title: Pseudo nucleotide composition or PseKNC: an effective formulation for analyzing genomic sequences.
abstract: With the avalanche of DNA/RNA sequences generated in the post-genomic age, it is urgent to develop automated methods for analyzing the relationship between the sequences and their functions. Towards this goal, a series of sequence-based methods have been proposed and applied to analyze various character-unknown DNA/RNA sequences in order for in-depth understanding their action mechanisms and processes. Compared with the classical sequence-based methods, the pseudo nucleotide composition or PseKNC approach developed very recently has the following advantages: (1) it can convert length-different DNA/RNA sequences into dimension-fixed digital vectors that can be directly handled by all the existing machine-learning algorithms or operation engines; (2) it can contain the desired features and properties according to the selection or definition of users; (3) it can cover considerable sequence pattern information, both local and global. This minireview is focused on the concept of pseudo nucleotide composition, its development and applications.
authors.affiliation: Department of Physics, School of Sciences, and Center for Genomics and Computational Biology, Hebei United University, Tangshan 063000, China. chenweiimu@gmail.com wchen@gordonlifescience.org.
authors.forename: Wei
authors.initials: W
authors.lastname: Chen
authors.forename: Hao
authors.initials: H
authors.lastname: Lin
authors.forename: Kuo-Chen
authors.initials: KC
authors.lastname: Chou
mesh_terms: D000465:Algorithms; D001482:Base Composition; D019295:Computational Biology / Q000379:methods*; D015894:Genome, Human; D006801:Humans; D008957:Models, Genetic; D017422:Sequence Analysis, DNA / Q000379:methods*; D017423:Sequence Analysis, RNA / Q000379:methods*