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The metabolomic physics of complex diseases
Human diseases involve metabolic alterations. Metabolomic profiles have served as a vital biomarker for the early identification of …
Shuang Wu, Xiang Liu, Ang Dong, Claudia Gragnoli, Christopher Griffin, Jie Wu, Shing-Tung Yau, Rongling Wu
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Multiscale Topological Indices for the Quantitative Prediction of SARS CoV-2 Binding Affinity Change upon Mutations
The Coronavirus disease 2019 (COVID-19) has affected people’s lives and the development of the global economy. Biologically, …
Jialin Bi, JunJie Wee, Xiang Liu, Cunquan Qu, Guanghui Wang, Kelin Xia
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Persistent Homology for RNA Data Analysis
Molecular representations are of great importance for machine learning models in RNA data analysis. Essentially, efficient molecular …
Kelin Xia, Xiang Liu, JunJie Wee
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Persistent Tor-algebra for protein–protein interaction analysis
Protein–protein interactions (PPIs) play crucial roles in almost all biological processes from cell-signaling and membrane transport to …
Xiang Liu, Huitao Feng, Zhi Lü, Kelin Xia
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Persistent Path-Spectral (PPS) Based Machine Learning for Protein–Ligand Binding Affinity Prediction
Molecular descriptors are essential to quantitative structure activity/property relationship (QSAR/QSPR) models and machine learning …
Ran Liu, Xiang Liu, Jie Wu
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Persistent Tor-algebra based stacking ensemble learning (PTA-SEL) for protein-protein binding affinity prediction
Protein-protein interactions (PPIs) play crucial roles in almost all biological processes. Recently, Data-driven machine learning …
Xiang Liu, Kelin Xia
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Hom-Complex-Based Machine Learning (HCML) for the Prediction of Protein–Protein Binding Affinity Changes upon Mutation
Protein−protein interactions (PPIs) are involved in almost all biological processes in the cell. Understanding protein−protein …
Xiang Liu, Huitao Feng, Jie Wu, Kelin Xia
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Multiphysical graph neural network (MP-GNN) for COVID-19 drug design
Graph neural networks (GNNs) are the most promising deep learning models that can revolutionize non-Euclidean data analysis. However, …
Li Xiao-Shuang, Xiang Liu, Le Lu, Xian-Sheng Hua, Ying Chi, Kelin Xia
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Dowker complex based machine learning (DCML) models for protein-ligand binding affinity prediction
With the great advancements in experimental data, computational power and learning algorithms, artificial intelligence (AI) based drug …
Xiang Liu, Huitao Feng, Jie Wu, Kelin Xia
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Molecular persistent spectral image (Mol-PSI) representation for machine learning models in drug design
Artificial intelligence (AI)-based drug design has great promise to fundamentally change the landscape of the pharmaceutical industry. …
Peiran Jiang, Ying Chi, Xiao-Shuang Li, Zhenyu Meng, Xiang Liu, Xian-Sheng Hua, Kelin Xia
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