loica
¶
Subpackages¶
Submodules¶
Package Contents¶
Classes¶
Assay measures a set of samples in parallel at a set of timepoints. |
|
Characterized context for gene expression, incorporates biomass and growth rate. |
|
A class that represents a gene product, protein or RNA. |
|
Representation of a genetic netowrk composed by a set of Operators, Regulators and Reporters. |
|
A class that represents a DNA fragment that encode a genetic operator. |
|
A class that represents a DNA fragment that encode a genetic operator. |
|
A class that represents a DNA fragment that encode a genetic operator. |
|
A class that represents a DNA fragment that encode a genetic operator. |
|
Context for gene expression, incorporates biomass and growth rate. |
|
A class that represents a DNA fragment that encode a genetic operator. |
|
A class that represents a DNA fragment that encode a genetic operator. |
|
A class that represents a DNA fragment that encode a genetic operator. |
|
A class that represents a DNA fragment that encode a genetic operator. |
|
Representation of a regulatory gene product. |
|
Representation of a regulatory gene product. |
|
Representation of a regulatory gene product. |
|
Representation of a regulatory gene product. |
|
Representation of a sample that encapsulates GeneticNetwork and Metabolism. |
|
Simulated context for gene expression, incorporates biomass and growth rate. |
|
A class that represents a DNA fragment that encode a genetic operator. |
|
A class that represents a DNA fragment that encode a genetic operator. |
|
Representation of a chemical |
|
Representation of a chemical |
Functions¶
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
- class Assay(samples, n_measurements, interval, name='Loica assay', description='', biomass_signal_id=None)¶
Assay measures a set of samples in parallel at a set of timepoints. Connects to flapjack to generate data, and to fit parameters to data.
…
- samplesList[Sample]
List of Samples that belongs to the Assay
- n_measurementsint
Number of measurements to take
- intervalint
Time in hours between each measurements
- namestr
Name of the Assay
- description: str
Descriptioin of the Assay
- biomass_signal_idint
Flapjack ID of the Assay that is associated with the Assay
- run(substeps=10, nsr=0, biomass_bg=0, fluo_bg=0)
Runs the Assay time series
- upload(flapjack, study)
Upload the data produced by running the Assay to Flapjack into the Study
Assay measures a set of samples in parallel at a set of timepoints Connects to flapjack to generate data, and to fit parameters to data
- run(self, substeps=10, nsr=0, biomass_bg=0, fluo_bg=0, stochastic=False)¶
Run the assay measuring at specified time points, with simulation time step dt
- upload(self, flapjack, study)¶
- class Colony(circuit=None, r0=1, mu0=1)¶
- fun(self, x)¶
- kymograph(self, nx, t0, tmax)¶
- map_kymo(self, kymo)¶
- norm_kymo(self, kymo)¶
- class DataMetabolism(name, fj, media, strain, vector, biomass_signal)¶
Bases:
Metabolism
Characterized context for gene expression, incorporates biomass and growth rate. …
- namestr, optional
Name of the metabolism or correponding strain
- fjFlapjack
Flapjack instance used to fetch data from
- mediastr
Name of the media to query
- strainstr
Name of the strain to query
- vectorstr
Name of the vector to query
- biomass_signalstr
Name of signal to query and use as biomass
- biomass(t)
Return biomass at a given time from characterization data
- growth:rate(t)
Return growth rate at a given time from characterization data
- biomass(self, t)¶
- growth_rate(self, t)¶
- class GeneProduct(name, init_concentration=0, degradation_rate=0, uri=None, sbol_comp=None, type_='PRO', color='silver')¶
A class that represents a gene product, protein or RNA.
…
- namestr
Name of the gene product
- init_concentrationint | float
Initial concentration of the gene product in Molar
- degradation_rateint | float
Degradation rate of the gene product
- type_str, optional
Molecular type of the gene product, could be ‘PRO’ or ‘RNA’
- uristr, optional
SynBioHub URI
- sbol_compSBOL Component, optional
SBOL Component
- shape = ^¶
- __str__(self)¶
Return str(self).
