Guang Hu

Dynamics-aware geometric learning predicts disease-associated molecular perturbations

This study introduces DynGeo-Pheno, a geometric deep learning framework that predicts disease-associated phosphosites and missense mutations by integrating protein dynamics and structural information.

Atomistic Profiling of KRAS Interactions with Monobodies and Affimer Proteins Through Ensemble-Based Mutational Scanning Unveils Conserved Residue Networks Linking Cryptic Pockets and Regulating Mechanisms of Binding, Specificity and Allostery

This study identifies conserved allosteric hotspots in KRAS through computational analysis of interactions with monobodies and affimers, revealing structural and functional networks that govern binding and allostery.

Decoding Mechanisms of PTEN Missense Mutations in Cancer and Autism Spectrum Disorder using Interpretable Machine Learning Approaches

This study uses interpretable machine learning and structural dynamics to analyze PTEN mutations linked to cancer and autism, revealing shared molecular mechanisms.

protPheMut: An Interpretable Machine Learning Tool for Classification of Cancer and Neurodevelopmental Disorders in Human Missense Variants

protPheMut predicts cancer and neurodevelopmental disorder phenotypes from missense variants using interpretable machine learning, achieving high accuracy in PI3K and PTEN mutation analysis.

Multi-omics investigation of spontaneous T2DM macaque emphasizes gut microbiota could up-regulate the absorption of excess palmitic acid in the T2DM progression

This study investigates the role of gut microbiota in T2DM progression in macaques, finding that microbiota enhances palmitic acid absorption, leading to inflammation and T2DM development.

Identifying Lymph Node Metastasis-related Factors in Breast Cancer using Differential Modular and Mutational Structural Analysis

This paper identifies factors related to lymph node metastasis in breast cancer using differential modular and mutational structural analysis of protein networks.

Network-based hub biomarker discovery for glaucoma

This paper identifies hub biomarkers and pathways for glaucoma using network medicine approaches and validates them with text-mining and genomic data.