Table 7.

Thirty-six BNLMs based on word embedding

Category	Algorithm	Model	Description
DNA	word2vec	Kmer2vec	Learn word representations via word2vec model (53)
		RevKmer2vec
		Mismatch2vec
		Subsequence2vec
	GloVe	Kmer-GloVe	Learn word representations via Glove model (54)
		RevKmer-GloVe
		Mismatch-GloVe
		Subsequence-GloVe
	fastText	Kmer-fastText	Learn word representations via fastText model (55)
		RevKmer-fastText
		Mismatch-fastText
		Subsequence-fastText
RNA	word2vec	Kmer2vec	Learn word representations via word2vec model (53)
		Mismatch2vec
		Subsequence2vec
	GloVe	Kmer-GloVe	Learn word representations via Glove model (54)
		Mismatch-GloVe
		Subsequence-GloVe
	fastText	Kmer-fastText	Learn word representations via fastText model (55)
		Mismatch-fastText
		Subsequence-fastText
Protein	word2vec	Kmer2vec	Learn word representations via word2vec model (53)
		Mismatch2vec
		DR2vec
		Top-n-gram2vec
		DT2vec
	GloVe	Kmer-Glove	Learn word representations via glove model (54)
		Mismatch-Glove
		DR-Glove
		Top-n-gram-Glove
		DT-Glove
	fastText	Kmer-fastText	Learn word representations via fastText model (55)
		Mismatch-fastText
		DR-fastText
		Top-n-gram-fastText
		DT-fastText