Titlebook: Intelligent Computing Theories and Application; 16th International C De-Shuang Huang,Kang-Hyun Jo Conference proceedings 2020 Springer Natu

reception

欢笑

poliosis

Predicting ,-, Transcription Factor Binding Sites with Deep Embedding Convolution Networkf discovery, In this paper, we propose a novel neural network based architecture i.e. eDeepCNN, combining multi-layer convolution network and embedding layer for predicting in-vitro DNA protein binding sequence. Our model fully utilize fitting capacity of deep convolution neural network and is well

amenity

Prediction of Membrane Protein Interaction Based on Deep Residual Learninger predict its spatial structure. Therefore, it is of great significance to study the interaction of membrane proteins. Currently, there is no contact method specifically for membrane protein prediction. In this paper, a membrane protein prediction tool based on deep residual learning is established

效果

GCNSP: A Novel Prediction Method of Self-Interacting Proteins Based on Graph Convolutional Networksf great significance for the exploration of new gene functions, protein function research and proteomics research. Although a large number of SIPs have been confirmed with the rapid development of high-throughput technology, the biological experimental method is still limited by blindness and high c

bibliophile

Predicting Protein-Protein Interactions from Protein Sequence Using Locality Preserving Projections ut technologies have been proposed to detect the PPIs in past decades. However, they have some drawbacks such as time-consuming and high cost, and at the same time, a high rate of false positive is also unavoidable. Hence, developing an efficient computational method for predicting PPIs is very nece

小歌剧

Mammal

者变

Yan Cui,Huacheng Gao,Rui Zhang,Yuanyuan Lu,Yuan Xue,Chun-Hou Zheng

delusion