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Per target secondary structure (a) and four-class solvent accessibility (b) accuracy for predictions using one hot encoding, a number of rawMSA networks, and a classical PSSM network trained and tested on the same dataset.

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posted on 2019-08-15, 17:41 authored by Claudio Mirabello, Björn Wallner

One hot100 skips the rawMSA embedding step and encodes the alignments using one hot encoding, limited to the top100 alignments for memory reasons. Four different rawMSA networks are tested at variable MSA depths, using top 100, 200, 500 or 1000 alignments from the MSAs as input to the SS-RSA network. The average accuracies are shown as red squares.

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