Jacob Goldberger

The paper analyzes bulk RNA-seq data from a kidney IRI mouse experiment to identify temporal phases and alternatively spliced genes, revealing potential splicing regulators involved in injury and repair.

The paper introduces robustness measures to evaluate cell-type classification reliability in single-cell RNA-seq datasets of kidney organoids and finds high robustness in most cell types except immature ones.

This paper develops a deep learning framework to detect kinematic events in primate reaching behavior and assesses its performance across animals.

This study uses unsupervised machine learning to identify temporal gene expression components in HeLa cells after cell cycle release, revealing oscillatory and transient patterns linked to cell cycle phases and cancer-related processes.

This study characterizes alternative splicing heterogeneity in high-risk Wilms tumors using RNAseq data, identifying splicing patterns linked to kidney development and EMT.