Updated reference manual

biocrnpyler/components/__init__.py

@@ -1,4 +1,4 @@
-"""BioCRNpyler component library (including DNA components).
+r"""BioCRNpyler component library (including DNA components).
 
 Components are the primary building blocks of models in BioCRNpyler.
 They represent biomolecular parts or motifs such as promoters,

biocrnpyler/components/basic.py

@@ -9,7 +9,7 @@
 
 
 class DNA(Component):
-    """DNA sequence component with specified length.
+    r"""DNA sequence component with specified length.
 
     A `DNA` component represents a DNA sequence with a given length in base
     pairs. This component has no associated mechanism to generate species or
@@ -665,7 +665,7 @@ def update_reactions(self) -> List[Reaction]:
 
 
 class Enzyme(Component):
-    """Enzyme that catalyzes conversion of substrates to products.
+    r"""Enzyme that catalyzes conversion of substrates to products.
 
     An `Enzyme` component represents an enzyme that catalyzes the conversion
     of one or more substrates into one or more products. The enzyme itself
@@ -712,7 +712,7 @@ class Enzyme(Component):
     The `Enzyme` component assumes all substrates are converted to all
     products in a single enzymatic step:
 
-        S1 + S2 + ... + SN + E --> P1 + P2 + ... + PM + E
+    $$ 'S1' + 'S2' + ... + 'S'_N + 'E' --> 'P1' + 'P2' + ... + 'P'_M + 'E' $$
 
     For enzymes that catalyze multiple distinct reactions, create separate
     `Enzyme` components with the same internal enzyme species.

biocrnpyler/components/combinatorial_complex.py

@@ -9,7 +9,7 @@
 
 
 class CombinatorialComplex(Component):
-    """Complex formed through combinatorial binding of multiple species.
+    r"""Complex formed through combinatorial binding of multiple species.
 
     A `CombinatorialComplex` component represents a complex that can form
     through multiple combinatorial binding pathways. The component
@@ -69,22 +69,22 @@ class CombinatorialComplex(Component):
     Case 1 - only `final_states` given: all species in final_states bind
     combinatorially:
 
-        individual_species <--> all_intermediates <--> final_states
+      $$'individual species' <--> 'all intermediates' <--> 'final states'$$
 
     Case 2 - `final_states` + `initial_states`: binding starts from
     specified initial states directly to final states:
 
-        initial_states <--> final_states
+      $$'initial_states' <--> 'final_states'$$
 
     Case 3 - `final_states` + `intermediate_states`: binding restricted to
     specified intermediates:
 
-        individual_species <--> intermediate_states <--> final_states
+      $$'individual species' <--> 'intermediate states' <--> 'final states'$$
 
     Case 4 - `final_states` + `initial_states` + `intermediate_states`: both
     initial and intermediate constraints applied:
 
-        initial_states <--> intermediate_states <--> final_states
+      $$'initial states' <--> 'intermediate states' <--> 'final states'$$
 
     The component name is automatically generated as a concatenation of
     final_states names separated by underscores if not provided.
@@ -700,6 +700,7 @@ def update_reactions(self):
             2. Generate reactions: intermediate_states <--> final_states
 
         Without intermediate_states:
+
             Generate reactions: initial_states <--> final_states directly
 
         Duplicate reactions are automatically filtered out. The method uses

biocrnpyler/components/dna/assembly.py

@@ -18,10 +18,10 @@ class DNAassembly(DNA):
     """High-level representation of a gene expression construct.
 
     A DNAassembly represents a complete gene expression unit combining a
-    promoter region, ribosome binding site (RBS), coding sequence, and the
-    RNA and protein products. This class provides a convenient interface for
-    modeling the central dogma pathway: DNA --> RNA --> Protein, where the
-    promoter controls transcription and the RBS controls translation.
+    promoter region, ribosome binding site (RBS), coding sequence, and the RNA
+    and protein products. This class provides a convenient interface for
+    modeling the central dogma pathway: DNA --> RNA --> Protein, where
+    the promoter controls transcription and the RBS controls translation.
 
     Parameters
     ----------

biocrnpyler/components/dna/promoter.py

@@ -646,14 +646,11 @@ class ActivatablePromoter(Promoter):
     Notes
     -----
     The activation follows a Hill function:
-
-    .. math::
-
-        \text{rate} = k_{\text{max}} \frac{[A]^n}{K_d^n + [A]^n}
-            + k_{\text{leak}}
-
-    where [A] is activator concentration, n is the Hill coefficient, and
-    :math:`K_d` is the dissociation constant.
+    $$
+    'rate' = k_'max' \frac{[A]^n}{K_d^n + [A]^n} + k_'leak'
+    $$
+    where [A] is activator concentration, $n$ is the Hill coefficient, and
+    $K_d$ is the dissociation constant.
 
     Examples
     --------
@@ -792,14 +789,11 @@ class RepressiblePromoter(Promoter):
     Notes
     -----
     The repression follows a Hill function:
-
-    .. math::
-
-        \text{rate} = k_{\text{max}} \frac{K_d^n}{K_d^n + [R]^n}
-            + k_{\text{leak}}
-
-    where [R] is repressor concentration, n is the Hill coefficient, and
-    :math:`K_d` is the dissociation constant.
+    $$
+    'rate' = k_'max' \frac{K_d^n}{K_d^n + [R]^n} + k_'leak'
+    $$
+    where [R] is repressor concentration, $n$ is the Hill coefficient, and
+    $K_d$ is the dissociation constant.
 
