A novel conjoint triad auto covariance (CTAC) coding method for predicting protein-protein interaction based on amino acid sequence

DOI10.1016/J.MBS.2019.04.002zbMath1425.92085OpenAlexW2940565759WikidataQ91566716 ScholiaQ91566716MaRDI QIDQ2328425

Yanyan Li

Publication date: 10 October 2019

Published in: Mathematical Biosciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.mbs.2019.04.002

zbMATH Keywords

protein-protein interactiondeep neural networksconjoint triad auto covariance

Mathematics Subject Classification ID

Biochemistry, molecular biology (92C40) Protein sequences, DNA sequences (92D20) Computational methods for problems pertaining to biology (92-08)

Related Items (1)

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Uses Software

• darch
• ImageNet
• Adam
• GitHub
• PPI_SVM
• DeepPPI
• AlexNet

Cites Work

• Adaptive compressive learning for prediction of protein-protein interactions from primary sequence
• Reducing the Dimensionality of Data with Neural Networks
• Unnamed Item

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