ASHG 2026 · Tier 1 Academic

Technical University of Munich at ASHG 2026

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

Munich, Germany

Technical University of Munich at ASHG 2026 in Montréal: 8 presentations (6 posters, 1 lightning talk, 1 platform talk); 5 research groups.

presentations on the program

research groups identified

Reviewers’ Choice abstracts

Explore everyone at ASHG 2026 →

Organization	ASHG 2026 Attendance
Technical University of Munich Munich, Germany	3 PhD Students · 2 Staff Scientists · 1 Postdoc
Chair of Computational Molecular Medicinecs.cit.tum.de/en/cmm/home Dry lab~26 people Uses statistical modeling on next-generation sequencing, mass spectrometry, DNA/RNA sequencing and proteomics data. Supports rare-disease diagnosis with the Prokisch group and Solve-RD. 68 papers since 2024 › CAGI, the Critical Assessment of Genome Interpretation, establishes progress and prospects for computational genetic variant interpretation methods Genome biology, 2024 Species-aware DNA language models capture regulatory elements and their evolution Genome biology, 2024 Deep learning-driven fragment ion series classification enables highly precise and sensitive de novo peptide sequencing Nature Communications, 2024 Source: OpenAlex author A5000244333 Funded by DFG, ERC › ERC, ERC Synergy grant EPIC · 2024-2030 “on a 6-year (2024-2030) ERC Synergy grant called EPIC” DFG, INST 95/1655-1 FUGG; INST 95/1863-1 FUGG · active “Co-financed by the DFG (INST 95/1655-1 FUGG and INST 95/1863-1 FUGG)” Source: lab pages 9 platforms and techniques › Analyzes next-generation sequencing, mass spectrometry-based proteomics, DNA sequencing, RNA sequencing Techniques statistical modeling, machine learning, deep learning, conditional autoencoder, de novo peptide sequencing Source: lab pages Currently hiring › “We are constantly seeking for highly motivated students in bioinformatics, physics and/or applied mathematics” Source: lab positions page	Talk Wed Oct 21 1:35 pm DeepRVAT2: Unified modeling of coding and regulatory rare variation at genome scale for enhanced gene discovery and diagnostics Advancing Precision Oncology with AI, Functional Genomics, and Multi-Omics: From Risk Prediction to Tumor Evolution and Therapeutic Discovery Collaborators: Helmholtz Munich, German Cancer Research Center Artificial intelligenceLarge-scale biobanksMendelian disorderRare variants Poster Wed Oct 21 2:30 pm ★ Reviewers’ Choice Improved gene-trait association discovery using functional gene embeddings and multi-trait modelling Artificial Intelligence and Machine Learning Genotype-phenotype correlationsLarge-scale biobanksMachine learningPhenome-wide association Poster Thu Oct 22 4:15 pm ★ Reviewers’ Choice DeepRVAT2: Unified Modeling of Coding and Regulatory Rare Variation at Genome Scale for Enhanced Gene Discovery and Diagnostics Artificial Intelligence and Machine Learning Collaborators: Helmholtz Munich, German Cancer Research Center Artificial intelligenceLarge-scale biobanksMendelian disorderRare variants Talk Fri Oct 23 11:15 am Standardized transcriptome analysis improves rare disease diagnosis in large rare disease consortia Resolving Rare Disease: Transcriptional, Functional, and Population-Scale Approaches Collaborators: University of Tübingen, UCL Queen Square Institute of Neurology +6 more BioinformaticsClinical geneticsMendelian disorderMulti-omics