     Examples
     --------

biocrnpyler/components/membrane.py

@@ -10,7 +10,7 @@
 
 
 class DiffusibleMolecule(Component):
-    """Molecule that diffuses passively through a membrane.
+    r"""Molecule that diffuses passively through a membrane.
 
     A `DiffusibleMolecule` component represents a molecule that undergoes
     passive diffusion across a membrane between two compartments. The
@@ -54,6 +54,7 @@ class DiffusibleMolecule(Component):
     energy. The diffusion mechanism generates bidirectional reactions:
 
     - Forward: substrate_internal --> substrate_external
+
     - Reverse: substrate_external --> substrate_internal
 
     If not specified using the `name` keyword, the component name is
@@ -442,9 +443,11 @@ class MembraneChannel(Component):
     The transport mechanism generates reactions based on the direction:
 
     - 'Importer': substrate_external + channel
-          --> substrate_internal + channel
+      --> substrate_internal + channel
+
     - 'Exporter': substrate_internal + channel
-          --> substrate_external + channel
+      --> substrate_external + channel
+
     - 'Passive': bidirectional transport following gradients
 
     The component name is automatically generated as:
@@ -679,9 +682,10 @@ class MembranePump(Component):
     against concentration gradients. The typical reaction scheme is:
 
     - Exporter: substrate_internal + ATP + pump -->
-                substrate_external + ADP + pump
+      substrate_external + ADP + pump
+
     - Importer: substrate_external + ATP + pump -->
-                substrate_internal + ADP + pump
+      substrate_internal + ADP + pump
 
     The ATP parameter controls the stoichiometry of ATP consumption per
     transport event.
@@ -877,7 +881,7 @@ def get_species(self):
         return self.membrane_pump
 
     def update_species(self):
-        """Use 'trasnport' mechanism to generate ATP-dependent species.
+        r"""Use 'transport' mechanism to generate ATP-dependent species.
 
         Uses the 'transport' mechanism to generate species including the
         pump protein, substrate, product, ATP, and ADP.
@@ -899,7 +903,7 @@ def update_species(self):
         )
 
     def update_reactions(self):
-        """Use 'trasnport' mechanism to generate ATP-dependent reactions.
+        """Use 'transport' mechanism to generate ATP-dependent reactions.
 
         Uses the 'transport' mechanism to generate reactions for active
         transport coupled to ATP hydrolysis.
@@ -923,7 +927,7 @@ def update_reactions(self):
 
 
 class MembraneSensor(Component):
-    """Two-component system (TCS) membrane sensor protein.
+    r"""Two-component system (TCS) membrane sensor protein.
 
     A `MembraneSensor` component represents a membrane sensor protein in a
     two-component signaling system. The sensor detects external signal
@@ -995,9 +999,10 @@ class MembraneSensor(Component):
     4. Activated response regulator regulates gene expression
 
     The general reaction scheme:
-
-        signal + sensor + ATP + response_protein -->
-        signal + sensor + ADP + response_protein-P
+    $$
+        & 'signal' + 'sensor' + 'ATP' + 'response_protein' \\
+        &     --> 'signal' + 'sensor' + 'ADP' + 'response_protein-P'
+    $$
 
     The component name is automatically generated as:
     '<membrane_sensor_protein_name>_<compartment_name>'

biocrnpyler/core/chemical_reaction_network.py

@@ -67,10 +67,10 @@ class ChemicalReactionNetwork(object):
     -----
     Mass action reactions follow standard mass action kinetics:
 
-    - Deterministic propensity: :math:`k \prod_{i} [S_i]^{a_i}`
-    - Stochastic propensity: :math:`k \prod_{i} \frac{S_i!}{(S_i - a_i)!}`
+    - Deterministic propensity: $k \prod_i [S$_i$]^{a_i}$
+    - Stochastic propensity: $k \prod_i \frac{S_i!}{(S_i - a_i)!}$
 
-    where :math:`a_i` is the stoichiometric coefficient of species :math:`i`.
+    where $a_i$ is the stoichiometric coefficient of species $i$.
 
     A valid CRN requires:
 

biocrnpyler/core/component.py

@@ -394,9 +394,9 @@ def add_attribute(self, attribute: str):
         ['fluorescent', 'ssrAtagged']
 
         """
-        assert (
-            isinstance(attribute, str) and attribute is not None
-        ), f"Attribute: {attribute} must be a str"
+        assert isinstance(attribute, str) and attribute is not None, (
+            f"Attribute: {attribute} must be a str"
+        )
 
         self.attributes.append(attribute)
         if hasattr(self, 'species') and self.species is not None:

biocrnpyler/core/mixture.py

@@ -239,9 +239,9 @@ def add_species(self, species: Union[List[Species], Species]):
             else:
                 species_list = species
 
-            assert all(
-                isinstance(x, Species) for x in species_list
-            ), 'only Species type is accepted!'
+            assert all(isinstance(x, Species) for x in species_list), (
+                'only Species type is accepted!'
+            )
 
             self.added_species += species_list
 

biocrnpyler/core/polymer.py

@@ -194,9 +194,9 @@ def polymer(self, parts):
 
         """
         polymer = []
-        assert isinstance(
-            parts, (list, tuple)
-        ), 'OrderedPolymer must be instantiated with a list'
+        assert isinstance(parts, (list, tuple)), (
+            'OrderedPolymer must be instantiated with a list'
+        )
         for item in parts:
             if isinstance(item, (list, tuple)):
                 part = item[0]