Force-frequency relationships of isolated cardiac myocytes show complex behaviors that are thought to be specific to both the species and the conditions associated with the experimental preparation. Ca(2+) signaling plays an important role in shaping the force-frequency relationship, and understanding the properties of the force-frequency relationship in vivo requires an understanding of Ca(2+) dynamics under physiologically relevant conditions. Ca(2+) signaling is itself a complicated process that is best understood on a quantitative level via biophysically based computational simulation. Although a large number of models are available in the literature, the models are often a conglomeration of components parameterized to data of incompatible species and/or experimental conditions. In addition, few models account for modulation of Ca(2+) dynamics via β-adrenergic and calmodulin-dependent protein kinase II (CaMKII) signaling pathways even though they are hypothesized to play an important regulatory role in vivo. Both protein-kinase-A and CaMKII are known to phosphorylate a variety of targets known to be involved in Ca(2+) signaling, but the effects of these pathways on the frequency- and inotrope-dependence of Ca(2+) dynamics are not currently well understood. In order to better understand Ca(2+) dynamics under physiological conditions relevant to rat, a previous computational model is adapted and re-parameterized to a self-consistent dataset obtained under physiological temperature and pacing frequency and updated to include β-adrenergic and CaMKII regulatory pathways. The necessity of specific effector mechanisms of these pathways in capturing inotrope- and frequency-dependence of the data is tested by attempting to fit the data while including and/or excluding those effector components. We find that: (1) β-adrenergic-mediated phosphorylation of the L-type calcium channel (LCC) (and not of phospholamban (PLB)) is sufficient to explain the inotrope-dependence; and (2) that CaMKII-mediated regulation of neither the LCC nor of PLB is required to explain the frequency-dependence of the data.