Steven J. Altschuler

Branched-chain amino acid fermentation as an alternative mammalian electron sink

This study identifies branched-chain amino acid fermentation as an alternative electron sink in mammals under hypoxia, with implications for reductive stress and sperm motility.

Dissecting the effects of GTPase and kinase domain mutations on LRRK2 endosomal localization and activity

The paper investigates how GTPase and kinase domain mutations in LRRK2 affect endosomal localization and Rab phosphorylation, finding that GTPase-inactivating mutants lead to more LRRK2+ endosomes and higher Rab phosphorylation.

Commitment in the Pink1/Parkin mitophagy decision circuit

The paper quantifies the relationship between PINK1 levels and Parkin recruitment dynamics to show a threshold and delay mechanism that prevents erroneous mitophagy activation.

A scalable screening platform for phenotypic subtyping of ALS patient-derived fibroblasts

The paper develops a scalable platform combining microscopy and machine learning to subtype ALS patient fibroblasts, identifying a FUS-ALS phenotypic score that correlates with age and treatment response.

On the role of photoreceptor identity in controlling accurate wiring of the Drosophila visual circuit

This study investigates how photoreceptor identity influences axon extension velocity and circuit formation in Drosophila.

Characterizing tissue composition through combined analysis of single-cell morphologies and transcriptional states

This paper introduces MUSE, a method that combines single-cell morphology and transcriptional data to better characterize tissue heterogeneity and identify subpopulations missed by individual modalities.

Loss of Tet2 affects proliferation and drug sensitivity through altered dynamics of cell-state transitions

This study shows that Tet2 loss-of-function in AML cells alters cell-state transitions, improving survival during drug treatment and contributing to relapse.

Massive single-cell RNA-seq analysis and imputation via deep learning

The paper introduces scScope, a deep learning method for cell-type composition identification from large-scale single-cell RNA-seq data.