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Enzymes are proteins that catalyze bio-chemical reactions in different ways and play important roles in metabolic pathways. The exponential rise in sequences of new enzymes has necessitated developing methods that accurately predict their function. To address this problem, approaches that cluster enzymes based on their sequence and structural similarity have been applied, but are known to fail for...
Inspired by complementary strategies, a hybrid supervised artificial immune classifier is put forward, which is on the basis of the clonal selection principle, and combined with the fuzzy c-means clustering (FCM) algorithm and information entropy theory. The new approach uses a weighted Euclidean distance based dissimilarity measure during all affinity evaluations. With the help of FCM clustering,...
Inspired by complementary strategies, a hybrid supervised artificial immune classifier is put forward, which is on the basis of the clonal selection principle, and combined with the Fuzzy C-Means clustering (FCM) algorithm. With the help of FCM clustering, the initial antibodies that image features of data set are extracted effectively, and then a clonal selection algorithm named CLONALG is adopted...
In genetic programming (GP), evolving tree nodes separately would reduce the huge solution space. However, tree nodes are highly interdependent with respect to their fitness. In this paper, we propose a new GP framework, namely, instruction-matrix (IM)-based GP (IMGP), to handle their interactions. IMGP maintains an IM to evolve tree nodes and subtrees separately. IMGP extracts program trees from...
In the last decade, the efforts of spoken language processing have achieved significant advances, however, the work with emotional recognition has not progressed so far, and can only achieve 50% to 60% in accuracy. This is because a majority of researchers in this field have focused on the synthesis of emotional speech rather than focusing on automating human emotion recognition. Many research groups...
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