Encodings and models for antimicrobial peptide classification for multi-resistant pathogens

Table 5 Different types of string kernels (see Table 1 for further details)

Encoding	Description	Summary	Used in	Used along with
Spectrum Kernel	generates all possible subsequences of length k and counts the occurrences of these k-mers	Density: - Information: -	[112]
Mismatch Kernel	considers a certain distance, hence mismatches, between two k-mers	Density: - Information: o	[114,115,116]	General Structure
Distant Segment Kernel	allows a gap between two k-mers	Density: - Information: o	[118]
Local Alignment Kernel	obtained from local alignment scores	Density: + Information: o	[119]	Spectrum Kernel, Mismatch Subsequence Kernel
Subsequence Kernel	measures sequence similarity, gaps within k-mers are taken into account	Density: + Information: o	[119]	Frequency of Amino Acid Pairs
Frequency of Amino Acid Pairs	similar to dipeptide composition	Density: - Information: o	[119]
String Kernels + Physicochemical Properties	optimization of existing string kernels such that these involve physicochemical properties	Density: + Information: +	[120]	Physicochemical Properties
Generic String Kernel	string kernel with physicochemical properties and penalization of non adjacent segments	Density: + Information: +	[121, 122]

ISSN: 1756-0381