## 3 Feature Encoding Methods
### Physicochemical-Based Methods
**GTPC**  
Grouped Tri-Peptide Composition (GTPC) is an advanced feature extraction method used in bioinformatics to analyse peptide sequences by considering the composition of tripeptides (triplets of consecutive amino acids) grouped by their physicochemical properties. This method extends the concept of grouped dipeptide composition (GDC) to tripeptides, providing an even more detailed and nuanced representation of the sequence [113]. Amino acids are first grouped on the basis of their physicochemical properties, such ashydrophobicity, charge, size, or polarity. For example, hydrophobic amino acids might be grouped together, and charged amino acids might form another group. Tripeptides are then formed by considering triplets of consecutive amino acids within these groups. For example, if we have two groups, hydrophobic (H) and charged (C), the possible tripeptide groups could be HHH, HHC, HCH, HCC, CHH, CHC, CCH, and CCC. For each tripeptide group, the GTPC algorithm calculates the frequency or proportion of that tripeptide in the peptide sequence. For example, if a peptide sequence contains ten tripeptides and three of them are from the hydrophobic-hydrophobic (HHH) group, the composition of the HHH group would be 30%. **EGAAC**  
The enhanced group amino acid composition (EGAAC) is an advanced feature extraction method that builds upon the traditional GAAC by incorporating additional layers of information and complexity [114]. This method aims to provide a more comprehensive and nuanced representation of peptide sequences by considering not only the physicochemical properties of amino acids but also their spatial distribution and interaction patterns. Amino acids are categorised into groups on the basis of their physicochemical properties, such as hydrophobicity, charge, size, and polarity. The EGAAC method calculates the frequency or proportion of each amino acid group in the peptide sequence, similar to GAAC. However, it also considers the distribution and interaction patterns of these groups within the sequence. The method can analyse the distribution of amino acid groups along a sequence, identifying patterns such as clustering or periodicity. EGAAC can capture the interactions between different groups, such as transitions from one group to another, which can provide insights into the structural and functional properties of the peptide. **CTD**  
The composition/transition/distribution (CTD) algorithm is a widely used feature extraction method for AMPs [115; 116]. It captures the essential characteristics of a peptide sequence by analysing the composition, transition, and distribution of its constituent amino acids. Composition means that the algorithm calculates the frequency of each amino acid in the peptide sequence. For example, if a peptide contains ten amino acids and three of them are lysine (K), the composition of lysine would be 30%. This provides a snapshot of the overall makeup of the peptide, highlighting the prevalence of specific amino acids that might be crucial for its antimicrobial activity. Transition refers to the frequency of changes between different types of amino acids along a sequence. For example, it measures how often a hydrophobic amino acid is followed by a hydrophilic amino acid or vice versa. This aspect is important because the spatial arrangement and interaction between different types of amino acids can influence a peptide's structure and its ability to interact with bacterial membranes. Distribution:  
Distribution examines the spatial arrangement of specific amino acids or groups of amino acids within the peptide. It identifies patterns such as clustering of certain amino acids at the N-terminus, C-terminus, or throughout the sequence. This is significant because the position of key residues can affect the peptide's stability, ability to penetrate bacterial membranes, and overall bioactivity. By combining these three components, the CTD algorithm provides a comprehensive representation of a peptide's characteristics.