Daphne Koller

This paper evaluates combining expression-based surrogate variables and genotype-based principal components in differential expression analysis, finding the combined approach improves replicability and biological recall in ALS datasets.

This paper introduces a pooled CRISPR screening platform combined with self-supervised deep learning to infer gene function from morphological phenotypes without target-specific biomarkers.

This paper shows that genome-wide association studies on ratio traits can be misleading, as associations may be driven by the denominator rather than the numerator, and proposes a method to correct for collider bias.

The paper uses deep learning on images of iPSC-derived motor neurons with fALS mutations to identify disease-relevant phenotypes and molecular differences.

EmbedGEM evaluates embeddings for genetic discovery by assessing heritability and disease relevance using polygenic risk scores and genome-wide association statistics.

The paper introduces COAST, a rare variant association test for allelic series, which improves power over SKAT-O in detecting gene-trait associations in lipid and cell count traits using UK Biobank data.

This study compares gene modules in human and mouse immune cells, finding conserved transcriptional organization but divergent regulatory mechanisms.