Table 2.

Description of the features used in the experiment

Type	Feature	Feature description	Tools
Inherent feature	CDS size	Gene coding sequence length	Python 3.7
	Protein size	Amino acid length
CodonW	T3s, C3s,	Relative synonymous codon usage of	CodonW [43]
	A3s, G3s	T, C, A, and G at the 3rd position
	CAI	Codon adaptation index
	CBI	Codon bias index
	Fop	Frequency of optimal codons
	Nc	Effective number of codons
	GC3s	GC of silent 3rd codon posit
	GC	GC content of gene
	L_sym	Number of synonymous codons
	Gravy	Hydrophobicity of protein
	Aromo	Aromaticity of protein
Amino acid usage frequency	Amino acid	A,R,D,C,Q,E,G,H,I,N,L,K,M,F,P,S,T,W,Y,V	Python 3.7
	Rare_aa_ratio	Frequency of rare amino acids
	Close_aa_ratio	Number of codons 3rd stop codon mutation
Physicochemical properties of amino acids	M_weight	Molecular weight	Pepstats [44]
	I_Point	Isoelectric point
	Tiny	(A + C + G + S + T)
	Small	(A + B + C + D + G + N + P + S + T + V)
	Aliphatic	(A + I + L + V)
	Aromatic	(F + H + W + Y)
	Nonpolar	(A + C + F + G + I + L + M + P + V + W + Y)
	Polar	(D + E + H + K + N + Q + R + S + T + Z)
	Charged	(B + D + E + H + K + R + Z)
	Basic	(H + K + R)
	Acidic	(B + D + E + Z)
	A_R Weight	Average Residue Weight
Transmembrane helix	ExpAA	Exp number of AAs in TMHs	TMHMM3 [45]
	First60	Exp number, first 60 AAs
	PredHel	Total prob of N-in
Hurst	Hurst	Hurst index	R package [46]
Information Entropy	Shannon Entropy	quantifies the average information content of the gene sequence from the distribution of symbols	Python 3.7
	Mutual Information	measures the information shared by two random variables	Python 3.7
	Kullback–Leibler divergence	measure the similarity of two probability distributions	Python 3.7
	Cross Entropy	measure the difference information between two probability distributions	Python 3.7