Articles in 2023

As long-read sequencing technologies continue to advance, the possibility of obtaining maps of DNA and RNA modifications at single-molecule resolution has become a reality. Here we highlight the opportunities and challenges posed by the use of long-read sequencing technologies to study epigenetic and epitranscriptomic marks and how this will affect the way in which we approach the study of health and disease states.

Nature is often hidden, sometimes overcome, seldom extinguished. —Francis Bacon

MARIO is a robust tool for accurately matching multimodal single-cell datasets.

The Photopick platform, which can be used for phenotype-activated cell selection, was used to develop the improved voltage sensors QuasAr6a and QuasAr6b. These GEVIs offer improved signals and are useful for all-optical electrophysiology.

Dimension reduction is a cornerstone of exploratory data analysis; however, traditional methods fail to preserve the spatial context of spatial genomics data. In this work, we develop a nonnegative spatial factorization (NSF) model that allows interpretable, parts-based decomposition of spatial single-cell count data. NSF allows label-free annotation of regions of interest in spatial genomics data and identifies genes and cells that can be used to define those regions.

We developed an advanced deep learning approach called local shape descriptors (LSDs) to enable analysis of large electron microscopy datasets with increased efficiency. This technique will speed processing of future petabyte-sized datasets and democratize connectomics research by enabling these analyses using modest computational infrastructure available to most laboratories.