Titlebook: Advanced Intelligent Computing in Bioinformatics; 20th International C De-Shuang Huang,Yijie Pan,Qinhu Zhang Conference proceedings 2024 Th

WAIL

Fully Convolutional Neural Network for Predicting Cancer-Specific CircRNA-MiRNA Interaction SitescRNAs regulate gene expression by adsorbing miRNAs and acting as ‘sponges’. Dysregulation of miRNAs has been observed in various cancer tissues, and co-expression of circRNAs with miRNAs has been noted in many cancer tissues. The co-expression of miRNAs with circRNAs may play an important role in re

jagged

GSDPI: An Integrated Feature Extraction Framework for Predicting Novel Drug-Protein Interactionelopment processes. However, existing DPIs prediction models still encounter challenges in efficiently extracting node features from complex networks. This paper proposed a novel DPIs prediction framework named GSDPI, in which graph neural networks (GNN) were employed to aggregate neighborhood infor

companion

情感脆弱

HyperCPI: A Novel Method Based on Hypergraph for Compound Protein Interaction Prediction with Good Gowever, existing deep learning approaches face a challenge due to the lack of representations for non-pairwise relations and substructures in compounds, leading to limited performance and poor generalization ability. To address this challenge, a novel method named HyperCPI is proposed in this study.

致敬

iEMNN: An Iterative Integration Method for Single-Cell Transcriptomic Data Based on Network Similarits arise from non-biological variations such as different sequencing batches, sequencing protocols, sequencing depths, and so on. Batch effects introduce systematic biases and confound biological variations of interest, which have a detrimental impact on the validity of study findings. Eliminating b

forbid

不自然

JAUNT

河潭

CDDTR: Cross-Domain Autoencoders for Predicting Cell Type Specific Drug-Induced Transcriptional Respextracted by 10-fold cross-validation have a 0.663 PCC, revealing the competence of CDDTR to predict the cross-cell type responses. By integrating perturbations from multiple cell lines and incorporating pre-training, the predictive performance of CDDTR can be further improved. Source code is availa

不朽中国