AIMC Topic: Neural Networks, Computer

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Learning on topological surface and geometric structure for 3D molecular generation.

Nature computational science
Highly effective de novo design is a grand challenge of computer-aided drug discovery. Practical structure-specific three-dimensional molecule generations have started to emerge in recent years, but most approaches treat the target structure as a con...

Multi-Label Classification With Dual Tail-Node Augmentation for Drug Repositioning.

IEEE/ACM transactions on computational biology and bioinformatics
Due to the lengthy and costly process of new drug discovery, increasing attention has been paid to drug repositioning, i.e., identifying new drug-disease associations. Current machine learning methods for drug repositioning mainly leverage matrix fac...

PointDE: Protein Docking Evaluation Using 3D Point Cloud Neural Network.

IEEE/ACM transactions on computational biology and bioinformatics
Protein-protein interactions (PPIs) play essential roles in many vital movements and the determination of protein complex structure is helpful to discover the mechanism of PPI. Protein-protein docking is being developed to model the structure of the ...

Predicting Protein-Protein Interactions Using Sequence and Network Information via Variational Graph Autoencoder.

IEEE/ACM transactions on computational biology and bioinformatics
Protein-protein interactions (PPIs) play a critical role in the proteomics study, and a variety of computational algorithms have been developed to predict PPIs. Though effective, their performance is constrained by high false-positive and false-negat...

Prediction of Five-Year Survival Rate for Rectal Cancer Using Markov Models of Convolutional Features of RhoB Expression on Tissue Microarray.

IEEE/ACM transactions on computational biology and bioinformatics
The ability to predict survival in cancer is clinically important because the finding can help patients and physicians make optimal treatment decisions. Artificial intelligence in the context of deep learning has been increasingly realized by the inf...

CRBSP:Prediction of CircRNA-RBP Binding Sites Based on Multimodal Intermediate Fusion.

IEEE/ACM transactions on computational biology and bioinformatics
Circular RNA (CircRNA) is widely expressed and has physiological and pathological significance, regulating post-transcriptional processes via its protein-binding activity. However, whereas much work has been done on linear RNA and RNA binding protein...

Molecular Joint Representation Learning via Multi-Modal Information of SMILES and Graphs.

IEEE/ACM transactions on computational biology and bioinformatics
In recent years, artificial intelligence has played an important role on accelerating the whole process of drug discovery. Various of molecular representation schemes of different modals (e.g., textual sequence or graph) are developed. By digitally e...

Prediction of Protein-Protein Interactions Using Vision Transformer and Language Model.

IEEE/ACM transactions on computational biology and bioinformatics
The knowledge of protein-protein interaction (PPI) helps us to understand proteins' functions, the causes and growth of several diseases, and can aid in designing new drugs. The majority of existing PPI research has relied mainly on sequence-based ap...

Automatic classification of microplastics and natural organic matter mixtures using a deep learning model.

Water research
Several preprocessing procedures are required for the classification of microplastics (MPs) in aquatic systems using spectroscopic analysis. Procedures such as oxidation, which are employed to remove natural organic matter (NOM) from MPs, can be time...

Improving the Effectiveness of Eigentrust in Computing the Reputation of Social Agents in Presence of Collusion.

International journal of neural systems
The introduction of trust-based approaches in social scenarios modeled as multi-agent systems (MAS) has been recognized as a valid solution to improve the effectiveness of these communities. In fact, they make interactions taking place in social scen...