Michael E. Vinyard

scDiffEq models single-cell dynamics using neural stochastic differential equations, improving trajectory reconstruction and fate prediction in hematopoiesis.

SIMBA is a graph embedding method that jointly embeds single cells and their features into a common space, enabling diverse single-cell analysis tasks.

The paper identifies critical base-resolution regulatory elements in immune gene expression using base editing and deep learning.

singlecellVR provides an accessible VR tool for visualizing single-cell data, supporting various modalities and offering a companion package for data conversion and pre-analyzed datasets.

The paper benchmarks 10 scATAC-seq analysis methods on synthetic and real datasets, finding SnapATAC, Cusanovich2018, and cisTopic perform best in separating cell populations across varying coverage and noise levels.