- express(self, rate)¶
- initialize(self)¶
- step(self, growth_rate, dt)¶
- class GeneticNetwork(vector=None)¶
Representation of a genetic netowrk composed by a set of Operators, Regulators and Reporters.
…
- operatorsList[Operator]
List of Operators that are part of the genetic network
- regulatorsList[Regulator]
List of Regulators that are part of the genetic network
- reportersList[Reporter]
List of Reporters that are part of the genetic network
- vectorint
Flapjack ID of the vector that is associated with the genetic network
- to_graph()
Builds a graph representation of the genetic netwok
- draw()
Generates a plot of the graph representation builded by to_graph()
- to_sbol(sbol_doc=None)
Generates a SBOL3 Document representation of the genetic network on sbol_doc
- add_operator(self, ops)¶
- add_regulator(self, regs)¶
- add_reporter(self, reps)¶
- draw(self, node_shape='o', node_size=500, linewidths=0, alpha=0.5, arrowsize=10, font_size=6, font_family='Tahoma', font_weight='bold', pos=nx.kamada_kawai_layout, contracted=False)¶
- initialize(self)¶
- step(self, growth_rate=1, t=0, dt=0.1)¶
- step_stochastic(self, growth_rate=1, t=0, dt=0.1)¶
- substep_stochastic(self, t=0, dt=0.1, growth_rate=1)¶
- to_contracted_graph(self)¶
- to_graph(self)¶
- to_sbol(self, sbol_doc: sbol3.Document = None) sbol3.Document ¶
Convert the genetic network to SBOL. :param sbol_doc: The SBOL document to add the genetic network to.
- class Hill1(input, output, alpha, K, n, name=None, uri=None, sbol_comp=None, color='skyblue')¶
Bases:
loica.operators.operator.Operator
A class that represents a DNA fragment that encode a genetic operator. The Hill1 Operator is an abstraction of a repressible or inducible promoter that maps an input into an output using a Hill function.
…
- inputRegulator | Supplement
The input of the operator that regulates the expression of the output
- outputRegulator | Reporter
The output of the operator that is regulated by the input
- alphaList
[Basal expression rate, Regulated expression rate in MEFL/second]
- Kint | float
Half expression input concentration in Molar
- nint | float
Hill coefficient, cooperative degree (unitless)
- uristr, optional
SynBioHub URI
- sbol_compSBOL Component, optional
SBOL Component
- namestr, optional
Name of the operator displayed on the network representation
- color: str, optional
Color displayed on the network representation
- characterize(flapjack, receiver, inverter, media, strain, signal, biomass_signal, gamma)
Parameterize the Operator model that maps Input concentration into Output expression rate
- __str__(self)¶
Return str(self).
- characterize(self, flapjack, receiver, inverter, media, strain, signal, biomass_signal, gamma)¶
- expression_rate(self, t, dt)¶
- forward_model(self, a_j, b_j, n_i=2, K_i=1, a_A=100.0, b_A=0, K_A=1, n_A=2, Dt=0.05, sim_steps=10, A=0, odval=[1] * 100, gamma=0, p0_1=0, p0_2=0, nt=100)¶
- residuals(self, df, oddf, a_A, b_A, K_A, n_A, gamma)¶
- class Hill1(input, output, alpha, K, n, name=None, uri=None, sbol_comp=None, color='skyblue')¶
Bases:
loica.operators.operator.Operator
A class that represents a DNA fragment that encode a genetic operator. The Hill1 Operator is an abstraction of a repressible or inducible promoter that maps an input into an output using a Hill function.
