Table 3.

Features employed by machine learning-based B-cell epitope prediction tools.

Machine learning tool	Feature types	Year	Ref.
ABCpred	Amino acid composition and sequence	2006	(29)
COBEPRO	Similarity to other epitopes	2009	(94)
EPITOPIA	Amino acid preference, secondary structure preference, surface accessibility, surface structure, evolution rate, polarity scale, flexibility scale, antigenicity scale, hydrophilicity scale	2009	(37)
CBTOPE	Amino acid composition, polarity, flexibility, antigenicity, hydrophobicity, sequence, similarity to other epitopes	2010	(36)
LBtope	Amino acid composition, sequence, similarity to other epitopes, variable epitope length control	2013	(27)
SEPPA 1.0 (*) SEPPA 2.0 (**) SEPPA 3.0 (***)	Amino acid propensity*, sequence combined with structure*, solvent accessible surface areas*, antigenicity combined with structure **, glycosylation combined with structure***	2019	(95–97)
EPCES/EPSVR	Amino acid, side-chain energy score, surface exposure, antigenicity combined with surface structure, and secondary structure	2020	(24)
SCANNET	Amino acid composition, secondary structure, accessible surface area, coordination number (van der Waals interaction), 2D solvent exposure, backbone and sidechain depth (distance from surface), surface convexity index, amino acid conservation	2022	(32)

Different versions of the SEPPA program have new features added to them, features with '*' were first included in SEPPA 1.0, while features with '**' and '***' were first included in SEPPA 2.0 and SEPPA3.0 respectively.