XPPAUT computer codes are available as a single ZIP file, or by chapter:

Chapter 1 - Dynamic Phenomena in Cell

Fig. 1.8	ExponentialDecayOne.ode - Models simple exponential decay using a first order decay. The only adjustable parameter is the decay rate.
Fig. 1.10AB	ExponentialDecayTwo.ode - Models simple exponential decay using a first order decay. Parameters include the decay rate and the asymptotic value.

Chapter 2 - Voltage Gated Ionic Currents

Fig. 2.6A	EquilibriumActivationGate.ode - The equilibrium open fraction of voltage-dependent (activation) gate.
Fig. 2.4???	HodgkinHuxley.ode - The implementation of the classic Hodgkin-Huxley equations for the squid giant axon.
Fig. 2.6AB	Plotting.ode - Demonstrates how to plot functions using XppAut/WinnPP. Uses a dummy differential equation to plot the auxiliary function.
Fig. 2.9ABCD Fig. 2.10AB Fig. 2.11AB Fig. 2.12A	MorrisLecarOne.ode - The Morris-Lecar model of the barnacle muscle.
Fig. 2.12B Ex. 2.8 Ex. 2.9 Ex. 2.10	MorrisLecarTwo.ode - The Morris-Lecar model of the barnacle muscle.

Chapter 3 - Transporters and Pumps

Fig. 3.12B

NaGlucoseFiveState.ode - the five-state Na/Glucose transporter, as modeled by Parent et al. 1992.

Chapter 4 - Reduction of Scale

Fig. 4.3	LTypeCaChannel.ode - Full and rapid model of L-type calcium channel.
Fig. 4.11	DeYoungKeizerSS.ode - Steady state open probability for De Young-Keizer IP3 receptor model

Chapter 5 - Whole Cell Models

Fig. 5.6A	KeizerLevine.ode - The Keizer-Levine RyR model.
Fig. 5.6B	KeizerLevineSS.ode - The steady-state Keizer-Levine RyR model.
Fig. 5.7A	KeizerLevineCC.ode - The closed-cell Keizer-Levine model.
Fig. 5.8 Fig. 5.9 Fig. 5.10	KeizerLevineOC.ode - The reduced, open-cell Keizer-Levine model.
Fig. 5.12 Fig. 5.13	LiRinzelCC.ode - The closed-cell Li-Rinzel gonadotroph model.
Fig. 5.14 Fig. 5.15	LiRinzelOC.ode - The open-cell Li-Rinzel gonadotroph model.
Fig. 5.16 Fig. 5.17	LiRinzelMorrisLecar.ode - The Li-Rinzel/Morris-Lecar gonadotroph model.
Fig. 5.19 Fig. 5.20	ChayKeizer.ode - The Chay-Keizer b-cell bursting model.
Fig. 5.21	ChayKeizerER.ode - The Chay-Keizer b-cell bursting model with ER.
???	km.ode - Used to compute ex5.11

Chapter 6 - Intercellular Communication

???	mlcdwrk.ode - Used to compute figure 6.9 A simple model for coincidence detection. A Morris-Lecar cell receives two just-subthreshold inputs that are identical and excitatory. The goal is to study the changes in the output signal as a function of the time difference between the two inputs.
???	mlds2cellwrk.ode - Used to compute figures 6.10 A simple model for motion and directionally. A selective Morris-Lecar cell (1st layer) receives two separate inputs, one inhibitory and one excitatory, temporally offset. A 2nd-layer ML cell receives same excitatory input as 1st-layer but also gets inhibitory input from 1st-layer neuron. The goal is to study the changes in the output signal as a function of the time difference between the two layer 1 inputs.
???	mlexcitwrk.ode - Used to compute figures 6.2, 6.6 Morris-Lecar pair with mutual excitation. Initial conditions lead to out-of-phase behavior when cells are uncoupled, before coupling is turned on at t=ton. Cells oscillate in synchrony for fast synapses: alpha=3, beta=1. Cells oscillate in antiphase for slow synapses: alpha=3, beta=0.1.
???	mlgapwrk.ode - Used to compute figure 6.3 Gap-junction coupled cells. Morris-Lecar dynamics with modified parameters. Notably: vc=-5, vd=10, phi=0.5 (originally: 2, 30, 0.04, respectively) Use weak gc (=1) for antiphase and strong gc (=2) for inphase oscillations.
???	mlinhwrk.ode - Used to compute figures 6.7 Morris-Lecar pair with mutual inhibition. Initial conditions lead to out-of-phase behavior when cells are coupled with fast synapses: alpha=3, beta=1 for t<tbeta and in-phase behavior when slow synapses: alpha=3, beta=0.1 for t>tbeta

