Protein coding regions are commonly diffused with non-coding regions due to 1/f background noise in such a way that a viable discernment between the two regions becomes cumbersome. Commonly employed digital signal processing methodologies lack fundamental genetic code context of nucleotides since these approaches treat DNA signal as normal digital signal that could be processed by traditional DSP tools and techniques. This paper reviews the prevailing approaches for protein coding regions identification that base on common DSP concepts and highlights the importance of genetic code context to be considered for any computational solution for protein coding regions identification. Nucleotides in a DNA signal carry certain natural characteristics i.e. presence in a distinctive triplet format, maintaining distinct structure, owning and further sharing distribution of densities in codons, fuzzy behaviors, semantic similarities, unbalanced nucleotides� distribution producing a relatively high bias for nucleotides� usage in coding regions etc. The computational solutions for protein coding regions identification that exploit these fundamental characteristic of nucleotides can significantly suppress the signal noise and hence can better contribute in identification. © 2017 Elsevier Ltd