Linhui Xie
Postdoctoral Associate in Biomedical Informatics and Data ScienceAbout
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Postdoctoral Associate in Biomedical Informatics and Data Science
Biography
Dr. Linhui Xie earned his Ph.D. in Electrical and Computer Engineering from Purdue University in 2024. During his doctoral studies, he contributed to advancing our understanding of Alzheimer’s disease as a research assistant at the Indiana Alzheimer’s Disease Research Center, where he developed interpretable deep learning and multi-omic integration methods. In 2023, he further expanded his expertise as a visiting student at the University of Pennsylvania, exploring latent space representations to enhance genetic association studies in neurodegenerative disorders.
Currently, Dr. Xie is a postdoctoral associate in the Department of Biomedical Informatics and Data Science at Yale School of Medicine with Dr. María Rodríguez Martínez. His research focuses on computational modeling, bioinformatics, computational systems biology, and interpretable AI. He applies integrative approaches, such as heterogeneous multi-omic data analysis, neuroimaging, and pathway modeling, to investigate neurodegeneration and human brain connectomes. At Yale, he leverages interpretable AI methods to study T cell receptor binding, B cell development, and autoimmune disease mechanisms.
Dr. Xie is inspired by Yale BIDS’ collaborative spirit and its world-renowned interdisciplinary research team. Reflecting on his enthusiasm, he shares: "What excites me most about joining Yale BIDS is the collaborative spirit within its world-renowned interdisciplinary research team. It offers phenomenal training at the intersection of biomedical data science and computational modeling. I am thrilled and eager to gain expertise in data-driven methods to accelerate discoveries in immunology."
Outside of work, Dr. Xie enjoys cycling, running, swimming, cooking, and spending time with his family. One of his most memorable adventures was a 25-day cycling journey spanning approximately 1,300 miles through breathtaking landscapes and high-altitude mountains, blending his love for physical challenges and the outdoors.
Appointments
Biomedical Informatics & Data Science
Postdoctoral AssociatePrimary
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Overview
Medical Research Interests
Public Health Interests
ORCID
0000-0003-1238-8789
Research at a Glance
Publications Timeline
Research Interests
Computational Biology
Publications
2025
Deep fusion of incomplete multi-omic data for molecular mechanism of Alzheimer’s disease
Xie L, Raj Y, Tong M, Nho K, Salama P, Saykin A, Fang S, Yan J. Deep fusion of incomplete multi-omic data for molecular mechanism of Alzheimer’s disease. Scientific Reports 2025, 15: 30182. PMID: 40825989, PMCID: PMC12361453, DOI: 10.1038/s41598-025-14636-2.Peer-Reviewed Original ResearchCitations
2024
Deciphering the tissue-specific functional effect of Alzheimer risk SNPs with deep genome annotation
Pugalenthi P, He B, Xie L, Nho K, Saykin A, Yan J. Deciphering the tissue-specific functional effect of Alzheimer risk SNPs with deep genome annotation. BioData Mining 2024, 17: 50. PMID: 39538253, PMCID: PMC11558841, DOI: 10.1186/s13040-024-00400-1.Peer-Reviewed Original ResearchCitationsAltmetricDeep Trans-Omic Network Fusion for Molecular Mechanism of Alzheimer’s Disease
Xie L, Raj Y, Varathan P, He B, Yu M, Nho K, Salama P, Saykin A, Yan J. Deep Trans-Omic Network Fusion for Molecular Mechanism of Alzheimer’s Disease. Journal Of Alzheimer’s Disease 2024, 99: 715-727. PMID: 38728189, PMCID: PMC12090225, DOI: 10.3233/jad-240098.Peer-Reviewed Original ResearchCitationsAltmetric
2023
Fused multi-modal similarity network as prior in guiding brain imaging genetic association
He B, Xie L, Varathan P, Nho K, Risacher S, Saykin A, Yan J, Initiative T. Fused multi-modal similarity network as prior in guiding brain imaging genetic association. Frontiers In Big Data 2023, 6: 1151893. PMID: 37215688, PMCID: PMC10196480, DOI: 10.3389/fdata.2023.1151893.Peer-Reviewed Original ResearchAltmetric
2022
Gene co-expression changes underlying the functional connectomic alterations in Alzheimer’s disease
He B, Gorijala P, Xie L, Cao S, Yan J. Gene co-expression changes underlying the functional connectomic alterations in Alzheimer’s disease. BMC Medical Genomics 2022, 15: 92. PMID: 35461274, PMCID: PMC9035246, DOI: 10.1186/s12920-022-01244-6.Peer-Reviewed Original ResearchCitationsAltmetricGenetic Influence Underlying Brain Connectivity Phenotype: A Study on Two Age-Specific Cohorts
Cong S, Yao X, Xie L, Yan J, Shen L, Initiative A. Genetic Influence Underlying Brain Connectivity Phenotype: A Study on Two Age-Specific Cohorts. Frontiers In Genetics 2022, 12: 782953. PMID: 35237294, PMCID: PMC8884108, DOI: 10.3389/fgene.2021.782953.Peer-Reviewed Original ResearchCitationsAltmetric
2021
Integrative-omics for discovery of network-level disease biomarkers: a case study in Alzheimer’s disease
Xie L, He B, Varathan P, Nho K, Risacher S, Saykin A, Salama P, Yan J. Integrative-omics for discovery of network-level disease biomarkers: a case study in Alzheimer’s disease. Briefings In Bioinformatics 2021, 22: bbab121. PMID: 33971669, PMCID: PMC8574309, DOI: 10.1093/bib/bbab121.Peer-Reviewed Original ResearchCitationsAltmetric
2020
Tau-related white-matter alterations along spatially selective pathways
Wen Q, Risacher S, Xie L, Li J, Harezlak J, Farlow M, Unverzagt F, Gao S, Apostolova L, Saykin A, Wu Y. Tau-related white-matter alterations along spatially selective pathways. NeuroImage 2020, 226: 117560. PMID: 33189932, PMCID: PMC8364310, DOI: 10.1016/j.neuroimage.2020.117560.Peer-Reviewed Original ResearchCitationsAltmetricIdentification of functionally connected multi-omic biomarkers for Alzheimer’s disease using modularity-constrained Lasso
Xie L, Varathan P, Nho K, Saykin A, Salama P, Yan J. Identification of functionally connected multi-omic biomarkers for Alzheimer’s disease using modularity-constrained Lasso. PLOS ONE 2020, 15: e0234748. PMID: 32555747, PMCID: PMC7299377, DOI: 10.1371/journal.pone.0234748.Peer-Reviewed Original ResearchCitationsAltmetricDifferential co-expression analysis reveals early stage transcriptomic decoupling in alzheimer’s disease
Upadhyaya Y, Xie L, Salama P, Cao S, Nho K, Saykin A, Yan J, Alzheimer’s Disease Neuroimaging Initiative F. Differential co-expression analysis reveals early stage transcriptomic decoupling in alzheimer’s disease. BMC Medical Genomics 2020, 13: 53. PMID: 32241275, PMCID: PMC7118822, DOI: 10.1186/s12920-020-0689-y.Peer-Reviewed Original ResearchCitationsAltmetric
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