…
- inputRegulator | Supplement
The input of the operator that regulates the expression of the output
- outputRegulator | Reporter
The output of the operator that is regulated by the input
- alphaList
[Basal expression rate, Regulated expression rate in MEFL/second]
- Kint | float
Half expression input concentration in Molar
- nint | float
Hill coefficient, cooperative degree (unitless)
- uristr, optional
SynBioHub URI
- sbol_compSBOL Component, optional
SBOL Component
- namestr, optional
Name of the operator displayed on the network representation
- color: str, optional
Color displayed on the network representation
- characterize(flapjack, receiver, inverter, media, strain, signal, biomass_signal, gamma)
Parameterize the Operator model that maps Input concentration into Output expression rate
- __str__(self)¶
Return str(self).
- characterize(self, flapjack, receiver, inverter, media, strain, signal, biomass_signal, gamma)¶
- expression_rate(self, t, dt)¶
- forward_model(self, a_j, b_j, n_i=2, K_i=1, a_A=100.0, b_A=0, K_A=1, n_A=2, Dt=0.05, sim_steps=10, A=0, odval=[1] * 100, gamma=0, p0_1=0, p0_2=0, nt=100)¶
- residuals(self, df, oddf, a_A, b_A, K_A, n_A, gamma)¶
- class Hill2(input, output, alpha, K, n, name=None, uri=None, sbol_comp=None, color='orange')¶
Bases:
loica.operators.receiver.Operator
A class that represents a DNA fragment that encode a genetic operator. The Hill2 Operator is an abstraction of a set of two repressible or inducible promoters that maps an 2 inputs into an output using a Hill function.
…
- inputList [Regulator | Supplement]
The inputs of the operator that regulates the expression of the output
- outputRegulator | Reporter | List
The output of the operator that is regulated by the input
- alphaList
[Basal expression rate, Regulated expression rate in MEFL/second]
- Kint | float
Half expression input concentration in Molar
- nint | float
Hill coefficient, cooperative degree (unitless)
- uristr, optional
SynBioHub URI
- sbol_compSBOL Component, optional
SBOL Component
- namestr, optional
Name of the operator displayed on the network representation
- color: str, optional
Color displayed on the network representation
- characterize(flapjack, receiver, inverter, media, strain, signal, biomass_signal, gamma)
Parameterize the Operator model that maps Input concentration into Output expression rate
- __str__(self)¶
Return str(self).
- characterize(self, flapjack, receiver1, receiver2, chemical1, chemical2, nor_inverter, media, strain, signal, biomass_signal, gamma, lower_bounds=[0] * 8, upper_bounds=[100000000.0, 8, 100000000.0, 8, 100000000.0, 100000000.0, 100000000.0, 100000000.0], init_x=[1, 2, 1, 2, 1, 0, 0, 0])¶
- expression_rate(self, t, dt)¶
- forward_model(self, rep1_K=1, rep1_n=2, rep2_K=1, rep2_n=2, alpha0=1, alpha1=0, alpha2=0, alpha3=0, a_A=100.0, b_A=0, K_A=1, n_A=2, a_B=100.0, b_B=0, K_B=1, n_B=2, Dt=0.05, sim_steps=10, A=0, B=0, odval=[1] * 100, gamma=0, rep1_0=0, rep2_0=0, fp_0=0, nt=100)¶
- residuals(self, df, oddf, a_A, b_A, K_A, n_A, a_B, b_B, K_B, n_B, chem1, chem2, gamma)¶
- class Hill2(input, output, alpha, K, n, name=None, uri=None, sbol_comp=None, color='orange')¶
Bases:
loica.operators.receiver.Operator
A class that represents a DNA fragment that encode a genetic operator. The Hill2 Operator is an abstraction of a set of two repressible or inducible promoters that maps an 2 inputs into an output using a Hill function.
…
- inputList [Regulator | Supplement]
The inputs of the operator that regulates the expression of the output
- outputRegulator | Reporter | List
The output of the operator that is regulated by the input
- alphaList
[Basal expression rate, Regulated expression rate in MEFL/second]
- Kint | float
Half expression input concentration in Molar
- nint | float
Hill coefficient, cooperative degree (unitless)
- uristr, optional
SynBioHub URI
- sbol_compSBOL Component, optional
SBOL Component
- namestr, optional
Name of the operator displayed on the network representation
- color: str, optional
Color displayed on the network representation
- characterize(flapjack, receiver, inverter, media, strain, signal, biomass_signal, gamma)
Parameterize the Operator model that maps Input concentration into Output expression rate
- __str__(self)¶
Return str(self).
