reception 发表于 2025-3-23 11:40:10
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http://reply.papertrans.cn/47/4695/469486/469486_12.pngpoliosis 发表于 2025-3-23 21:27:19
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 wellamenity 发表于 2025-3-24 00:00:09
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 发表于 2025-3-24 04:15:03
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 cbibliophile 发表于 2025-3-24 06:34:26
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 发表于 2025-3-24 12:11:12
http://reply.papertrans.cn/47/4695/469486/469486_17.pngMammal 发表于 2025-3-24 15:55:02
http://reply.papertrans.cn/47/4695/469486/469486_18.png者变 发表于 2025-3-24 22:11:25
Yan Cui,Huacheng Gao,Rui Zhang,Yuanyuan Lu,Yuan Xue,Chun-Hou Zhengdelusion 发表于 2025-3-24 23:39:36
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