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Table 1 Features calculated for motifs in the metamatti classifier

From: Metamotifs - a generative model for building families of nucleotide position weight matrices



Maximum metamotif hit scores with all of the familial metamotifs

Motifs were scanned with all input metamotifs and the optimal score was chosen. Both familially discovered and models discovered.

Per-column average entropy

Average Shannon entropy of columns.

MLE Dirichlet parameters

A maximum likelihood Dirichlet distribution is estimated as described in [42] and the parameters of this distribution are used as features (α A ,α G ,α C ,α T ).

Symmetric Dirichlet background parameters

A symmetric Dirichlet distribution is estimated as described above.