Brian L. Trippe

Leveraging polygenic enrichments of gene features to predict genes underlying complex traits and diseases

The paper introduces a method to prioritize causal genes for complex traits by integrating GWAS data with gene expression and biological data, achieving high precision in gene-trait pair identification.

Broadly applicable and accurate protein design by integrating structure prediction networks and diffusion generative models

Fine-tuning RoseTTAFold as a diffusion denoiser gives RFdiffusion, a general protein backbone generator; a designed influenza haemagglutinin binder matched its model by cryo-EM.

Inhibition of cell fate repressors secures the differentiation of the touch receptor neurons of Caenorhabditis elegans

The paper shows that ZAG-1 inhibits EGL-44/EGL-46 to promote TRN differentiation in C. elegans, forming a negative feedback loop that regulates neuronal fate choice.

K-mer Motif Multinomial Mixtures

The paper introduces K-mer Motif Multinomial Mixtures (KMMMs), a Bayesian framework for motif discovery in sequence data, and applies it to DNAse hypersensitive sites and ChIP-seq peaks.