Russell Littman

The paper introduces CellMAPP and CHART to analyze multiplexed antibody imaging data, revealing modular morphological programs in response to genetic perturbations.

PRESAGE predicts perturbation expression responses using gene embeddings and outperforms existing methods in functional evaluations.

The paper identifies distinct subtypes of cardiac-innervating sympathetic neurons using viral tracing and single-cell RNA sequencing, revealing their unique physiological roles in stress responses.

SCING improves GRN inference accuracy and interpretability using gradient boosting and mutual information on scRNAseq, snRNAseq, and spatial transcriptomics data.

JSTA improves spatial transcriptomics accuracy by jointly segmenting cells and annotating their types, revealing detailed spatial gene expression patterns in mouse hippocampus.

This study benchmarks WGS-based structural variant callers using a PCR-confirmed gold standard, finding wide performance variation and identifying tools best suited for low and ultra-low pass data.

This study benchmarks error-correction methods for next-generation sequencing data, finding significant variation in performance across datasets with no single method being optimal overall.

The paper assesses the installability and archival stability of computational biology tools, finding many are inaccessible or hard to install, and recommends policy changes to improve these aspects.