Wednesday, November 20
Combi Seminar: Dr. Georg Seelig | University of Washington
"Machine-learning guided sequence design for mRNA and gene therapy applications"
1:30 | Foege Auditorium | remote viewing option | talk will be recorded | flier

Recent Research Highlights

 

Feder Lab
Phylodynamic models disentangle growth patterns in solid tumors

Wang Lab
Generative AI modeling for extrapolating heterogeneous time-series gene expression data

Ha Lab
Computational modeling of circulating tumor DNA for blood-based classification of prostate cancer clinical phenotypes

Mostafavi Lab
Cross-modality representation learning from multi-omic single cell assays

Shojaie Lab
Discovering causal cellular mechanisms using single cell RNAseq data

Lee Lab
Explainable AI approach to cancer precision medicine design

Noble Lab
Deep learning framework for identifying the peptide responsible for generating each observed mass spectrum

Baker Lab

RFdiffusion: A generative model for protein design