The identification of regions of DNA sequences that code for proteins is one of the most fundamental applications in bioinformatics. These protein-coding regions are in contrast to other DNA regions that encode functional RNA molecules, provide structural stability of chromosomes, serve as genetic raw materials, represent molecular fossils, or have no known purpose (sometimes called “junk DNA”). A number of approaches have been suggested for differentiating between the protein-coding and non-protein-coding regions of DNA. A selection of these approaches is based on digital signal processing (DSP) techniques. These DSP techniques rely on the phenomenon that protein-coding regions have a prominent power spectrum peak at frequency f = ⅓ arising from the length of codons (three nucleic acids). This article partitions the identification of protein-coding regions into four discrete steps. Based on this partitioning, DSP techniques can be easily described and compared based on their unique implementations of the processing steps. We compare the approaches, and discuss strengths and weaknesses of each in the context of different applications. Our work provides an accessible introduction and comparative review of DSP methods for the identification of protein-coding regions. Additionally, by breaking down the approaches into four steps, we suggest new combinations that may be worthy of future study.
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