matlab-simulate-simbiology-model

Name: matlab-simulate-simbiology-model
Author: matlab

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How to install matlab-simulate-simbiology-model?

matlab/matlab-agentic-toolkit/matlab-simulate-simbiology-model

$npx -y skills add matlab/matlab-agentic-toolkit --skill matlab-simulate-simbiology-model

Installs into the current project.

Summary

Simulate SimBiology models — ODE, stochastic (SSA), scenarios, and sensitivity analysis. Use when asked to run, simulate, predict, explore what-if, or identify influential parameters.

Files · 1

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SKILL.md

1	# Simulate SimBiology Models
2
3	Run simulations of SimBiology models: deterministic ODE, stochastic SSA,
4	scenario exploration, and sensitivity analysis.
5
6	## When to Use
7
8	- "simulate", "run", "predict" model behavior
9	- "what if" / "what happens if" (implies simulation or scenarios)
10	- Time-course results from a model
11	- Dose-response studies, parameter sweeps, factorial designs
12	- Stochastic, SSA, Gillespie, noise, gene expression variability
13	- "which parameters matter most", sensitivity, Sobol, Morris
14	- Keywords: "simulate", "run", "predict", "what-if", "stochastic", "sensitivity"
15
16	## When NOT to Use
17
18	- Model construction or diagram layout (use `matlab-build-simbiology-model`)
19	- Parameter estimation from data (use `matlab-fit-simbiology-model`)
20	- NCA / AUC / Cmax from data (use `matlab-fit-simbiology-model`)
21
22	## Must-Follow Rules
23
24	### 0. Add helper scripts to the MATLAB path first
25
26	Run at the start of every session:
27	```matlab
28	addpath(fullfile('<WORKSPACE_ROOT>', '.claude', 'skills', 'matlab-simulate-simbiology-model', 'scripts'));
29	```
30
31	### 1. Element-wise operators in observables
32
33	Use `./` and `.*` (element-wise) in observable expressions when mixing
34	time-varying species with constant parameters. Plain `/` and `*` cause
35	size mismatches at simulation time.
36
37	### 2. StatesToLog for constant parameters
38
39	When observables reference constant parameters (e.g., `Drug ./ Vd`),
40	add those parameters explicitly to `StatesToLog`:
41	```matlab
42	cs.RuntimeOptions.StatesToLog = [m.Species; sbioselect(m,'Type','parameter','Name','Vd')];
43	```
44	`StatesToLog = 'all'` does not log constant compartments or parameters.
45
46	### 3. All reactions must be MassAction for SSA
47
48	The stochastic solver does not support custom rate expressions. Every
49	reaction must use `addkineticlaw(rx, 'MassAction')`.
50
51	### 4. Do NOT combine Scenarios with `+`
52
53	The `+` operator is not supported on `SimBiology.Scenarios` objects.
54	Always use `add()` to append entries.
55
56	### 5. Reset local sensitivity options after use
57
58	Local sensitivity settings persist on the configset and affect
59	subsequent simulations. Always reset:
60	```matlab
61	cs.SolverOptions.SensitivityAnalysis = false;
62	cs.SensitivityAnalysisOptions.Inputs = [];
63	cs.SensitivityAnalysisOptions.Outputs = [];
64	```
65
66	### 6. Set `MaximumWallClock` to prevent hung simulations
67
68	When fitting or scanning, bad parameter values can make individual
69	simulations extremely slow. Protect against this:
70	```matlab
71	cs.MaximumWallClock = 60; % seconds; default is Inf
72	```
73	This is a configset property (not a solver or optimizer option).
74	It stops any single simulation that exceeds the wall clock limit.
75
76	### 7. Unit conversion requires `TimeUnits`
77
78	When `cs.CompileOptions.UnitConversion = true`, you MUST also set
79	`cs.TimeUnits` to match your StopTime units (e.g., `'hour'`).
80	Otherwise SimBiology defaults to seconds and your 24-unit simulation
81	covers 24 seconds, not 24 hours:
82	```matlab
83	cs.CompileOptions.UnitConversion = true;
84	cs.TimeUnits = 'hour';
85	cs.StopTime = 24; % now correctly 24 hours
86	```
87
88	### 8. Scenario results are interleaved, not blocked
89
90	Factorial scenario results come back interleaved by the first dimension.
91	Always use `generate(sc)` to map result indices to conditions — never
92	assume all entries of one factor appear consecutively.
93
94	## Decision Table
95
96	\| Scenario \| Approach \|
97	\|----------\|----------\|
98	\| One-off simulation \| `sbiosimulate` \|
99	\| Parameter sweep / Monte Carlo \| `createSimFunction` \|
100	\| Dose/variant/parameter what-if \| `SimBiology.Scenarios` + `createSimFunction` \|
101	\| Low molecule count / noise \| SSA solver (`cs.SolverType = 'ssa'`) \|
102	\| Which parameters matter? \| `sbiosobol` (Sobol) or `sbioelementaryeffects` (Morris) \|
103	\| Quick sensitivity check \| Local sensitivity via configset \|
104
105	## Basic Simulation (`sbiosimulate`)
106
107	Prefer returning SimData (single output) — it carries state names,
108	units, and metadata, and works directly with `sbioplot` and `selectbyname`:
109
110	```matlab
111	m = getModelByUUID(modelId);
112	cs = getconfigset(m, 'active');
113	cs.StopTime = 24;
114	cs.SolverType = 'ode15s';
115	simData = sbiosimulate(m);
116	```
117
118	With a dose (configset is required as 2nd argument when passing doses):
119	```matlab
120	d = sbiodose('Bolus', 'schedule');
121	d.TargetName = 'Drug'; d.Amount = 100; d.Time = 0;
122	simData = sbiosimulate(m, cs, d); % NOT sbiosimulate(m, d) — errors
123	```
124
125	## Plotting Results
126
127	Use `sbioplot` for quick visualization of SimData:
128	```matlab
129	simData = sbiosimulate(m, cs, d);
130	sbioplot(simData);
131	```
132
133	For custom plots, extract numeric data first:
134	```matlab
135	[t, x, names] = getdata(simData);
136	plot(t, x);
137	legend(names, 'Interpreter', 'none');
138	xlabel('Time'); ylabel('Amount');
139	```
140
141	## Extracting State Data from SimData
142
143	Use

