Academia Sinica at ASHG 2026

Oct 20–24, 2026 Montréal, Canada ~7.5k attendees Website

Academia Sinica brings 7 presentations from 3 research groups to ASHG 2026 in Montréal. Its program centres on population genetics, biobank resources and computational analysis. Taiwan Biobank brings long-read sequencing of 200 Taiwanese samples, Fann Lab examines air pollution and Alzheimer’s risk, and 陳弘昕老師研究室 prioritizes disease targets across East Asian and European populations.

OrganizationASHG 2026 Attendance
Academia Sinica
Taipei, Taiwan
2 Staff Scientists · 1 PI · 1 Postdoc
Taiwan Biobanktwbiobank.org.tw
Wet lab
Builds a Taiwanese population biobank combining genotyping arrays, whole-genome sequencing, methylation and health data. Supports biomedical research on disease onset, progression and treatment.
14 platforms and techniques
›
Works with
Chemagen Blood DNA isolation kit, TWB1 genotyping array, TWB2 genotyping array, Whole-genome sequencing (WGS), Illumina Infinium MethylationEPIC BeadChip, NXType NGS HLA typing Kit, Bruker IVDr nuclear magnetic resonance platform, Liquid chromatography-tandem mass spectrometry (LC-MS/MS)
Techniques
genotype imputation, genome-wide associations, HLA imputation, variant annotation, DNA methylation profiling, genetic correlations
Source: lab pages
No funding stated · No openings posted
Poster
Wed Oct 21
2:30 pm
Establishing a robust quality control and imputation pipeline for harmonizing distinct genotyping arrays at biobank scale
Collaborators: Institute of Biomedical Sciences, Academia Sinica
Large-scale biobanksStatistical geneticsGenetic epidemiologyGenome-wide association study
Poster
Thu Oct 22
4:15 pm
Fann Labibms.sinica.edu.tw/cathy-fann
Dry lab~7 people
Analyzes UK and Taiwan Biobanks, GWAS and multi-omics data with machine learning. Applies polygenic risk scores to migraine, Alzheimer’s disease and asthma.
19 papers since 2024
›
The Taiwan Precision Medicine Initiative provides a cohort for large-scale studies
Nature, 2025
Population-specific polygenic risk scores for people of Han Chinese ancestry
Nature, 2025
The Taiwan Precision Medicine Initiative: A Cohort for Large-Scale Studies
bioRxiv (Cold Spring Harbor Laboratory), 2024
Source: OpenAlex author A5028466052
8 platforms and techniques
›
Techniques
Genetic statistics, Genetic epidemiology, GWAS, Machine learning, Polygenic risk scores, Rare-variant analysis, AI clustering, Multi-omics integration
Source: lab pages
No funding stated · No openings posted
Poster
Fri Oct 23
2:30 pm
Genetic susceptibility and PM2.5 exposure jointly shape Alzheimer’s disease risk in Taiwanese cohorts
Collaborators: Institute of Biomedical Sciences, Academia Sinica, Taipei Veterans General Hospital +2 more
Alzheimer’s diseaseGene environment interactionPolygenic risk scoreGenome-wide association study
陳弘昕老師研究室ibms.sinica.edu.tw/hung-hsin-chen
Dry lab
Develops algorithms for longitudinal EHR, biobank, RNA-sequencing and multi-omic data. Uses them to study disease genes, phenotype trajectories and disease incidence.
56 papers since 2024
›
The Taiwan Precision Medicine Initiative provides a cohort for large-scale studies
Nature, 2025
Population-specific polygenic risk scores for people of Han Chinese ancestry
Nature, 2025
Large-scale genome-wide analyses of stuttering
Nature Genetics, 2025
Source: OpenAlex author A5084182903
7 platforms and techniques
›
Analyzes
RNA-sequencing, Electronic health records (EHR)
Techniques
Shared segment approaches, Longitudinal analysis, Multi-omic profiling, Genetic epidemiology, Biobank analysis
Source: lab pages
Currently hiring
›
“Dr.陳弘昕(Chen,Hung-Hsin ) 誠徵: 博士後研究 1名 研究助理 1名”
Source: lab positions page
No funding stated
Poster
Thu Oct 22
4:15 pm
Ancestry-matched and cross-omics Mendelian randomization prioritizes transcriptomic and proteomic targets across East Asian and European disease phenomes
Collaborators: Institute of Biomedical Sciences, Academia Sinica, Laureate Institute for Brain Research
Expression quantitative trait lociLarge-scale biobanksMendelian randomizationPhenome-wide association
2 more presenters — research group not yet identified

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