Description Usage Format Details Source References
Six different datasets containing the simulation results for each constraint.
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Each dataset is a list containing six elements:
$tabR
Dataframe of nsim*npt
rows and (3*n+4
) columns. Column $sim
is the number of current simulation.
Each row corresponds to the state at each observation step (i.e. after pasobs
mutations),
and columns are respectively concentrations (E1
to En
), kinetic parameters (kin1
to kin_n
), total concentration, total kinetic, flux, activities (A1
to An
), and simulation number (column $sim
)
$tabP_e
Numeric matrix of npt
rows and n+1
columns, corresponding to relative concentrations at equilibrium (column 1 to n
) at each observation step (in rows), and associated simulation number (column $sim
)
$tabP_r
Same as $tabP_e
, but for response coefficients
$list_init
List of 3 elements, containing initial values of concentrations in $E0
, kinetic parameters in $kin0
and activities in $A0
for each simulation. Each element is a numeric matrix of nsim
rows and n
columns
$list_final
List of 3 elements, containing final values of concentrations in $E_f
, kinetic parameters in $kin_f
and activities in $A_f
for each simulation. Each element is a numeric matrix of nsim
rows and n
columns
$param
List of input parameters:
n
: number of enzymes,
nsim
: number of simulation,
E0
: matrix of initial concentrations, identical to $list_init$E0
,
kin0
: matrix of initial kinetic parameters, identical to $list_init$kin0
,
Keq
: numeric vector of constant equilibrium,
beta
: matrix of co-regulation coefficients,
B
: numeric vector of global co-regulation coefficients,
correl
: character string indicating the constraint abbreviation,
N
: population size,
pasobs
: number of steps between two system observations,
npt
: number of system observations,
X
: parameter for flux computation,
Etot0
: initial total concentration,
pmutA
: probability for activity mutation,
other parameters are described in simul.evol.enz.multiple
Possible constraints are listed below:
"SC"
: independence between all enzymes
"Comp"
: competition for resources
"RegPos"
: positive regulation
"RegNeg"
: negative regulation
"CRPos"
: competition plus positive regulation
"CRNeg"
: competition plus negative regulation
There is ten simulations by constraint.
Simulations differ by the initial concentrations (manually chosen), but initial concentrations are identical between constraints.
Chosen equilibrium for tabP_e
and tabP_r
are the theoretical equilibrium for constraints "SC"
, "Comp"
and "RegPos"
, and the effective one for constraints "RegNeg"
, "CRPos"
and "CRNeg"
.
These simulation results are exploited in Coton et al. (2021).
New datasets when there are regulation groups
"data_sim_CRNeg_1grpNeg1sgl"
contains simulation results when there are one negative group and one singleton with competition.
"data_sim_RegNeg_1grpNeg1grpPos"
contains simulation results when there are one negative and one positive groups, without competition.
Function simul.evol.enz.multiple
have been used to obtained these datasets. Input parameters are listed in data_sim_xx$param
(where xx
is the constraint abbreviation). E0
have been randomly chosen. Seed have been set to 1 before the simulations for the first constraint.
Coton at al. (2021)
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