This dissertation presents the first photoacoustic study of single cells using ultra-high frequencies (UHF, over 100 MHz). At these frequencies, unique features occur in the photoacoustic signal spectrum which depend on the cell size, morphology and structure. A finite element model (FEM) was developed to simulate the photoacoustic signals from ideal spherical droplets containing a perfluorocarbon liquid and optically absorbing nanoparticles. The model was applied to droplets in suspension and on a boundary to examine how the photoacoustic spectrum varies with droplet size and configuration, and compared to measurements using a 375 MHz transducer. Good agreement in the spectral features between the measured values and the FEM and analytical solution were observed. For the droplet on a boundary, additional spectral features were observed there were correctly predicted by the FEM, but not the analytical solution. The FEM could be applied to situations where the analytical model cannot be used, such as the asymmetric shape of red blood cells (RBCs). Measurements of single RBCs were then compared to the FEM. The frequency location of the spectral minima shifted to higher frequencies as the RBC rotated from a vertical to horizontal orientation. The spectral minima shifted to lower frequencies as the RBC swelled from the normal biconcave shape to a spherical morphology. Healthy RBCs were differentiated from spherocytes, echinocytes and swollen RBCs using changes in the photoacoustic spectrum (p<0.001). These results suggest that the photoacoustic spectrum can be used to classify RBCs according to their shape and pathology. Classification of cells using the photoacoustic spectral features was applied to measurements of blood cells and circulating tumor cells (CTCs) such as melanoma and acute myeloid leukemia (AML) cells. Measurements of 89 cells showed that variations in the spectrum and signal amplitude could be used to identify and differentiate melanoma and AML cells from RBCs, thus identifying foreign cells in the bloodstream. This dissertation investigates how UHF photoacoustics can be used to identify and classify cells and particles in a sample using their photoacoustic spectra, with the end goal of using these methods to identify cell pathology and detect CTCs clinically.