New statistics

Author: Paulocracy

cosa/max_reacs_aerobic_WILDTYPE_OPTMDF_STANDARDCONC.txt

@@ -12,6 +12,7 @@
 nadph_to_nadp = []
 
 num_with_nad_or_nadp = 0
+tcosa_with_dG0 = []
 for key in list(dG0s.keys()):
     if key.endswith("_REV"):
         continue
@@ -37,24 +38,25 @@
     nadp_is_product = "nadp_c" in product_met_ids
     nadph_is_product = "nadph_c" in product_met_ids
 
+    is_nad_nadp = False
     if (nad_is_educt) and (nadh_is_product):
         nad_to_nadh.append(dG0)
         nadh_to_nad.append(-dG0)
-        print(key, dG0)
-        num_with_nad_or_nadp += 1
+        is_nad_nadp = True
     if (nadh_is_educt) and (nad_is_product):
         nadh_to_nad.append(dG0)
         nad_to_nadh.append(-dG0)
-        print(key, dG0)
-        num_with_nad_or_nadp += 1
+        is_nad_nadp = True
     if (nadp_is_educt) and (nadph_is_product):
         nadp_to_nadph.append(dG0)
         nadph_to_nadp.append(-dG0)
-        print(key, dG0)
-        num_with_nad_or_nadp += 1
+        is_nad_nadp = True
     if (nadph_is_educt) and (nadp_is_product):
         nadph_to_nadp.append(dG0)
         nadp_to_nadph.append(-dG0)
+        is_nad_nadp = True
+    if is_nad_nadp:
+        tcosa_with_dG0.append(key.replace("_FWD", ""))
         print(key, dG0)
         num_with_nad_or_nadp += 1
 
@@ -64,3 +66,5 @@
 print("nadp_to_nadph", round(mean(nadp_to_nadph), 3), round(median(nadp_to_nadph), 3), len(nadp_to_nadph))
 print("nadph_to_nadp", round(mean(nadph_to_nadp), 3), round(median(nadph_to_nadp), 3), len(nadph_to_nadp))
 print("num_with_nad_or_nadp", num_with_nad_or_nadp)
+print(len(set(tcosa_with_dG0)))
+print(tcosa_with_dG0)

cosa/max_reacs_aerobic_WILDTYPE_OPTSUBMDF_STANDARDCONC.txt

@@ -34,7 +34,7 @@ def cosa_maximal_reaction_numbers(anaerobic: bool, expanded: bool, growth_epsilo
     biomass_reaction_id = "BIOMASS_Ec_iML1515_core_75p37M"
 
     original_cobra_model = copy.deepcopy(cobra_model)
-    for concentrations in ("STANDARDCONC", "VIVOCONC"):
+    for concentrations in ("STANDARDCONC",): #"VIVOCONC"):
         print(f"CONCENTRATIONS: {concentrations}")
         print(f"=CONCENTRATION RANGES: {concentrations}=")
         if concentrations == "STANDARDCONC":
@@ -44,7 +44,7 @@ def cosa_maximal_reaction_numbers(anaerobic: bool, expanded: bool, growth_epsilo
             dG0_values = copy.deepcopy(paperconc_dG0_values)
             used_concentration_values = concentration_values_paper
 
-        for target in ("OPTSUBMDF",): # "OPTMDF",
+        for target in ("OPTMDF", "OPTSUBMDF"):
             print(f"TARGET: {target}")
             print(f"===OPTIMIZATION TARGET: {target}===")
 
@@ -81,16 +81,19 @@ def cosa_maximal_reaction_numbers(anaerobic: bool, expanded: bool, growth_epsilo
                     cat=pulp.LpContinuous,
                 )
                 z_sum = 0.0
+                all_tcosa_ids = get_all_tcosa_reaction_ids(cobra_model)
                 for reaction_id in reaction_ids:
-                    if not reaction_id.endswith("_TCOSA"):
-                        continue
-                    z_active = pulp.LpVariable(
-                        name=f"z_active_{reaction_id}",
-                        cat=pulp.LpBinary,
-                    )
-                    optmdfpathway_base_problem += -optmdfpathway_base_variables[reaction_id] + z_active * 1e-6 <= 0
-                    optmdfpathway_base_variables: Dict[str, pulp.LpVariable] = optmdfpathway_base_problem.variablesDict()
-                    z_sum += optmdfpathway_base_variables[f"z_active_{reaction_id}"]
+                    # if not reaction_id.endswith("_TCOSA"):
+                    #     continue
+                    # z_active = pulp.LpVariable(
+                    #     name=f"z_active_{reaction_id}",
+                    #     cat=pulp.LpBinary,
+                    # )
+                    # optmdfpathway_base_problem += -optmdfpathway_base_variables[reaction_id] + z_active * 1e-5 <= 0
+                    # optmdfpathway_base_variables: Dict[str, pulp.LpVariable] = optmdfpathway_base_problem.variablesDict()
+                    if reaction_id in all_tcosa_ids:
+                        if "_VARIANT_" not in reaction_id:
+                            z_sum += optmdfpathway_base_variables[f"z_var_{reaction_id}"]
                 z_sum_var = pulp.LpVariable(
                     name=f"z_sum_var",
                     lowBound=-float("inf"),
@@ -143,7 +146,7 @@ def cosa_maximal_reaction_numbers(anaerobic: bool, expanded: bool, growth_epsilo
                         z_value = minimization_result["values"][var_name]
                         reaction_string = cobra_model.reactions.get_by_id(reac_id).reaction
                         if z_value > 0.1:
-                            report_line = f"* {reac_id} | {round(dG0_values[reac_id]['dG0'], 3)} kJ/mol | {reaction_string}"
+                            report_line = f"* {reac_id} | {round(dG0_values[reac_id]['dG0'], 3)} kJ/mol | {minimization_result['values'][reac_id]} | {reaction_string}"
                             active_reactions.append(reac_id)
                             # print(report_line)
                             report += report_line + "\n"

cosa/max_reacs_anaerobic_WILDTYPE_OPTMDF_STANDARDCONC.txt

@@ -0,0 +1,32 @@
+import cobra
+from statistics import mean, median
+from helper import json_load
+
+
+model = cobra.io.read_sbml_model("resources/iML1515_irreversible_cleaned.xml")
+dG0s = json_load("resources/dG0_iML1515_irreversible_cleaned.json")
+
+with open("./deleted_transporters.txt", "r", encoding="utf-8") as f:
+    deleted = f.readlines()
+deleted = [x.split(" | ")[0].replace("_ORIGINAL_NADP_TCOSA", "")\
+                    .replace("_ORIGINAL_NAD_TCOSA", "")\
+                    .replace("_VARIANT_NAD_TCOSA", "")\
+                    .replace("_VARIANT_NADP_TCOSA", "")\
+                    .replace("_FWD", "")\
+                    .replace("_REV", "") for x in deleted]
+
+num_with_dG0 = 0
+for key in list(dG0s.keys()):
+    if key.endswith("_REV"):
+        continue
+    key = key.replace("_ORIGINAL_NADP_TCOSA", "")\
+            .replace("_ORIGINAL_NAD_TCOSA", "")\
+            .replace("_VARIANT_NAD_TCOSA", "")\
+            .replace("_VARIANT_NADP_TCOSA", "")\
+            .replace("_FWD", "")\
+            .replace("_REV", "")
+    if key in deleted:
+        continue
+    num_with_dG0 += 1
+
+print("num_with_dG0", num_with_dG0)