSQL-2.0.8 (http://www.Hughes.com.au) or higher

Title: MAGIC - Markov Affinity-Based Graph Imputation of Cells
Authors@R: c(person(given = "David", family = "van Dijk", email = "davidvandijk@gmail.com", role = c("aut")),
person(given = 'Scott', family = 'Gigante', email = 'scott.gigante@yale.edu', role = 'cre', comment = c(ORCID = '0000-0002-4544-2764')))
Description: MAGIC (Markov affinity-based graph imputation of cells) is a method for addressing technical noise in single-cell data, including under-sampling of mRNA molecules, often termed "dropout" which can severely obscure important gene-gene relationships. MAGIC shares information across similar cells, via data diffusion, to denoise the cell count matrix and fill in missing transcripts. Read more: van Dijk et al. (2018) <DOI:10.1016/j.cell.2018.05.061>.
Imports: methods, stats, reticulate (>= 1.4), ggplot2

person(given = 'Scott', family = 'Gigante', email = 'scott.gigante@yale.edu', role = 'cre',

Suggests: Seurat (>= 3.0.0), readr, viridis, phateR
Packaged: 2019-11-12 15:58:30 UTC; scottgigante

Packaged: 2019-11-20 23:59:32 UTC; scottgigante

Title: Continuous Optimization using Memetic Algorithms with Local
Author: Christoph Bergmeir, Daniel Molina, José M. Benítez
Description: This package implements an algorithm family for continuous
optimization called memetic algorithms with local search chains
(MA-LS-Chains). Memetic algorithms are hybridizations of
genetic algorithms with local search methods. They are
especially suited for continuous optimization.