We report on factors that affect DNA hybridization detection using ion-sensitive field-effect transistors (ISFETs). Signal generation at the interface between the transistor and immobilized biomolecules is widely ascribed to unscreened molecular charges causing a shift in surface potential and hence the transistor output current. Traditionally, the interaction between DNA and the dielectric or metal sensing interface is modeled by treating the molecular layer as a sheet charge and the ionic profile with a Poisson-Boltzmann distribution. The surface potential under this scenario is described by the Graham equation. This approximation, however, often fails to explain large hybridization signals on the order of tens of mV. More realistic descriptions of the DNA-transistor interface which include factors such as ion permeation, exclusion, and packing constraints have been proposed with little or no corroboration against experimental findings. In this study, we examine such physical models by their assumptions, range of validity, and limitations. We compare simulations against experiments performed on electrolyte-oxide-semiconductor capacitors and foundry-ready floating-gate ISFETs. We find that with weakly charged interfaces (i.e., low intrinsic interface charge), pertinent to the surfaces used in this study, the best agreement between theory and experiment exists when ions are completely excluded from the DNA layer. The influence of various factors such as bulk pH, background salinity, chemical reactivity of surface groups, target molecule concentration, and surface coatings on signal generation is studied. Furthermore, in order to overcome Debye screening limited detection, we suggest two signal enhancement strategies. We first describe frequency domain biosensing, highlighting the ability to sort short DNA strands based on molecular length, and then describe DNA biosensing in multielectrolytes comprising trace amounts of higher-valency salt in a background of monovalent saline. Our study provides guidelines for optimized interface design, signal enhancement, and the interpretation of FET-based biosensor signals.