biocrnpyler.core.HillNegative

class biocrnpyler.core.HillNegative(k: float, s1: Species, K: float, n: float)

Bases: Hill

Negative Hill function propensity (repression).

Implements a repressive Hill function. As s1 increases, the rate decreases from k toward zero.

Parameters:

• k (float or ParameterEntry) – Maximum rate constant (when s1=0). Must be positive.

• s1 (Species) – Input species that represses the reaction.

• K (float or ParameterEntry) – Half-saturation constant (concentration at half-maximal repression). Must be positive.

• n (float or ParameterEntry) – Hill coefficient (cooperativity). Must be positive. Values > 1 indicate ultrasensitive repression.

Attributes:

name (str) – Set to ‘hillnegative’ for this propensity type.

See also

HillPositive

Activating Hill function.

ProportionalHillNegative

Proportional negative Hill.

Notes

The following mathematical formula is implemented:

\[p(s_1; k, K, n) = \frac{k}{1 + (s_1/K)^n} \]

leading to the following behavior:

• When s1 = 0: rate = \(k\)

• When s1 = \(K\): rate = \(k\)/2

• When s1 \(\gg\) \(K\): rate \(\rightarrow\) 0

• Larger \(n\) gives sharper (more switch-like) repression

Examples

Create a Hill repression propensity:

>>> R = bcp.Species('R')  # Repressor
>>> prop = bcp.HillNegative(k=10.0, s1=R, K=50.0, n=2.0)

Model transcriptional repression:

>>> repressor = bcp.Species('repressor')
>>> kmax = bcp.ParameterEntry('kmax', 1.0)
>>> Ki = bcp.ParameterEntry('Ki', 100.0)
>>> prop = bcp.HillNegative(k=kmax, s1=repressor, K=Ki, n=2.0)

Methods

create_kinetic_law	Create SBML kinetic law for Hill propensity.
from_dict	Create a propensity from a dictionary.
get_available_propensities	Get all available propensity subclasses.
is_valid_propensity	Check if an object is a valid Propensity subclass instance.
pretty_print	Generate human-readable string representation of propensity.
pretty_print_parameters	Generate formatted string of all propensity parameters.
pretty_print_rate	Generate human-readable rate formula string.

property K

Half-saturation (dissociation) constant value.

Type:

float

__eq__(other)

Test equality between propensities.

Parameters:

other (Propensity) – Other propensity to compare with.

Returns:

True if propensities have the same class and propensity_dict.

Return type:

bool

create_kinetic_law(model, sbml_reaction, stochastic, **kwargs)

Create SBML kinetic law for Hill propensity.

This method is shared by all Hill subclasses.

Parameters:

• model (libsbml.Model) – SBML model object.

• sbml_reaction (libsbml.Reaction) – SBML reaction to add kinetic law to.

• stochastic (bool) – If True, uses stochastic formulation (same as deterministic for Hill functions).

• **kwargs – Additional arguments. ‘reverse_reaction’ is not supported.

Returns:

Created SBML kinetic law object.

Return type:

libsbml.KineticLaw

Raises:

ValueError – If reverse_reaction=True (Hill propensities cannot be reversible) or if rate formula is invalid.

property d

Proportional species (None if not proportional).

Type:

Species

classmethod from_dict(propensity_dict)

Create a propensity from a dictionary.

Parameters:

propensity_dict (dict) – Dictionary with ‘parameters’ and ‘species’ keys containing parameter and species values.

Returns:

New instance of the propensity class.

Return type:

Propensity

static get_available_propensities() → Set

Get all available propensity subclasses.

Returns:

Set of all Propensity subclass types available in BioCRNpyler.

Return type:

set

Examples

>>> propensities = bcp.Propensity.get_available_propensities()
>>> bcp.MassAction in propensities
True

property is_reversible

Whether the propensity represents a reversible reaction.

Default is False. Subclasses override this for reversible kinetics.

Type:

bool

static is_valid_propensity(propensity_type) → bool

Check if an object is a valid Propensity subclass instance.

Recursively checks all subclasses of Propensity to determine if the given object is a valid propensity type.

Parameters:

propensity_type (object) – Object to check for Propensity validity.

Returns:

True if propensity_type is an instance of Propensity or any of its subclasses, False otherwise.

Return type:

bool

Examples

>>> prop = bcp.MassAction(k_forward=100.0)
>>> bcp.Propensity.is_valid_propensity(prop)
True
>>> bcp.Propensity.is_valid_propensity("not a propensity")
False

property k

Maximum rate constant value.

Type:

float

property k_forward

Forward rate constant.

Raises:

NotImplementedError – Must be implemented by subclasses that use rate constants.

Type:

Float

property k_reverse

Reverse rate constant for reversible reactions.

Raises:

NotImplementedError – Must be implemented by subclasses that use rate constants.

Type:

Float or None

property n

Hill coefficient (cooperativity) value.

Type:

float

pretty_print(show_parameters=True, **kwargs)

Generate human-readable string representation of propensity.

Parameters:

• show_parameters (bool, default True) – If True, includes parameter values in output.

• **kwargs – Additional keyword arguments passed to formatting methods.

Returns:

Formatted string showing rate formula and optionally parameters.

Return type:

str

pretty_print_parameters(show_keys=True, **kwargs)

Generate formatted string of all propensity parameters.

Parameters:

• show_keys (bool, default True) – If True, shows search and found keys for ModelParameter objects (useful for debugging parameter lookup).

• **kwargs – Additional formatting keyword arguments.

Returns:

Formatted string listing all parameters and their values.

Return type:

str

pretty_print_rate(show_parameters=True, **kwargs)

Generate human-readable rate formula string.

Returns:

Formatted Hill negative formula.

Return type:

str

property s1

Input species driving the Hill function.

Type:

Species

property species: List

All species used in the propensity function.

Type:

List of Species