Author

Di Wang

The University of Texas at San Antonio Health Science CenterORCID 0000-0003-0460-1463Unclaimed ORCID profile · follow to get notified of new preprints

Additional preprints under this name without ORCID

Di Wang6 papers · Allen Institute

Biology Disciplines

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Genetic & Genomic Medicine· 1 Neuroscience· 1

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Research Focus:differential expression· 1 Research Focus:gene regulatory network inference· 1 Research Focus:GWAS / association mapping· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Approach:statistical model· 1

Frequent Co-Authors

Christos A. DavatzikosiD· 2 shared Derek B. ArcheriD· 2 shared Mohamad HabesiD· 2 shared Timothy J. HohmaniD· 2 shared Aditi Sathe· 1 shared Alaina Durant· 1 shared Alzheimer’s Disease Neuroimaging Initiative· 1 shared Andrew J. SaykiniD· 1 shared

Activity by Year

2025-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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2 shared papersGenetic & Genomic Medicine

Christos A. DavatzikosORCID

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2 papers

Recent·Most cited

Genetic & Genomic MedicineAlzheimer s & DementiaPeer-reviewedJul 1, 2026

Genetic architecture of the limbic white matter microstructure in aging and Alzheimer's Disease.

Anna Lorenz, Aditi Sathe, Yisu Yang…·The Alzheimer's Disease Sequencing Project (ADSP)

This study identifies genetic loci and pathways associated with limbic white matter microstructure in aging and Alzheimer's Disease using multi-cohort diffusion MRI and bulk RNA-seq data.

DOI 10.1002/alz.71630

humanbulk RNA-seq

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NeurosciencebioRxivPreprintJun 9, 2025

Advancing Fair and Explainable Machine Learning for Neuroimaging Dementia Pattern Classification in Multi-Ethnic Populations

Ngoc-Huynh Ho, Sokratis Charisis, Nicolas Honnorat…·Mohamad Habes

This study addresses dementia classification bias across ethnic groups using few-shot learning and domain alignment, reducing performance gaps between White American and Hispanic cohorts.

DOI 10.1101/2025.06.09.658375

machine learning (classical)benchmarking

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