Anticancer peptides (ACPs) are being widely studied as potential peptide-based anticancer agents because of their ability to interact selectively with cancer cells. Despite this promise, computational identification of ACPs and prediction of their cancer-type activity remain difficult, mainly because available peptide...
A novel BAN-SDBPred (Bilinear Attention Network for Single and Double Stranded DNA-Binding Protein Prediction) method, which outperforms the existing predictors in terms of all performance measures on the training and independent test data and expects that BAN-SDBPred outperforms the existing predictors in terms of all...
K. Arshad, Muhammad Arif, A. Worachartcheewan et al.· ACS Omega· 0 citations
The enzyme kinetic parameters, including the turnover number, Michaelis constant, and inhibition constant, are key metrics for assessing catalytic performance. Although deep learning models have recently incorporated multimodal information from enzymes and substrates to predict these parameters, several obstacles still...
Cheng-Hao Zhu, Wei-Ping Ding, Wei Zhang et al.· Journal of Chemical Informat...· 0 citations
Deep3MVPF, a multiview deep learning framework for 3'UTR stability prediction and m6A site identification, integrates a multiscale convolutional neural network, a k-mer de Bruijn graph neural network, and a secondary-structure graph neural network to jointly model sequence, topological, and structural representations.
Jun-Yi Liu, Qi Zhang, Jiangning Song et al.· Journal of Chemical Informat...· 0 citations
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