Prescriptions

CCSynergy: an integrative deep-learning framework enabling context-aware prediction of anti-cancer drug synergy.

Combination therapy is a promising strategy for confronting the complexity of cancer. However, experimental exploration of the vast space of potential drug combinations is costly and unfeasible. Therefore, computational methods for predicting drug synergy are much needed for narrowing down this space, especially when examining new cellular contexts. Here, we thus introduce CCSynergy, a flexible, c...

A social theory-enhanced graph representation learning framework for multitask prediction of drug-drug interactions.

Current machine learning-based methods have achieved inspiring predictions in the scenarios of mono-type and multi-type drug-drug interactions (DDIs), but they all ignore enhancive and depressive pharmacological changes triggered by DDIs. In addition, these pharmacological changes are asymmetric since the roles of two drugs in an interaction are different. More importantly, these pharmacological c...

A computer vision image differential approach for automatic detection of aggressive behavior in pigs using deep learning.

Pig aggression is a major problem facing the industry as it negatively affects both the welfare and the productivity of group-housed pigs. This study ...

Use of the PARO robot as a social mediator in a sample of children with neurodevelopmental disorders and typical development.

BACKGROUND: Social robotics is a research field aimed at providing robots with skills related to social behavior and natural human interaction. Many s...

Enhancing Therapeutic Delivery Using Micro- and Nanorobots.

"The traditional way of delivering drugs has a very low efficiency. For instance, with solid tumors, drug delivery efficiency is reported to be lower ...

Perceiver CPI: a nested cross-attention network for compound-protein interaction prediction.

MOTIVATION: Compound-protein interaction (CPI) plays an essential role in drug discovery and is performed via expensive molecular docking simulations....

[Computational toxicology in drug safety research].

The progress of computational toxicology (CompTox) in drug safety research is highly anticipated. CompTox provides toxicity screening methods for drug...

State-of-the-art Application of Artificial Intelligence to Transporter-centered Functional and Pharmaceutical Research.

Protein transporters not only have essential functions in regulating the transport of endogenous substrates and remote communication between organs an...

[Development of a Medical Big Data Analysis System Utilizing Artificial Intelligence Analytics in Clinical Pharmacy].

Industrial reforms utilizing artificial intelligence (AI) have been progressing remarkably worldwide in recent years. In medical informatics, medical ...

Application of in Silico Technologies for Drug Target Discovery and Pharmacokinetic Analysis.

Drug discovery is researched and developed through many processes, but its overall success rate is extremely low, requiring a very long period of deve...

Artificial Intelligence in Drug Formulation and Development: Applications and Future Prospects.

Artificial Intelligence (AI) has emerged as a powerful tool in various domains, and the field of drug formulation and development is no exception. Thi...

3D Printable Drug Delivery Systems: Next-generation Healthcare Technology and Regulatory Aspects.

A revolutionary shift in healthcare has been sparked by the development of 3D printing, propelling us into an era replete with boundless opportunities...

Drug-Protein Interactions Prediction Models Using Feature Selection and Classification Techniques.

BACKGROUND: Drug-Protein Interaction (DPI) identification is crucial in drug discovery. The high dimensionality of drug and protein features poses cha...

Recent Trends in Computer-aided Drug Design for Anti-cancer Drug Discovery.

Cancer is considered one of the deadliest diseases globally, and continuous research is being carried out to find novel potential therapies for myriad...

GeoPacker: A novel deep learning framework for protein side-chain modeling.

Atomic interactions play essential roles in protein folding, structure stabilization, and function performance. Recent advances in deep learning-based...

Towards emotionally aligned social robots for dementia: perspectives of care partners and persons with dementia.

BACKGROUND: Persons living with dementia and their care partners place a high value on aging in place and maintaining independence. Socially assistive...

Learning temporal difference embeddings for biomedical hypothesis generation.

MOTIVATION: Hypothesis generation (HG) refers to the discovery of meaningful implicit connections between disjoint scientific terms, which is of great...

A review of biomedical datasets relating to drug discovery: a knowledge graph perspective.

Drug discovery and development is a complex and costly process. Machine learning approaches are being investigated to help improve the effectiveness a...

Artificial intelligence-driven prediction of multiple drug interactions.

When a drug is administered to exert its efficacy, it will encounter multiple barriers and go through multiple interactions. Predicting the drug-relat...

MHADTI: predicting drug-target interactions via multiview heterogeneous information network embedding with hierarchical attention mechanisms.

MOTIVATION: Discovering the drug-target interactions (DTIs) is a crucial step in drug development such as the identification of drug side effects and ...