- characterize(self, flapjack, receiver1, receiver2, chemical1, chemical2, nor_inverter, media, strain, signal, biomass_signal, gamma, lower_bounds=[0] * 8, upper_bounds=[100000000.0, 8, 100000000.0, 8, 100000000.0, 100000000.0, 100000000.0, 100000000.0], init_x=[1, 2, 1, 2, 1, 0, 0, 0])¶
- expression_rate(self, t, dt)¶
- forward_model(self, rep1_K=1, rep1_n=2, rep2_K=1, rep2_n=2, alpha0=1, alpha1=0, alpha2=0, alpha3=0, a_A=100.0, b_A=0, K_A=1, n_A=2, a_B=100.0, b_B=0, K_B=1, n_B=2, Dt=0.05, sim_steps=10, A=0, B=0, odval=[1] * 100, gamma=0, rep1_0=0, rep2_0=0, fp_0=0, nt=100)¶
- residuals(self, df, oddf, a_A, b_A, K_A, n_A, a_B, b_B, K_B, n_B, chem1, chem2, gamma)¶
- class Metabolism(name=None)¶
Context for gene expression, incorporates biomass and growth rate. …
- namestr, optional
Name of the metabolism or correponding strain
- class Operator(output, name=None, uri=None, sbol_comp=None, color='skyblue')¶
A class that represents a DNA fragment that encode a genetic operator.
…
- outputRegulator | Reporter
The output of the operator that is regulated by the input
- uristr, optional
SynBioHub URI
- sbol_compSBOL Component, optional
SBOL Component
- namestr, optional
Name of the operator displayed on the network representation
- color: str, optional
Color displayed on the network representation
- __str__(self)¶
Return str(self).
- class Operator(output, name=None, uri=None, sbol_comp=None, color='skyblue')¶
A class that represents a DNA fragment that encode a genetic operator.
…
- outputRegulator | Reporter
The output of the operator that is regulated by the input
- uristr, optional
SynBioHub URI
- sbol_compSBOL Component, optional
SBOL Component
- namestr, optional
Name of the operator displayed on the network representation
- color: str, optional
Color displayed on the network representation
- __str__(self)¶
Return str(self).
- class Receiver(input, output, alpha, K, n, name=None, uri=None, sbol_comp=None, color='skyblue')¶
Bases:
loica.operators.operator.Operator
A class that represents a DNA fragment that encode a genetic operator. The Receiver Operator is an abstraction of an inducible promoter that maps an external input into an output using a Hill function.
…
- inputRegulator | Supplement
The input of the operator that regulates the expression of the output
- outputRegulator | Reporter
The output of the operator that is regulated by the input
- alphaList
[Basal expression rate, Regulated expression rate in MEFL/second]
- Kint | float
Half expression input concentration in Molar
- nint | float
Hill coefficient, cooperative degree (unitless)
- uristr, optional
SynBioHub URI
- sbol_compSBOL Component, optional
SBOL Component
- namestr, optional
Name of the operator displayed on the network representation
- color: str, optional
Color displayed on the network representation
- unit: str, optional
Units of the characterization data
- characterize(flapjack, receiver, inverter, media, strain, signal, biomass_signal, gamma)
Parameterize the Operator model that maps Input concentration into Output expression rate
- __str__(self)¶
Return str(self).
