Laura M. Gunsalus

The paper introduces Decima, a model that predicts cell type- and condition-specific gene expression from DNA sequence using single-cell RNA sequencing data.

This paper introduces CompBioBench, a benchmark for evaluating agentic systems in computational biology, showing strong performance across diverse tasks.

Polygraph assesses synthetic regulatory DNA elements using features like diversity and motif composition to improve gene therapy design.

This study introduces novel methods for comparing chromatin contact maps and evaluates their performance using Hi-C data and in silico maps, highlighting the need for biologically informed approaches.

ChromaFactor deconvolves single-molecule chromatin organization data using non-negative matrix factorization to identify key functional components and their molecular contributions.

gReLU provides a framework for DNA sequence modeling and design, including tools for training, evaluating, and applying pre-trained models to predict and create regulatory elements.

The paper uses deep learning to assess how sequence changes affect chromatin organization, finding that repetitive elements and noncoding RNA genes significantly influence 3D genome structure.

The paper profiles H3K27ac in brain cell types from AD patients and finds acetylation differences in oligodendrocytes linked to AD risk genes and pathways.

The paper uses deep mutational scanning in yeast to show that a toxic conformation of α-synuclein is stable under chemical perturbations, while mutations affecting toxicity are influenced by these perturbations.