BioOpt Classes (API)¶

Model¶

class model.Bounds(lb=-inf, ub=inf)¶

Bases: object

Bounds holds description of reactions constraints

Parameters:	lb – Minimal amount of of flux that can go through a reaction (Lower bound). Negative numbers denote reverse direction. ub – Maximal amount of of flux that can go through a reaction (Upper bound). Negative numbers denote reverse direction.
Returns:	`Bounds`

copy()¶

Create a deep copy of current object

Return type:	`Bounds`

direction¶

Suggested reaction direction. If lower bound is negative the reaction is suggested to be reversible. Otherwise irreversibility is implied. This is only a suggestion to Reaction class and this suggestion can be broken by enabling reaction reversibility through Reaction.direction

Return type:	`Direction`

static inf()¶

Returns infinity

Returns:	`float`

lb¶: Minimal amount of of flux that can go through a reaction (Lower bound). Negative numbers denote reverse direction.

lb_is_finite¶: Returns inf False if lower bound is -infinity or +infinity

ub¶: Maximal amount of of flux that can go through a reaction (Upper bound). Negative numbers denote reverse direction.

ub_is_finite¶: Returns inf False if upper bound is -infinity or +infinity

class model.Direction(type)¶

Bases: object

Describe reaction directionality. Don’t use this class directly! Use factory constructors Direction.forward() and Direction.reversible()

Parameters:	type – f - Irreversible (f orward); r - Reversible (r eversible)
Returns:	`Direction`

copy()¶

Create a deep copy of current object

Return type:	`Direction`

static forward()¶

Returns irreversible directionality descriptor singleton of type Direction

Returns:	`Direction`

static reversible()¶

Returns reversible directionality descriptor singleton of type Direction

Returns:	`Direction`

class model.Metabolite(name, boundary=False)¶

Bases: object

Metabolite holds information about metabolite. Currently only supported information is metabolite name and whether metabolite satisfies boundary condition (imported/exported)

Parameters:	name – Metabolite name. Metabolite name should be a non-empty string. boundary – Boundary condition (imported/exported - True; otherwise - false)
Returns:	`Metabolite`

boundary¶: Boundary condition (imported/exported - True; otherwise - false)

copy()¶

Create a deep copy of current object

Return type:	`Metabolite`

name¶: Metabolite name. Metabolite name should be a non-empty string.

order_boundary¶: Priority of displaying this metabolite. Metabolites with higher priority (lower numbers) are displayed earlier in “-External Metabolites” section

class model.Model¶

Bases: object

BioOpt model is a main class in package. It contains list of reactions in the model and other additional information.

static commune(models, model_prefix='ML{0:04d}_', env_prefix='ENV_', block=[])¶

Merge two or more models into community model. Community model allows organisms represented by models to share metabolites. Briefly, the algorithm first appends reaction and metabolite names in original models with ML****_ prefix. Then for every metabolite exported in original models boundary condition is set to False and new export reaction is created. This export reactions allows metabolites to travel from joined models into shared environment and back. This setup allows organisms to exchange metabolites through common environment.

Originally this merging framework was described in “OptCom: A Multi-Level Optimization Framework for the Metabolic Modeling and Analysis of Microbial Communities” by Ali R. Zomorrodi and Costas D. Maranas.

Parameters:

models – List of Model to join
model_prefix – Model prefix, Model prefix is added to all reaction names to avoid name collision in joined model.
env_prefix – Prefix of metabolites in shared environment.
block – List of names (in original models) of metabolites which should be not allowed to be exchanged between organisms. An obvious example of such metabolite is biomass.

Return type:

Model

design_objective¶

Design optimization target (i.e. Ethanol)

Return type:	list of `MathExpression`

find_boundary_metabolites()¶

Searches for imported/exported metabolites

Return type:	list of `Metabolite`

find_boundary_reactions()¶

Searches for reactions exporting or importing metabolites

Return type:	list of `Reaction`

find_metabolite(names=None, regex=False)¶

Searches model for metabolites with specified names (patterns). If multiple metabolites are found this function returns only the first one.

Parameters:	names – name or list of names of metabolites regex – If True names argument is assumed to be a regular expression
Return type:	`Metabolite`

find_metabolites(names=None, regex=False)¶

Searches model for metabolites with specified names (patterns). This function is capable of returning multiple metabolites.

Parameters:	names – name or list of names of metabolites regex – If True names argument is assumed to be a regular expression
Return type:	list of `Metabolite`

find_reaction(names=None, regex=False)¶

Searches model for reactions with specified names (patterns). If multiple reactions are found this function returns only the first one.

Parameters:	names – name or list of names of reactions regex – If True names argument is assumed to be a regular expression
Return type:	`Reaction`

find_reactions(names=None, regex=False)¶

Searches model for reactions with specified names (patterns). This function is capable of returning multiple reactions.

