Background: In the post-genome age, it is more urgent to understand the functions of
genes and proteins. Since experimental methods are usually costly and time consuming, computational
predictions are recognized as an alternative approach. In developing a predictive method for
functional genomics and proteomics, one of the most important steps is to represent biological sequences
with a fixed length numerical form, which can be further analyzed using machine learning
algorithms. Chou’s pseudo-amino acid compositions and the pseudo k-nucleotide compositions are
algorithms for this purpose.
Conclusion: Since the appearance of these algorithms, several software tools have been developed
as implementations. These software tools facilitate the application of these algorithms. As these
software tools are developed with different technologies and for different application scenarios, we
will briefly review the technical aspect of these software tools in this short review.
Keywords: Pseudo-amino acid compositions, pseudo k-nucleotide compositions, sequence representations, Chou’s five-step
rule, functional genomics, functional proteomics.
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