Biological networks are complex and constructing dynamics for large systems can prove difficult. We explore utilizing data-driven techniques to infer the underlying dynamics of a biological network. We will discuss methods which infer dynamics with polynomial interactions (i.e. Mass-Action systems) as well as those with rational functions in the dynamics (i.e. Michaelis–Menten type).