- characterize(self, flapjack, vector, media, strain, signal, biomass_signal)¶
- expression_rate(self, t, dt)¶
- forward_model(self, a=0, b=1, K_A=1, n_A=2, Dt=0.05, sim_steps=10, A=[0], odval=[1] * 100, gamma=0, p0=0, nt=100)¶
- residuals(self, df, oddf)¶
- class Receiver(input, output, alpha, K, n, name=None, uri=None, sbol_comp=None, color='skyblue')¶
Bases:
loica.operators.operator.Operator
A class that represents a DNA fragment that encode a genetic operator. The Receiver Operator is an abstraction of an inducible promoter that maps an external input into an output using a Hill function.
…
- inputRegulator | Supplement
The input of the operator that regulates the expression of the output
- outputRegulator | Reporter
The output of the operator that is regulated by the input
- alphaList
[Basal expression rate, Regulated expression rate in MEFL/second]
- Kint | float
Half expression input concentration in Molar
- nint | float
Hill coefficient, cooperative degree (unitless)
- uristr, optional
SynBioHub URI
- sbol_compSBOL Component, optional
SBOL Component
- namestr, optional
Name of the operator displayed on the network representation
- color: str, optional
Color displayed on the network representation
- unit: str, optional
Units of the characterization data
- characterize(flapjack, receiver, inverter, media, strain, signal, biomass_signal, gamma)
Parameterize the Operator model that maps Input concentration into Output expression rate
- __str__(self)¶
Return str(self).
- characterize(self, flapjack, vector, media, strain, signal, biomass_signal)¶
- expression_rate(self, t, dt)¶
- forward_model(self, a=0, b=1, K_A=1, n_A=2, Dt=0.05, sim_steps=10, A=[0], odval=[1] * 100, gamma=0, p0=0, nt=100)¶
- residuals(self, df, oddf)¶
- class Regulator(name, init_concentration=0, degradation_rate=0, sbol_comp=None, color='lightgreen')¶
Bases:
GeneProduct
Representation of a regulatory gene product. Child of GeneProduct.
- class Regulator(name, init_concentration=0, degradation_rate=0, sbol_comp=None, color='lightgreen')¶
Bases:
GeneProduct
Representation of a regulatory gene product. Child of GeneProduct.
- class Reporter(name, init_concentration=0, degradation_rate=0, signal_id=None, color='w', sbol_comp=None)¶
Bases:
GeneProduct
Representation of a regulatory gene product.
- signal_idstr, optional
Flapjack ID of the signal that the reporter is associated with.
- colorstr, optional
Color of the reporter
- class Reporter(name, init_concentration=0, degradation_rate=0, signal_id=None, color='w', sbol_comp=None)¶
Bases:
GeneProduct
Representation of a regulatory gene product.
- signal_idstr, optional
Flapjack ID of the signal that the reporter is associated with.
- colorstr, optional
Color of the reporter
- class Sample(genetic_network=None, metabolism=None, assay=None, media=None, strain=None)¶
Representation of a sample that encapsulates GeneticNetwork and Metabolism. Incorporate environment information such as Supplements or chemicals, strain and media. Ex: 1 well in a plate, single cell. …
- genetic_networkGeneticNetwork
genetic network that is part of the sample
- metabolismMetabolism
metabolism that drives the genetic network in the sample
- assayAssay
assay to which this sample belongs
- mediastr
Name of the media in the sample
- strainstr
Name of the strain in the sample
Methods
- add_supplement(supplement, concentration)
stablishes the concentration of Supplement
- initialize(self)¶
- set_regulator(self, name, concentration)¶
- set_reporter(self, name, concentration)¶
- set_supplement(self, supplement, concentration, profile=None)¶
- step(self, t, dt, stochastic=False)¶
- class SimulatedMetabolism(name, biomass, growth_rate)¶
Bases:
Metabolism
Simulated context for gene expression, incorporates biomass and growth rate. …
- namestr, optional
Name of the metabolism or correponding strain
- biomass
A function of time that describes biomass f(t)=biomass
- growth_rate
A function of time that describes the growth rate f(t)=growth rate
- class Source(output, rate, uri=None, sbol_comp=None, color='blue', name=None)¶
Bases:
Operator
A class that represents a DNA fragment that encode a genetic operator. The Source Operator is an abstraction of a constitutive promoter that produces output.
