AIMC Topic: Neural Networks, Computer

Clear Filters Showing 2431 to 2440 of 31376 articles

Enhancing Predictions of Drug Solubility Through Multidimensional Structural Characterization Exploitation.

IEEE journal of biomedical and health informatics
Solubility is not only a significant physical property of molecules but also a vital factor in small-molecule drug development. Determining drug solubility demands stringent equipment, controlled environments, and substantial human and material resou...

BINDTI: A Bi-Directional Intention Network for Drug-Target Interaction Identification Based on Attention Mechanisms.

IEEE journal of biomedical and health informatics
The identification of drug-target interactions (DTIs) is an essential step in drug discovery. In vitro experimental methods are expensive, laborious, and time-consuming. Deep learning has witnessed promising progress in DTI prediction. However, how t...

DRGCL: Drug Repositioning via Semantic-Enriched Graph Contrastive Learning.

IEEE journal of biomedical and health informatics
Drug repositioning greatly reduces drug development costs and time by discovering new indications for existing drugs. With the development of technology and large-scale biological databases, computational drug repositioning has increasingly attracted...

AEGNN-M:A 3D Graph-Spatial Co-Representation Model for Molecular Property Prediction.

IEEE journal of biomedical and health informatics
Improving the drug development process can expedite the introduction of more novel drugs that cater to the demands of precision medicine. Accurately predicting molecular properties remains a fundamental challenge in drug discovery and development. Cu...

Prediction of Drug-Target Interactions With High- Quality Negative Samples and a Network-Based Deep Learning Framework.

IEEE journal of biomedical and health informatics
Identification of drug-target interactions (DTIs) plays a crucial role in drug discovery. Compared to traditional experimental methods, computer-based methods for predicting DTIs can significantly reduce the time and financial burdens of drug develop...

MDTL-ACP: Anticancer Peptides Prediction Based on Multi-Domain Transfer Learning.

IEEE journal of biomedical and health informatics
Anticancer peptides (ACPs) have emerged as one of the most promising therapeutic agents for cancer treatment. They are bioactive peptides featuring broad-spectrum activity and low drug-resistance. The discovery of ACPs via traditional biochemical met...

Decoding Drug Response With Structurized Gridding Map-Based Cell Representation.

IEEE journal of biomedical and health informatics
A thorough understanding of cell-line drug response mechanisms is crucial for drug development, repurposing, and resistance reversal. While targeted anticancer therapies have shown promise, not all cancers have well-established biomarkers to stratify...

Enhancing Drug Repositioning Through Local Interactive Learning With Bilinear Attention Networks.

IEEE journal of biomedical and health informatics
Drug repositioning has emerged as a promising strategy for identifying new therapeutic applications for existing drugs. In this study, we present DRGBCN, a novel computational method that integrates heterogeneous information through a deep bilinear a...

Optimization of enzyme-ultrasound assisted extraction from mulberries anthocyanins based on response surface methodology and deep neural networks and analysis of in vitro antioxidant activities.

Food chemistry
This study used Xinjiang native "medicinal and food dual-use" resource mulberries as raw material, and optimized the extraction process of mulberries anthocyanins by enzyme-ultrasound-assistance through the establishment of a response surface model (...

PredIDR2: Improving accuracy of protein intrinsic disorder prediction by updating deep convolutional neural network and supplementing DisProt data.

International journal of biological macromolecules
Intrinsically disordered proteins (IDPs) or regions (IDRs) are widespread in proteomes, and involved in several important biological processes and implicated in many diseases. Many computational methods for IDR prediction are being developed to decre...