Chapter 7 - Spatial Modeling

Fig. 7.6	DiffusionEquation.ode - Numerical solution of the diffusion equation in one dimension
Fig. 7.8	BistableEquation.ode - Numerical solution of the bistable equation in one dimension.
P. 192-4	FitzHughNagumoSpatial.ode - The FitzHugh-Nagumo traveling wave model.

Chapter 8 - Modeling Intracellular Calcium Waves and Sparks

???	Heteroclinic.ode -
???	RateFunction.ode -
Fig. 8.4A	TravelingFront.ode -
Fig. 8.7A	TravelingPulse.ode / TravelingPulse.set -
Fig. 8.10A	KinematicWave.ode -
Fig. 8.12A	FDFContinuous.ode - Used to compute figures ??, ??
Fig. 8.12B	FDFSaltatory.ode -
???	WCaBistable.ode - WCaBistable.ode.set
???	WCaExcitable.ode - WCaExcitable.ode.set
???	WCaOscillatory.ode - WCaOscillatory.ode.set

Chapter 9 - Biochemical Oscillations

Fig. 9.6	SubstrateDepletion.ode / SubstrateDepletion.set - The substrate-depletion oscillator.
Fig. 9.7	ActivatorInhibitor.ode / ActivatorInhibitor.set - The activator-inhibitor oscillator.
Sec. 9.4.3	Goodwin.ode - The Goodwin model in Section 9.4.3.
Sec. 9.4.3	BlissPainterMarr.ode - The Bliss-Painter-Marr model in Section 9.4.3.
Sec. 9.5.2	DiscreteTimeLag.ode - The discrete time lag model in Section 9.5.2. This model does NOT work.
Ex. 9.4	Keller.ode / Keller.set - The Keller gene expression model in Exercise 9.4.
Ex. 9.10	Goldbeter.ode / Goldbeter_B(t).ode / Goldbeter_B(t).set - The Goldbeter calcium induced calcium release model in Exercise 9.10.

Chapter 10 - Cell Cycle Controls

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Chapter 11 Modeling the Stochastic Gating of Ion Channels

Fig. 11.3	Markov.ode - A two-state Markov model.
???	MeanVarParabola.ode -
???	MeanVarWiener.ode -
Fig. 11.10	OpenFractionLangevin.ode - The Langevin formulation of an ensemble of two-state channels.
Fig. 11.17	StochasticMorrisLecarLangevin.ode - The Langevin formulation of the stochastic Morris-Lecar model.
Fig. 11.11AB	TwoStateFluctVolt.ode - A model for membrane voltage fluctuations due to the stochastic gating of one channel. Parameters do not reflect the exact parameters used in Fig. 11.11.
Fig. 11.11C	TwentyStateFluctVolt.ode - A model for membrane voltage fluctuations due to the stochastic gating of twenty channels. Parameters do not reflect the exact parameters used in Fig. 11.11.
???	TwoStateMarkov.ode -

Chapter 12 - Molecular Motors: Theory

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Chapter 13 - Molecular Motors: Examples

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Appendix A - Qualitative Analysis of Differential Equations

???	ExponentialDecayOne.ode - Used to compute figures ??, ?? This program models simple exponential decay using a first order decay. The only adjustable parameter is the decay rate.
???	ExponentialDecayTwo.ode - Used to computer figures ??, ?? This program models simple exponential decay using a first order decay. Parameters include the decay rate and the asymptotic value.

Appendix B - Solving and Analyzing Dynamical Systems using XPPAUT

Sec. B.1.1	Linear system Eq. B.1
Fig. B.9 Fig. B.10 Fig. B.11 Fig. B.12 Fig. B.13 Fig. B.14	FitzHughNagumo.ode - The FitzHugh-Nagumo model Eq. B.2.
Fig. B.15	FitzHughNagumoSpatial.ode - The FitzHugh-Nagumo model in Sec. B.4.
Fig. B.16	Sodium channel Sec. B.5.2
Fig. B.17	Flashing ratchetSec. B.5.3

Appendix C - Numerical Algorithms

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