…
- outputRegulator | Reporter
The output of the operator that is constitutively expressed
- ratefloat
Output constitutive expression rate in MEFL/second
- uristr, optional
SynBioHub URI
- sbol_compSBOL Component, optional
SBOL Component
- namestr, optional
Name of the operator displayed on the network representation
- color: str, optional
Color displayed on the network representation
- characterize(flapjack, receiver, inverter, media, strain, signal, biomass_signal, gamma)
Parameterize the Operator model that maps Input concentration into Output expression rate
- __str__(self)¶
- characterize(self, flapjack, vector, media, strain, signal, biomass_signal)¶
- expression_rate(self, t, dt)¶
- forward_model(self, Dt=0.25, sim_steps=10, odval=[1] * 97, rate=1, gamma=0, p0=0, nt=100)¶
- residuals(self, df, oddf)¶
- class Source(output, rate, uri=None, sbol_comp=None, color='blue', name=None)¶
Bases:
Operator
A class that represents a DNA fragment that encode a genetic operator. The Source Operator is an abstraction of a constitutive promoter that produces output.
…
- outputRegulator | Reporter
The output of the operator that is constitutively expressed
- ratefloat
Output constitutive expression rate in MEFL/second
- uristr, optional
SynBioHub URI
- sbol_compSBOL Component, optional
SBOL Component
- namestr, optional
Name of the operator displayed on the network representation
- color: str, optional
Color displayed on the network representation
- characterize(flapjack, receiver, inverter, media, strain, signal, biomass_signal, gamma)
Parameterize the Operator model that maps Input concentration into Output expression rate
- __str__(self)¶
- characterize(self, flapjack, vector, media, strain, signal, biomass_signal)¶
- expression_rate(self, t, dt)¶
- forward_model(self, Dt=0.25, sim_steps=10, odval=[1] * 97, rate=1, gamma=0, p0=0, nt=100)¶
- residuals(self, df, oddf)¶
- class Sum(input, output, alpha, K, n, uri=None, sbol_comp=None)¶
Bases:
Operator
- color = skyblue¶
- shape = s¶
- __str__(self)¶
- expression_rate(self, t, dt)¶
- class Supplement(name, pubchemid=None, supplier_id=None, sbol_comp=None, color='pink')¶
Representation of a chemical
…
- namestr
Name of the supplement
- concentrationint | float
concentration of the supplement in Molar
- pubchemidstr
PubChemID URI of the supplement
- supplier_idstr
Supplier ID of the supplement. An URL of the product that you aquire. Accepts list of the form [product URL, catalog number, batch].
- sbol_compstr
SBOL component of the supplement.
- __str__(self)¶
Return str(self).
- class Supplement(name, pubchemid=None, supplier_id=None, sbol_comp=None, color='pink')¶
Representation of a chemical
…
- namestr
Name of the supplement
- concentrationint | float
concentration of the supplement in Molar
- pubchemidstr
PubChemID URI of the supplement
- supplier_idstr
Supplier ID of the supplement. An URL of the product that you aquire. Accepts list of the form [product URL, catalog number, batch].
- sbol_compstr
SBOL component of the supplement.
- __str__(self)¶
Return str(self).
- characterize_growth(flapjack, vector, media, strain, biomass_signal, n_gaussians, epsilon)¶
- forward_model_growth(Dt=0.05, sim_steps=10, muval=[0] * 100, od0=0, nt=100)¶
- gompertz(t, y0, ymax, um, l)¶
- gompertz_growth_rate(t, y0, ymax, um, l)¶
- load_loica(filename)¶
- ramp_biomass(t, od0, start, slope)¶
- ramp_growth_rate(t, start, slope)¶
- residuals_growth(data, epsilon, dt, t, n_gaussians)¶
- save_loica(obj, filename)¶
- step_biomass(t, od0, start)¶
- step_growth_rate(t, start)¶