Performance improvement for a 2D convolutional neural network by using SSC encoding on protein–protein interaction tasks

Background: The interactions of proteins are determined by their sequences and affect the regulation of the cell cycle, signal transduction and metabolism, which is of extraordinary significance to modern proteomics research. Despite advances in experimental technology, it is still expensive, labori...

Full description

Bibliographic Details
Main Authors:	Chen, X. (Author), Dai, Z. (Author), Huang, Q. (Author), Li, Z. (Author), Ma, Y. (Author), Wang, Y. (Author), Zhang, Y. (Author), Zou, X. (Author)
Format:	Article
Language:	English
Published:	BioMed Central Ltd 2021
Subjects:	amino acid sequence Amino Acid Sequence article biology Computational Biology Convolution convolutional neural network Convolutional neural networks deep learning Deep learning Encoding (symbols) Encoding informations extraction Forecasting High performance processors Learning systems molecular docking Molecular Docking Simulation Molecular modeling Network coding Neural Networks, Computer prediction Prediction accuracy Protein interaction protein protein interaction Protein sequences Proteins Proteomics Proteomics research Sequence statistics Signal transduction software Software State assignment Statistical information
Online Access:	View Fulltext in Publisher

Internet

View Fulltext in Publisher

Performance improvement for a 2D convolutional neural network by using SSC encoding on protein–protein interaction tasks

Internet

Similar Items