Data Science in Systems Biologymls.ls.tum.de/en/daisybio/home Wet + dry lab~30 people Analyzes transcriptomics, proteomics, spatial and single-cell omics, and cohort data with machine learning. Uses them for drug-response prediction, network medicine and population-cohort analysis. Funded by BMBF, Novo Nordisk Foundation +6 more › BMBF, DROP2AI · active “The BMBF-funded DROP2AI project aims to predict drug response” Novo Nordisk Foundation, MOPITAS · active “The Novo Nordisk Foundation support the project MOPITAS” DFG, DyHealthNet · active “In the DFG-funded project DyHealthNet we build an explorative analysis platform” +5 more on the lab page Source: lab pages 13 platforms and techniques › Works with Transcriptomics drug screens, Proteomics drug screens, Spatial omics, Single-cell omics, Shallow shotgun metagenomics sequencing, Bulk RNA-seq Techniques Machine learning, Data integration, Network medicine, Cell lines, Organoids, Mouse models, Human-in-the-loop analysis Source: lab pages No openings posted	Poster Wed Oct 21 2:30 pm GNExT uncovers pharmacological targets from genome-wide association studies through network medicine integration Genetic, Genomic, and Epigenomic Resources and Databases Collaborators: Eurac Research, Friedrich-Alexander-Universität Erlangen-Nürnberg +1 more BioinformaticsGenome-wide association studyIdentification of disease genesPharmacologic therapy
NFDI GHGAghga.de/about-us/team-members Dry lab~101 people Develops standardised omics workflows for WGS, WES, RNA sequencing, 10x single-cell and Xenium data. Supports variant detection, rare disease diagnostics and cancer research. Funded by DFG › DFG, NFDI · active “GHGA is funded via the DFG under the umbrella of the NFDI.” Source: lab pages 12 platforms and techniques › Analyzes Whole-genome sequencing (WGS), Targeted sequencing, Whole-exome sequencing (WES), RNA sequencing, 10x single-cell RNA-seq, Xenium Techniques Germline variant calling and annotation, Somatic variant calling, Variant benchmarking, RNA-seq analysis, RNA outlier detection, Spatial transcriptomics analysis Source: lab pages Currently hiring › “We are constantly looking for talents in software development and cloud computing” Source: lab positions page	Poster Wed Oct 21 2:30 pm Omics outlier analysis in rare cancers reveals the function of rare germline variants in predisposition genes Cancer Collaborators: Technische Universität Dresden, Deutsches Konsortium für Translationale Krebsforschung +5 more CancerVariant interpretationAlternative splicingMulti-omics
Workflowsghga.de/de/ueber-uns/das-team Dry lab~15 people Standardizes NGS workflows for WGS, WES, RNA-seq, single-cell RNA-seq and Xenium data. Supports reproducible variant detection, rare-disease diagnostics and cancer research. Funded by Deutsche Forschungsgemeinschaft (DFG) › Deutsche Forschungsgemeinschaft (DFG), NFDI · active “Die GHGA wird über die DFG unter dem Dach der NFDI gefördert.” Source: lab pages 15 platforms and techniques › Analyzes Whole-genome sequencing (WGS), Targeted sequencing, Whole-exome sequencing (WES), RNA sequencing, Single-cell RNA-seq, Spatial transcriptomics, Xenium, Proteomics Techniques Germline variant calling and annotation, Somatic variant calling, Allele-specific copy-number estimation, Short tandem repeat analysis, Variant benchmarking, Aberrant expression and splicing detection, Continuous integration and deployment Source: lab pages Currently hiring › “We are constantly looking for talents in software development and cloud computing” Source: lab positions page	Poster Thu Oct 22 4:15 pm Refined NMD and splicing annotations improve aberrant gene expression prediction Molecular Effects of Genetic Variation Collaborators: Institute of Computational Biology BioinformaticsClinical geneticsComputational toolsRare variants
Niopek Labniopeklab.de Works in rare disease and computational genetics.	Poster Thu Oct 22 4:15 pm ★ Reviewers’ Choice Causal variant prioritization for rare disease using biobank-calibrated gene impairment and functional gene embeddings Artificial Intelligence and Machine Learning Identification of disease genesRare variantsMachine learningLarge-scale biobanks

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