Daniela Witten

IsoRanker uses long-read transcriptomics to prioritize non-coding variants in Mendelian conditions by detecting expression outliers, allelic imbalance, and NMD, leading to the identification of pathogenic variants in one individual.

This study shows that LHA GABAergic and glutamatergic neurons independently scale activity during consumption and cooperatively regulate striatal dopamine release in mice.

The paper uses single cell calcium imaging in mice to show that most CeA neurons encode valence of unconditioned stimuli, with a smaller subset encoding salience.

The paper introduces FIRE to comprehensively map haplotype-selective chromatin accessibility in diploid human genomes, revealing somatic epimutations that contribute to non-genetic chromatin alterations.

The paper develops a method to simultaneously fit single-cell neural activity models and group neurons into functional cell types, improving prediction accuracy and interpretability.

The paper identifies candidate genes with large fitness effects in aneuploid yeast under specific stress conditions using a piecewise constant model.

The paper validates a spike inference method using calcium imaging in dopamine neurons, showing accurate spike detection in both slice and in vivo settings.

This paper introduces MSNR, a multi-scale network regression method that models brain networks at multiple scales, showing improved interpretability and performance in linking brain connectivity to phenotypes.

The paper develops and evaluates methods to estimate neural spiking rates from wide-field calcium imaging data by deconvolving calcium indicator dynamics and accounting for noise.

The paper presents a large-scale dataset of neural activity in the mouse visual cortex and shows that responses to different stimuli are largely independent, suggesting multi-layer hierarchical computation.