Classic papers
Computer Simulations
Chance, B. (1943) The kinetics of the enzyme-substrate compound of peroxidase. J. Biol. Chem. 151, 553-577. PDF
The first simulation in biology was performed in 1943 long before the appearance of digital computers. Britton Chance used a differential analyzer to solve numerically a set of two differential equations to analyse the kinetics of horsearadish peroxidase.
Gear C. W. (1971) The automatic integration of ordinary differential equations. Commun. ACM 14, 176-9. (Citation Classic)
This paper presents the first automatic computer code for the solution of stiff differential equations in digital computers. Stiff equations are common when modelling biological systems and result from the co-existence of processes with very different time scales. 
Mathematical Models
Duncan WG, Loomis RS, Williams WA & Hanau R. (1967) A model for simulating photosynthesis in plant communities. Hilgardia 38, 181-205. (Citation Classic)
An early work where a mathematical model was set up to predict the rate of photosynthesis from the knowledge of leaf area, leaf distribution, leaf reflectivity and transmissivity, solar elevation and brightness, skylight brightness, and the relationship between leaf illumination and photosynthetic rate. Experimental measurements obtained subsquently revealed that the model was accurate.
Sel'kov E. E. (1968) Self-oscillations in glycolysis. 1. A simple single-frequency model. Eur. J. Biochem. 4, 79-86.
A simple mathematical model of glycolysis was set up. It predicted that glycolytic oscillations (observed experimentally in 1964 by Britton Chance et al.) could be triggered if glucose is injected with a constant rate near a critical bifurcation value.
Wilkinson G R & Shand D G. (1975) A physiological approach to hepatic drug clearance. Clin. Pharmacol. Ther. 18 377-90. (Citation Classic)
This paper described a pharmacokinetic model for the hepatic elimination of drugs based on the relationship between the involved physiological factors including the concept of "intrinsic clearance".
Reich, J.G. & Sel'kov, E.E. (1981) "Energy metabolism of the cell: A theoretical treatise" Academic Press, London.
In this book the energy metabolism of the cell is studied from a theoretical and quantiative point of view. Dozens of mathematical models are built to analyse particular aspects of the cellular energy metabolism, and ultimately an integrative, but simple, model of energy metabolism is set up. Strong emphasis is given to time-scale analysis and how stoichiometry and moiety conservation of metabolic pathways have strong implications for their regulation.
Biochemical Systems Theory
Savageau, M.A. (1969) Biochemical systems analysis. I. Some mathematical properties of the rate law for the component enzymatic reactions. J. Theor. Biol. 25, 365-369.
Savageau, M.A. (1969) Biochemical systems analysis. II. The steady-state solutions for an n-pool system using a power-law approximation J. Theor. Biol. 25, 370-379.
Savageau, M.A. (1970) Biochemical systems analysis. III. Dynamic solutions using a power-law approximation J. Theor. Biol. 26, 215-226.
Biochemical Systems Theory (BST) was developed by Mike Savageau in the late 60s. A major advantage of the BST approach is that knowledge of the exact mechanism of each reaction is not required to set up equations, models are designed based solely on the identity of the reactants and their reactional and regulatory interconnections. The result is a canonical form using power-law representations (either S-systems or Generalized Mass Action (GMA). Useful links:
A simple but rigorous introduction to BST.
A good page on BST.
a MatLab toolbox under development to implement BST.
Metabolic Control Analysis
Kacser, H. & Burns, J.A. (1973) The control of flux. Symp. Soc. Exp. Biol. 27, 65-107. An updated reprint can be found in Biochem. Soc. Trans. 23, 341-366.
Heinrich, R. & Rapoport, T.A. (1974) A linear steady-state treatment of enzymatic chains. General properties, control and effector strength. Eur. J. Biochem. 42, 89-95.
Metabolic control analysis (MCA) was developed in the early 70s and its classic result is that there is no rate-limiting step in a biochemical pathway, and instead control of the pathway flux is distributed among all reactions of the pathway. MCA is a quantitative sensitivity analysis of fluxes and metabolite concentrations and has some aspects related with BST. Useful links:
MCA homepage dedicated to the memory of Professor Henrik Kacser.
An extensive FAQ on MCA.
GEPASI: an excellent simulation package to model biological systems (among many useful features implements MCA, but beware when implementing models with several compartments!).
An online introductory course on MCA.