The application of digital signal processing (DSP) for the identification of the locations of hot spots in proteins is explored. DSP provides a natural framework for analyzing biologi¬cal sequence information due to the inherently discrete nature of the biological sequences. Two new techniques for the identification of the locations of hot spots in proteins are proposed. In the first technique. the short-time discrete Fourier transform (STDFT) of the protein numerical sequence is computed and its columns are multiplied by the discrete Fourier transform (DFT) coefficients. Through this technique, hot-spot locations can be clearly identified in teens of distinct peaks in the spectrogram, thus achieving good local¬ization in the amino-acid domain. Several example protein sequences are used to illustrate the technique. The second technique is based on the use of digital filters. The criteria that determine the filter type and the filter-design specifications for the application of interest are dis¬cussed. Based on this investigation, the inverse-Chebyshev UR digital filter is found to be the most suitable filter for the application. The use of zero-phase filtering to eliminate the need of computing the phase response of the digital filter is also investigated. A control parameter that can be used to distinguish the hot-spot locations on the basis of their sig¬nificance in the protein's function is introduced. The technique is then illustrated by using the same set of example protein sequences that were used for the first technique. The two techniques are then compared in teens of their computational complexity. The filter-based technique is found to be computationally much more efficient than the transform-based technique and hence it is much more suitable for a hardware implementation. The proposed techniques are capable of identifying the known hot-spot locations with good accuracy. In addition, they also identify several new hot-spot locations that may provide new insights into the working of protein molecules.