Prescriptions

MolUNet++: Adaptive-grained Explicit Substructure and Interaction Aware Molecular Representation Learning

Molecular representation learning is a critical task in AI-driven drug development. While graph neural networks (GNNs) have demonstrated strong performance and gained widespread adoption in this field, efficiently extracting and explicitly analyzing functional groups remains a challenge. To address this issue, we propose MolUNet++, a novel model that employs Molecular Edge Shrinkage Pooling (MESPo...

An organotypic in vitro model of human papillomavirus-associated precancerous lesions allowing automated cell quantification for preclinical drug testing

A durable organotypic epithelial raft culture was established as a model of cervical precancer. Plausible time- and dose-dependent effects of cisplatin, 5-FU, and sinecatechins treatment were observed on keratinocytes and HPV-transformed cells. Treatment effects were reliably quantified using machine learning-based cell classification. This model may serve as a platform for preclinical investigati...

Biological Database Mining for LLM-Driven Alzheimer’s Disease Drug Repurposing

This study presents a software pipeline that leverages LLMs to apply knowledge stored in natural language (such as in pharmacological texts) and ontol...

OmniPert: A Deep Learning Foundation Model for Predicting Responses to Genetic and Chemical Perturbations in Single Cancer Cells

In cancer, intra- and inter-patient heterogeneity presents a significant challenge for therapeutic management, as patients with apparently similar pro...

Pixel-Precise Lesion Localization in WSIs via Weakly Supervised Streaming Convolution with ReLSE and Adaptive Self-Training

A robust artificial intelligence-assisted workflow for tumor assessment in pathology requires not only accurate classification but also precise lesion...

A Deep Learning-based Method for Drug Molecule Representation and Property Prediction

Accurately and robustly representing drug molecule features, prediction of drug-target biomacromolecule interactions, and determining drug molecule ph...

Prediction of bacterial protein-compound interactions with only positive samples

Prediction of Compound-Protein Interactions (CPI) in bacteria is crucial to advance various pharmaceutical and chemical engineering fields, including ...

Using spatial statistics to infer game-theoretic interactions in an agent-based model of cancer cells

Drug resistance in cancer is shaped not only by evolutionary processes but also by eco-evolutionary interactions between tumor subpopulations. These i...

Polymer functionalized liposomes as universal nanocarriers for drug delivery: Single particle insights on size-dependent performance and intracellular behavior

Nanomedicine requires smart delivery systems that are precise, robust, and universal. While liposomes are established vehicles in drug delivery, their...

Interdisciplinary Study on Drug-Induced-Phospholipidosis of Repurposing Libraries through Machine Learning and Experimental Evaluation in Different Cell Lines

Phospholipidosis is a cellular condition characterized by the excessive accumulation of phospholipids within cells, that also can be induced by medica...

An Evaluation of Biomolecular Energetics Learned by AlphaFold

Deep learning has revolutionized protein structural prediction, with function prediction on the horizon. Because biomolecular properties emerge from a...

DrugPT: A Flexible Framework for Integrating Gene and Chemical Representations in Perturbation Modeling

Accurately modeling the transcriptional response of cells to drug perturbations is critical for drug discovery and precision medicine. Here, we propos...

Transcriptomic profiling and machine learning uncover gene signatures of psoriasis endotypes and disease severity

Despite increased understanding of psoriasis pathogenesis, molecular classification of clinical phenotypes and disease severity is poorly defined. Kno...

DeepADR: Multi-modal Prediction of Adverse Drug Reaction Frequency by Integrating Early-Stage Drug Discovery Information via Kolmogorov-Arnold Networks

Adverse drug reactions (ADRs) are a major cause of clinical trial failure and post-market withdrawal, posing significant risks to public health and im...

Predicting Drug Response with Multi-Task Gradient-Boosted Trees in Epilepsy

Despite the availability of numerous anti-seizure medications (ASMs), drug resistance remains a major issue for people with epilepsy. The probability ...

Early Target Prediction in Action Observation

Previous research has established that observers can predict action targets through hand preshaping. However, two critical questions remain unexplored...

Human protein interactome structure prediction at scale with Boltz-2

In humans, protein-protein interactions mediate numerous biological processes and are central to both normal physiology and disease. Extensive researc...

Tension shapes memory: Computational insights into neural plasticity

Mechanical forces have recently emerged as critical modulators of neural communication, yet their role in high-level cognitive functions remains poorl...

Developing inhibitors of the guanosine triphosphate hydrolysis accelerating activity of Regulator of G protein Signaling-14

Regulator of G protein Signaling-14 (RGS14), an intracellular inactivator of G protein-coupled receptor (GPCR) signaling, is considered an undruggable...

BioScientist Agent: Designing LLM-Biomedical Agents with KG-Augmented RL Reasoning Modules for Drug Repurposing and Mechanistic of Action Elucidation

Drug discovery is protracted, resource-intensive, and afflicted by attrition rates exceeding 90 %, which leaves most diseases, particularly rare or ne...