7 papers
Generative and multimodal AI for materials prediction and design: Progress, challenges, and perspectives
Xianyuan Liu, Charles Anjah, Benjamin E. Jolly +9
Artificial intelligence (AI) is accelerating materials prediction and design by enabling efficient exploration of chemical and structural spaces, with particular promise for novel…
Co-Evolution-Based Metal-Binding Residue Prediction with Graph Neural Networks
Sayedmohammadreza Rastegari, Sina Tabakhi, Xianyuan Liu +3
Understanding protein-metal interactions is central to structural biology, with metal ions being vital for catalysis, stability, and signal transduction. Predicting metal-binding r…
Towards deployment-centric multimodal AI beyond vision and language
Xianyuan Liu, Jiayang Zhang, Shuo Zhou +45
Multimodal artificial intelligence (AI) integrates diverse types of data via machine learning to improve understanding, prediction, and decision-making across disciplines such as h…
Mask prior-guided denoising diffusion improves inverse protein folding
Peizhen Bai, Filip MiljkoviÄ, Xianyuan Liu +4
Inverse protein folding generates valid amino acid sequences that can fold into a desired protein structure, with recent deep-learning advances showing strong potential and competi…
Interpretable Multimodal Learning for Tumor Protein-Metal Binding: Progress, Challenges, and Perspectives
Xiaokun Liu, Sayedmohammadreza Rastegari, Yijun Huang +12
In cancer therapeutics, protein-metal binding mechanisms critically govern the pharmacokinetics and targeting efficacy of drugs, thereby fundamentally shaping the rational design o…
MeDSLIP: Medical Dual-Stream Language-Image Pre-training with Pathology-Anatomy Semantic Alignment
Wenrui Fan, Mohammod N. I. Suvon, Shuo Zhou +6
Pathology and anatomy are two essential groups of semantics in medical data. Pathology describes what the diseases are, while anatomy explains where the diseases occur. They descri…