Research Article
Prediction Protein-Protein Interactions with LSTM
@INPROCEEDINGS{10.1007/978-3-030-97124-3_41, author={Zheng Tao and Jiahao Yao and Chao Yuan and Ning Zhao and Bin Yang and Baitong Chen and Wenzheng Bao}, title={Prediction Protein-Protein Interactions with LSTM}, proceedings={Simulation Tools and Techniques. 13th EAI International Conference, SIMUtools 2021, Virtual Event, November 5-6, 2021, Proceedings}, proceedings_a={SIMUTOOLS}, year={2022}, month={3}, keywords={Deep learning Protein-protein interaction LSTM}, doi={10.1007/978-3-030-97124-3_41} }- Zheng Tao
Jiahao Yao
Chao Yuan
Ning Zhao
Bin Yang
Baitong Chen
Wenzheng Bao
Year: 2022
Prediction Protein-Protein Interactions with LSTM
SIMUTOOLS
Springer
DOI: 10.1007/978-3-030-97124-3_41
Abstract
As the basis and key of cell activities, protein plays an important role in many life activities. Protein usually does not work alone. Under normal circumstances, most proteins perform specific functions by interacting with other proteins, and play the greatest role in life activity. The prediction of protein-protein interaction (PPI) is a very basic and important research in bioinformatics. PPI controls a large number of cell activities and is the basis of most cell activities. It provides a very important theoretical basis and support for disease prevention and treatment, and drug development. Because experimental methods are slow and expensive, methods based on machine learning are gradually being applied to PPI problems. We propose a new model called BiLSTM-RF, which can effectively predict PPI.