Parameters:	names – name or list of names of reactions regex – If True names argument is assumed to be a regular expression
Return type:	list of `Reaction`

objective¶

Optimization target (i.e. Biomass)

Return type:	class:MathExpression

reactions¶

List of reactions in the model

Return type:	list of `Reaction`

save(path=None, inf=1000)¶

Save model on disc in bioopt format

Parameters:	path – The name or full pathname of the file where the BioOpt model is to be written. inf – Number which would be used for constraints with infinite bounds

unify_references()¶: Find metabolite with identical names which are stored as different instances and unify instances.

class model.Operation(operation, is_unary)¶

Bases: object

Object describing operation type. Don’t use this class directly! Instead use factory constructors:

Operation.addition()
Operation.subtraction()
Operation.multiplication()
Operation.division()
Operation.negation() (Unary operation)

Parameters:	operation – String describing the operation (binary operations: `+-/`, unary operations: `-`) is_unary* – Describes what type of operation is created. Unary operations support only one argument, while binary support two.
Returns:	`Operation`

static addition()¶

Returns addition operation singleton

Return type:	`Operation`

static division()¶

Returns division operation singleton

Return type:	`Operation`

is_unary¶: Is operation unary. True - unary; otherwise False :return: bool

static multiplication()¶

Returns multiplication operation singleton

Return type:	`Operation`

static negation()¶

Returns negation operation (unary) singleton

Return type:	`Operation`

priority¶

Operation priority. Operations with higher priority (lower numbers) are executed before lower priority operations

Return type:	`Operation`

static subtraction()¶

Returns subtraction operation singleton

Return type:	`Operation`

symbol¶

Short description of operation

- Addition
- Subtraction
/ Division
- Multiplication
- Negation

Return type:	`Operation`

class model.Reaction(name, reactants=, products=, direction=None, bounds=None)¶

Bases: object

Reaction class holds information about reaction including reaction name, members, directionality and constraints

Parameters:	name – Reaction name. Reaction name should be non-empty string reactants – Reaction left-hand-side. Object of class `ReactionMemberList`. products – Reaction right-hand-side. Object of class `ReactionMemberList`. direction – Reaction direction. Object of class `Direction`. bounds – Reaction constraints. Object of class `Bounds`.
Return type:	`Reaction`

bounds¶

Reaction constraints

Return type:	`Bounds`

bounds_reset()¶: Reset bounds to predefined default. For reversible reaction defaults bounds are [-inf, +inf]. For forward reactions it is [0, +inf]

copy()¶

Create a deep copy of current object

Return type:	`Reaction`

direction¶

Reaction direction

Return type:	`Direction`

find_effective_bounds()¶

Find effective bounds. For example if reaction is described as irreversible but constraints are [-10, 10] the effective bounds would be [0, 10]

Return type:	`Bounds`

name¶: Reaction name

products¶

Products

Return type:	`ReactionMemberList`

reactants¶

Reactants

Return type:	`ReactionMemberList`

reverse()¶: Reverse reactions. This functions change reactants and products places and inverses constraints so that reaction would go other way

class model.ReactionMember(metabolite, coefficient=1)¶

Bases: object

Bounds is a wrapper for Metabolite object when used in reaction reactants or products. It contains reference to the metabolite itself and to it’s coefficient in the reaction.

Parameters:	metabolite – Reference to `Metabolite` object coefficient – Multiplier associated with metabolite
Returns:	`ReactionMember`

coefficient¶: Multiplier associated with metabolite

copy()¶

Create a deep copy of current object

Return type:	`ReactionMember`

metabolite¶

Reference to metabolite

Return type:	`Metabolite`

class model.ReactionMemberList¶

Bases: list

ReactionMemberList is a list of ReactionMember instances. ReactionMemberList inherits from list all the usual functions to manage a list

copy()¶

Create a deep copy of current object

Return type:	`ReactionMemberList`

find_member(name)¶

Find metabolite by name in the list

Return type:	`ReactionMember`

Converter¶

class converter.Bioopt2CobraPyConverter(description=None)¶

Bioopt model object to COBRApy model object converter. More details on COBRApy library can be found online

Return type:	`Bioopt2COBRApyConverter`

convert(bioopt_model)¶

Convert BioOpt model to COBRApy model instance

Parameters:	bioopt_model – BioOpt model of type :class;`model.Model`
Return type:	`cobra.Model`

class converter.Bioopt2SbmlConverter(level=2, version=3, inf=1000, reaction_id='auto', metabolite_id='auto', compartment_id='auto', compartment_suffix=True, compartment_pattern='_(\w+)$', simulate_boundary=False, metabolite_map={})¶

Bioopt model object to libSBML document object converter. More details on SBML specification can be found online

Parameters:

level – SBML level from 1 to 3 (default: 2)
version – SBML version number (default: 3). Check SBML specification for details
inf – A number to substitute __infinity__ values. SBML doesn’t have number __infinity__ so everywhere infinity is used in BioOpt it will be replaced with this number (default: 1000)
reaction_id – Reaction id pattern. “name” - reaction name will be used as id. “auto” - an auto-incremental “R_XXXX” value will be used for reaction id (default: “auto”)
metabolite_id – Metabolite id pattern. “name” - metabolite name will be used as id. “auto” - an auto-incremental “M_XXXX” value will be used for metabolite id (default: “auto”)
compartment_id – Compartment id pattern. “name” - compartment name will be used as id. “auto” - an auto-incremental “C_XXXX” value will be used for compartment id (default: “auto”)
compartment_suffix – Specifies whether metabolite names should be appended with compartment name
compartment_pattern – Regular expression pattern describing how to extract compartment information from metabolite name. By default everything after last underscore _ character is considered a compartment. i.e., metabolite_e - is from compartment “e”

Return type:

Bioopt2SbmlConverter

convert(bioopt_model)¶

Convert BioOpt model to libSBML document instance

Parameters:	bioopt_model – BioOpt model of type :class;`model.Model`
Return type:	`libsbml.SBMLDocument`