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Field guide to functions for biologists Functions and data can be explored at http://www.shodor.org/interactivate/activities/MultiFunctionDataFly/ Exponential – Formula for representing the change in a quantity over time when the rate of change depends on the amount. Examples include: Radioactive decay – time course of amount of starting material shows exponential decay First-order rate law phenomena where change ~ k*A = rate constant * amount Unconstrained growth – in population, economy, … Decay At=A0e-kt : Where At is the amount of decaying substance A at time t, A0 is the starting amount at time = 0, and k is the rate constant governing the decay = the proportion of the substance that is lost over some time interval In function flyer : f(x) = 50*exp(-0.15*x) Growth At=A0ekt : Where things are the same as in the decay case, except that, with a positive exponent, substance is being added as time elapses Rectangular hyperbola – Formula for representing systems where there is a case of diminishing returns, in other words increasing the input leads to less and less increase in the output. Examples include: Ligand binding – plot of site occupancy as a function of ligand concentration o Y = [L] / (KD + [L]), where Y is fractional binding site occupancy, [L] is ligand concetration, and KD is the dissociation constant or concentration at which half of the binding sites are occupied Rate of enzymatic reaction – rate of production as a function of substrate concentration o v = vMax * [S] / (KM +[S]), where v is the reaction velocity and vMax is the maximum velocity (= turnover number times # of binding sites times enzyme concentration), [S] is substrate concentration, and KM is the Michaelis constant for quasi-equilibrium substrate binding Spring loading – deformation as a function of force applied Vehicle velocity – speed as a function of fuel consumption rate, or as a function of engine power delivered to the wheels Capacitor charging – charge on capacitor as a function of applied voltage o How would the relationship between current through a resistor versus applied potential differ? Filtration – rate of flow through filter as a function of pressure (maybe this isn’t as limited (this is more of a resistor than a capacitor Function flyer version of equation f(x) = 1*x/(50+x) set x-axis 0 to 100, y-axis 0 to 5 Sigmoidal function – Can represent a combination of an exponential unconstrained growth at low densities followed by an approach toward a limited carrying capacity at high densities Hill equation – occupancy of allosterically coupled binding sites o f(x) = xn / (Kd + xn) , where x is the ligand concentration, f(x) is the fractional occupancy of the binding sites, and n is the Hill coefficient, for which a positive value indicates positive cooperativity (such that binding at one site increases affinity at the other sites), and negative values indicate negative cooperativity. The upper limit of the absolute value of the coefficient is the number of binding sites Logistic - f(t) = 1 / (1 + e-t) Gompertz - f(t) = aebe^ct : may possess asymmetrical approach to its two asymptotes, with the lower asymptote approached much more slowly than upper Linear – Represents situations where there is a direct dependence between parameters in a system. The scaling factor, or slope, may be positive or negative. Quadratic – two parameterizations, one that is mathematically easy to derive, the other that is parametrically easy to understand f(x) = ax2 + bx + c : this is the standard form 2 f(x) = a(x-h) + k : this is the vertex form where h and k are the x and y coordinates of the vertex respectively. This form is derived from the standard form by a process called completing the square. Cosine – periodic functions are extremely important for understanding cyclical phenomena, of which there are many in biology Gaussian – The normal curve. This is the most famous of the “bump-shaped” functions. Computational Mathematics Glossary Differentiation Integration Laplace transformation Series expansion