Modeling long-range DNA dependencies is crucial for understanding genome structure and function across diverse biological contexts. However, effectively capturing these dependencies, which may span millions of base pairs in tasks such as three-dimens...
Journal of chemical information and modeling
Nov 17, 2025
Data-driven modeling based on machine learning (ML) is becoming a central component of protein engineering workflows. This perspective presents the elements necessary to develop effective, reliable, and reproducible ML models, and a set of guidelines...
Diverse machine learning methods promise to forecast gene expression changes in response to novel genetic perturbations. However, these methods' accuracy is not well characterized. We created a benchmarking platform that combines a panel of 11 large-...
Journal of computer-aided molecular design
Nov 14, 2025
Accurately predicting polymer density from SMILES strings remains challenging due to the small size, high noise, and chemically diversity of typical datasets. We introduce LiteBoost, a deliberately minimalist gradient boosting model that employs shal...
. Quantitative assessment of treatment response in advanced prostate cancer (APC) with bone metastases remains an unmet clinical need. Whole-body diffusion-weighted MRI (WB-DWI) provides two response biomarkers: total diffusion volume (TDV) and globa...
We present MicroVerse, a software application based on large language models (LLMs) designed to generate C# scripts simulating three-dimensional colonies of model organisms, including and , within the Unity platform. The system, which utilizes fine-...
In this work we introduce TorchANI-Amber, an interface for routine molecular dynamics simulations of biomolecular systems using ANI-style machine learning potentials. TochANI-Amber incorporates the ANI neural network potentials into the Amber softwar...
Data-independent acquisition (DIA)-based mass spectrometry is becoming an increasingly popular mass spectrometry acquisition strategy for carrying out quantitative proteomics experiments. Most of the popular DIA search engines make use of in silico g...
The early and accurate classification of eye diseases is essential for preventing irreversible visual impairment. This task can be performed by deep learning approaches that automatically classify retinal fundus images according to potential illnesse...
Recent advances in spatial transcriptomics (ST) highlight the need to integrate multiple slices for joint analysis. A key challenge is generating interpretable embeddings that preserve spatial geometry while correcting batch effects. We present MaskG...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.