From 2e2202857f363ade6f11f4582a4052fc22933fd4 Mon Sep 17 00:00:00 2001
From: Claus Jonathan Fritzemeier <clausjonathan.fritzemeier@hhu.de>
Date: Wed, 17 Jun 2015 16:05:37 +0200
Subject: [PATCH] changes mentioned by kurt hornik
---
DESCRIPTION | 13 +++++++------
man/addReact.Rd | 4 +++-
man/readProb-methods.Rd | 12 +++++++++---
man/writeProb-methods.Rd | 11 ++++++++---
4 files changed, 27 insertions(+), 13 deletions(-)
diff --git a/DESCRIPTION b/DESCRIPTION
index 6ac300e..26272a2 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,10 +1,11 @@
Package: sybil
Type: Package
-Title: sybil - Efficient Constrained Based Modelling in R
+Title: Efficient Constrained Based Modelling in R
Version: 1.3.0
-Date: 2015-03-30
-Authors@R: c(person("Gabriel", "Gelius-Dietrich", role = c("aut")),
- person(c("C.", "Jonathan"), "Fritzemeier", role = c("ctb", "cre"), email = "clausjonathan.fritzemeier@uni-duesseldorf.de"),
+Date: 2015-06-17
+Authors@R: c(
+ person(c("C.", "Jonathan"), "Fritzemeier", role = c("cre", "ctb"), email = "clausjonathan.fritzemeier@uni-duesseldorf.de"),
+ person("Gabriel", "Gelius-Dietrich", role = c("aut")),
person("Rajen", "Piernikarczyk", role = "ctb"),
person(c("Marc", "Andre"), "Daxer", role = "ctb"),
person("Benjamin", "Braasch", role = "ctb"),
@@ -17,9 +18,9 @@ Suggests: glpkAPI (>= 1.2.8), cplexAPI (>= 1.2.4), clpAPI (>= 1.2.4),
lpSolveAPI (>= 5.5.2.0), parallel, grid
URL:
http://www.cs.hhu.de/en/research-groups/bioinformatics/software/sybil.html
-Description: The package sybil is a Systems Biology Library for R, implementing algorithms for constraint based analyses of metabolic networks (e.g. flux-balance analysis (FBA), minimization of metabolic adjustment (MOMA), regulatory on/off minimization (ROOM), robustness analysis and flux variability analysis).
+Description: This Systems Biology Library for R implements algorithms for constraint based analyses of metabolic networks (e.g. flux-balance analysis (FBA), minimization of metabolic adjustment (MOMA), regulatory on/off minimization (ROOM), robustness analysis and flux variability analysis). Most of the current LP/MILP solvers are supported via additional packages.
LazyLoad: yes
-License: GPL-3
+License: GPL-3 | file LICENSE
Collate: generics.R validmodelorg.R validoptsol.R validreactId.R
validreactId_Exch.R validsysBiolAlg.R addAlgorithm.R
addExchReact.R addReact.R addSolver.R blockedReact.R
diff --git a/man/addReact.Rd b/man/addReact.Rd
index 5e10126..2470300 100644
--- a/man/addReact.Rd
+++ b/man/addReact.Rd
@@ -118,7 +118,9 @@
data(Ec_core)
# add reaction A + 2 B <-> C to the model
-modelNew <- addReact(Ec_core, id="newReact", met=c("A", "B", "C"), Scoef=c(-1, -2, 1), reversible=TRUE, lb=-1000, ub=1000, obj=0)
+modelNew <- addReact(Ec_core, id="newReact", met=c("A", "B", "C"),
+ Scoef=c(-1, -2, 1), reversible=TRUE,
+ lb=-1000, ub=1000, obj=0)
# view the new reaction
shrinkMatrix(modelNew, j="newReact")
diff --git a/man/readProb-methods.Rd b/man/readProb-methods.Rd
index d175196..b33a0af 100644
--- a/man/readProb-methods.Rd
+++ b/man/readProb-methods.Rd
@@ -88,9 +88,15 @@
library(sybil)
data(Ec_core)
- prob <- sysBiolAlg(Ec_core, algorithm = "fba", solver="glpkAPI") # create a sysBiolAlg object (we use here GLPK (!))
- save(file="prob.RData",prob) # write the R-object to disc
- writeProb(prob@problem, fname="prob.lp", ff="lp") # now write the linear program part (managed by the solver) to disc
+
+ # create a sysBiolAlg object (we use here GLPK (!))
+ prob <- sysBiolAlg(Ec_core, algorithm = "fba", solver="glpkAPI")
+
+ # write the R-object to disc
+ save(file="prob.RData",prob)
+
+ # now write the linear program part (managed by the solver) to disc
+ writeProb(prob@problem, fname="prob.lp", ff="lp")
# start new R session
diff --git a/man/writeProb-methods.Rd b/man/writeProb-methods.Rd
index bcb82d3..214ebf9 100644
--- a/man/writeProb-methods.Rd
+++ b/man/writeProb-methods.Rd
@@ -87,9 +87,14 @@
library(sybil)
data(Ec_core)
- prob <- sysBiolAlg(Ec_core, algorithm = "fba", solver="glpkAPI") # create a sysBiolAlg object (we use here GLPK (!))
- save(file="prob.RData",prob) # write the R-object to disc
- writeProb(prob@problem, fname="prob.lp", ff="lp") # now write the linear program part (managed by the solver) to disc
+ # create a sysBiolAlg object (we use here GLPK (!))
+ prob <- sysBiolAlg(Ec_core, algorithm = "fba", solver="glpkAPI")
+
+ # write the R-object to disc
+ save(file="prob.RData",prob)
+
+ # now write the linear program part (managed by the solver) to disc
+ writeProb(prob@problem, fname="prob.lp", ff="lp")
# start new R session
--
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