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matlab-simulate-simbiology-model

815stars105forks

View on GitHub

How to install matlab-simulate-simbiology-model?

matlab/matlab-agentic-toolkit/matlab-simulate-simbiology-model

$npx -y skills add matlab/matlab-agentic-toolkit --skill matlab-simulate-simbiology-model

Installs into the current project.

Summary

Simulate SimBiology models — ODE, stochastic (SSA), scenarios, and sensitivity analysis. Use when asked to run, simulate, predict, explore what-if, or identify influential parameters.

Files · 1

View on GitHub

SKILL.md

1	# Simulate SimBiology Models
2
3	Run simulations of SimBiology models: deterministic ODE, stochastic SSA,
4	scenario exploration, and sensitivity analysis.
5
6	## When to Use
7
8	- "simulate", "run", "predict" model behavior
9	- "what if" / "what happens if" (implies simulation or scenarios)
10	- Time-course results from a model
11	- Dose-response studies, parameter sweeps, factorial designs
12	- Stochastic, SSA, Gillespie, noise, gene expression variability
13	- "which parameters matter most", sensitivity, Sobol, Morris
14	- Keywords: "simulate", "run", "predict", "what-if", "stochastic", "sensitivity"
15
16	## When NOT to Use
17
18	- Model construction or diagram layout (use `matlab-build-simbiology-model`)
19	- Parameter estimation from data (use `matlab-fit-simbiology-model`)
20	- NCA / AUC / Cmax from data (use `matlab-fit-simbiology-model`)
21
22	## Must-Follow Rules
23
24	### 0. Add helper scripts to the MATLAB path first
25
26	Run at the start of every session:
27	```matlab
28	addpath(fullfile('<WORKSPACE_ROOT>', '.claude', 'skills', 'matlab-simulate-simbiology-model', 'scripts'));
29	```
30
31	### 1. Element-wise operators in observables
32
33	Use `./` and `.*` (element-wise) in observable expressions when mixing
34	time-varying species with constant parameters. Plain `/` and `*` cause
35	size mismatches at simulation time.
36
37	### 2. StatesToLog for constant parameters
38
39	When observables reference constant parameters (e.g., `Drug ./ Vd`),
40	add those parameters explicitly to `StatesToLog`:
41	```matlab
42	cs.RuntimeOptions.StatesToLog = [m.Species; sbioselect(m,'Type','parameter','Name','Vd')];
43	```
44	`StatesToLog = 'all'` does not log constant compartments or parameters.
45
46	### 3. All reactions must be MassAction for SSA
47
48	The stochastic solver does not support custom rate expressions. Every
49	reaction must use `addkineticlaw(rx, 'MassAction')`.
50
51	### 4. Do NOT combine Scenarios with `+`
52
53	The `+` operator is not supported on `SimBiology.Scenarios` objects.
54	Always use `add()` to append entries.
55
56	### 5. Reset local sensitivity options after use
57
58	Local sensitivity settings persist on the configset and affect
59	subsequent simulations. Always reset:
60	```matlab
61	cs.SolverOptions.SensitivityAnalysis = false;
62	cs.SensitivityAnalysisOptions.Inputs = [];
63	cs.SensitivityAnalysisOptions.Outputs = [];
64	```
65
66	### 6. Set `MaximumWallClock` to prevent hung simulations
67
68	When fitting or scanning, bad parameter values can make individual
69	simulations extremely slow. Protect against this:
70	```matlab
71	cs.MaximumWallClock = 60; % seconds; default is Inf
72	```
73	This is a configset property (not a solver or optimizer option).
74	It stops any single simulation that exceeds the wall clock limit.
75
76	### 7. Unit conversion requires `TimeUnits`
77
78	When `cs.CompileOptions.UnitConversion = true`, you MUST also set
79	`cs.TimeUnits` to match your StopTime units (e.g., `'hour'`).
80	Otherwise SimBiology defaults to seconds and your 24-unit simulation
81	covers 24 seconds, not 24 hours:
82	```matlab
83	cs.CompileOptions.UnitConversion = true;
84	cs.TimeUnits = 'hour';
85	cs.StopTime = 24; % now correctly 24 hours
86	```
87
88	### 8. Scenario results are interleaved, not blocked
89
90	Factorial scenario results come back interleaved by the first dimension.
91	Always use `generate(sc)` to map result indices to conditions — never
92	assume all entries of one factor appear consecutively.
93
94	## Decision Table
95
96	\| Scenario \| Approach \|
97	\|----------\|----------\|
98	\| One-off simulation \| `sbiosimulate` \|
99	\| Parameter sweep / Monte Carlo \| `createSimFunction` \|
100	\| Dose/variant/parameter what-if \| `SimBiology.Scenarios` + `createSimFunction` \|
101	\| Low molecule count / noise \| SSA solver (`cs.SolverType = 'ssa'`) \|
102	\| Which parameters matter? \| `sbiosobol` (Sobol) or `sbioelementaryeffects` (Morris) \|
103	\| Quick sensitivity check \| Local sensitivity via configset \|
104
105	## Basic Simulation (`sbiosimulate`)
106
107	Prefer returning SimData (single output) — it carries state names,
108	units, and metadata, and works directly with `sbioplot` and `selectbyname`:
109
110	```matlab
111	m = getModelByUUID(modelId);
112	cs = getconfigset(m, 'active');
113	cs.StopTime = 24;
114	cs.SolverType = 'ode15s';
115	simData = sbiosimulate(m);
116	```
117
118	With a dose (configset is required as 2nd argument when passing doses):
119	```matlab
120	d = sbiodose('Bolus', 'schedule');
121	d.TargetName = 'Drug'; d.Amount = 100; d.Time = 0;
122	simData = sbiosimulate(m, cs, d); % NOT sbiosimulate(m, d) — errors
123	```
124
125	## Plotting Results
126
127	Use `sbioplot` for quick visualization of SimData:
128	```matlab
129	simData = sbiosimulate(m, cs, d);
130	sbioplot(simData);
131	```
132
133	For custom plots, extract numeric data first:
134	```matlab
135	[t, x, names] = getdata(simData);
136	plot(t, x);
137	legend(names, 'Interpreter', 'none');
138	xlabel('Time'); ylabel('Amount');
139	```
140
141	## Extracting State Data from SimData
142
143	Use

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