ASHG 2026 · Tier 2–3 Academic

Dana-Farber Cancer Institute at ASHG 2026

Name: ASHG 2026 Annual Meeting
Start: 2026-10-20
End: 2026-10-24
Location: Montréal

Boston, Massachusetts

Dana-Farber Cancer Institute at ASHG 2026 in Montréal: 6 presentations (3 platform talks, 3 posters); 4 research groups.

presentations on the program

research groups identified

sessions invited to or moderated

Explore everyone at ASHG 2026 →

Organization	ASHG 2026 Attendance
Dana-Farber Cancer Institute Boston, Massachusetts	4 Postdocs · 1 PI
Gusev Labgusevlab.org Dry lab Develops statistical methods for single-cell transcriptomics, epigenomics and electronic health record data. Studies disease mechanisms, treatment response and prediction in large clinical cohorts. 112 papers since 2024 › Lung cancer in patients who have never smoked — an emerging disease Nature Reviews Clinical Oncology, 2024 Genetic and molecular architecture of complex traits Cell, 2024 Cross-ancestry atlas of gene, isoform, and splicing regulation in the developing human brain Science, 2024 Source: OpenAlex author A5044886059 Funded by Common Fund of the Office of the Director of the National Institutes of Health › Common Fund of the Office of the Director of the National Institutes of Health, Genotype-Tissue Expression (GTEx) Project · active “The Genotype-Tissue Expression (GTEx) Project was supported by the Common Fund of the Office of the Director of the National Institutes of Health.” Source: lab pages 7 platforms and techniques › Analyzes ATAC-seq Techniques Statistical modeling, GWAS, Single-cell transcriptomics, Machine learning, Survival analysis, Fine-mapping Source: lab pages No openings posted	Poster Wed Oct 21 2:30 pm Cell-type- and cell-state-specific genetic regulation in the aging brain Molecular Effects of Genetic Variation Alzheimer’s diseaseExpression quantitative trait lociIdentification of disease genesNeurodegeneration Talk Thu Oct 22 11:15 am Single-cell gene expression heritability informed by gene × cell-state interactions Cross-Disease Insights into Neuropsychiatric and Neurodegenerative Disorders Gene environment interactionHeritabilityNeurodegenerationSingle-cell
Center for Cancer Systems Biologyccsb.dana-farber.org Wet lab~14 people Maps binary protein-protein interactions using yeast two-hybrid, MAPPIT, GPCA and TAP-MS. Builds human ORFeome resources for disease and pathogen-host network studies. 23 papers since 2024 › Widespread variation in molecular interactions and regulatory properties among transcription factor isoforms Molecular Cell, 2025 The Time Machine: Future Scenario Generation Through Generative AI Tools Future Internet, 2025 Pervasive mislocalization of pathogenic coding variants underlying human disorders Cell, 2024 Source: OpenAlex author A5040546953 14 platforms and techniques › Runs Yeast two-hybrid (Y2H), MAPPIT, GPCA, Tandem affinity purification–mass spectrometry (TAP-MS), Reverse Yeast Two-Hybrid (RY2H), NanoLuc Two-Hybrid (N2H), DNA-barcoded protein technologies Techniques Forward and reverse genetics, CRISPR technologies, Gateway recombinational cloning, Phenotypic screens, Proteomic analysis, Transcriptional profiling, Saccharomyces cerevisiae model Source: lab pages No funding stated · No openings posted	Talk Thu Oct 22 11:15 am High-throughput profiling of macromolecular interaction perturbations in human genetic disorders Uptown Funk(tion): Don’t Believe Me, Just Perturb Collaborators: Université Libre de Bruxelles, University of Toronto +1 more Genetic variationPhenotypeProteomicsVariant interpretation
Collins Genomics Lablabs.dana-farber.org/collins-genomics Dry lab~10 people Analyzes germline whole-genome sequencing and population-scale genomic data with genome informatics, statistics and machine learning. Targets cancer predisposition, tumorigenesis and early-onset cancer interception. 22 papers since 2024 › Diversity and consequences of structural variation in the human genome Nature Reviews Genetics, 2025 Rare germline structural variants increase risk for pediatric solid tumors Science, 2025 Author Correction: A genomic mutational constraint map using variation in 76,156 human genomes Nature, 2024 Source: OpenAlex author A5022093098 Funded by National Cancer Institute, Haroun Family Foundation +2 more › National Cancer Institute, NCI Pathway to Independence Award for Early-Stage Postdoctoral Researchers; R00 CA286805 · 2025-2028 “2025-2028 — $419,661 — NCI Pathway to Independence Award for Early-Stage Postdoctoral Researchers (PI; R00 CA286805)” Haroun Family Foundation · 2025-2027 “2025-2027 — $112,500 — Haroun Family Foundation (MPIs: Collins, Gillani)” American Cancer Society, Institutional Research Grant; IRG-24-1290526-01 · 2026 “2026 — $55,000 — American Cancer Society Institutional Research Grant (PI; IRG-24-1290526-01)” +1 more on the lab page Source: lab pages 8 platforms and techniques › Analyzes Germline whole-genome sequencing, Cancer sequencing datasets Techniques Genome informatics, Statistics / machine learning, Epigenomics, Multimodal data fusion / integration, Statistical modeling, Structural and rare noncoding variant analysis Source: lab pages Currently hiring › “We are always looking for motivated and collaborative people to join our team.” Source: lab positions page	Moderator Thu Oct 22 8:15 am The Long and Short of It: Long-Read Genomics from Biobanks to the Clinic
Price Labhsph.harvard.edu/research/price-lab Works in computational genetics. 24 papers since 2024 › Deciphering the impact of genomic variation on function Nature, 2024 Tissue-specific enhancer–gene maps from multimodal single-cell data identify causal disease alleles Nature Genetics, 2024 Pervasive findings of directional selection realize the promise of ancient DNA to elucidate human adaptation bioRxiv (Cold Spring Harbor Laboratory), 2024 Source: OpenAlex author A5066797582	Talk Wed Oct 21 11:45 am When to trust a genomic deep learning model: Effect magnitude as an intrinsic confidence signal for personalized expression prediction Promise and Peril of Sequence-to-Function Models for Variant Effect Predictions Collaborators: Boston Children's Hospital Deep learningExpression quantitative trait lociGene regulationGenetic variation
2 more presenters — research group not yet identified

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