Laura M. Heiser

This study identifies HIF1A as a key mediator of OSM-induced collective epithelial migration, linking cytokine signaling to metabolic and immune pathways in breast cancer.

The paper introduces a spatial pharmacology platform to study how chemotherapy affects immune and metabolic states in tumors, identifying key metabolic axes and resistant macrophage populations.

This paper introduces a trajectory-centric framework to model dynamic tumor-immune interactions, showing that treatment-phase TME states predict immunotherapy response better than pre-treatment states.

The paper develops MMIST, a computational approach linking live-cell morphodynamics to gene expression changes during cell state transitions.

The paper introduces an algorithm to correct mislabeling and align object positions in longitudinal 3D cell culture imaging, improving data integrity and reproducibility.

This study identifies immune mimicry in breast cancer cells, where neoplastic cells express leukocyte receptors, enhancing tumor aggressiveness and therapy resistance.

The paper introduces a framework for mathematical modeling of multicellular systems using interpretable cell behavior rules derived from biological knowledge and multi-omics data.

This study investigates how combinations of EGF, OSM, and TGFB cytokines synergistically drive cell motility through CXCR2 chemotaxis and CREB activation in MCF10A cells.

This study shows paclitaxel response in TNBC mimics interferon response, revealing ELF3 as a biomarker for resistance.

The paper uses delay embedding and VAE features to predict single-cell dynamics of a molecular reporter from unlabeled live-cell imaging data.

The paper integrates sequencing and imaging data to map cell cycle states, linking transcriptome states to living cells with high resolution.

The paper evaluates deconvolution methods for inferring immune infiltration from bulk gene expression using a DREAM Challenge, finding that some community-contributed methods, especially deep learning-based ones, perform well.

The paper uses scRNA-seq to identify three subclasses of zebrafish Rohon-Beard neurons, showing Fgf signaling is critical for axon maintenance and cell survival.

The paper identifies Mcf2lb as a regulator of rosette integrity during collective cell migration in zebrafish, showing its role in apical constriction and rosette organization.

The paper presents a LINCS Microenvironment perturbation dataset cataloging transcriptional, proteomic, epigenomic, and phenotypic responses of MCF10A cells to six ligands, enabling integrative analysis of molecular and phenotypic changes.

The paper develops a method to remove technical artifacts from high-throughput imaging assays using systematic replication, improving biological signal clarity.

MOBILE identifies context-specific molecular networks by integrating multi-omics data, revealing new regulatory mechanisms in immune and developmental pathways.

The paper develops an open-source, scalable mechanistic model for single-cell proliferation and death signaling, demonstrating its application to understand IFNγ's anti-proliferative effects.

This paper introduces a morphodynamical trajectory embedding method to analyze live-cell imaging data, revealing ligand-specific cell state transitions and improving trajectory modeling compared to snapshot-based analysis.

This paper introduces a lineage tree-based hidden Markov model to quantify cellular heterogeneity and plasticity using single-cell lineage data, showing it can classify distinct phenotypic states and drug responses in cancer and non-cancer cell populations.

The paper introduces ME-VAE, a multi-encoder VAE for single-cell image analysis that extracts transform-invariant biologically meaningful features, improving cell population separation and phenotypic differences.

This paper introduces a cell tracking method based on Voronoi partition and stable matching to improve tracking accuracy from coarsely sampled live-cell imaging data.

The paper investigates how nutrient limitations affect invasion in cancer populations, showing that phenotypic imbalance accelerates invasion while balance decelerates it.

The paper investigates how preprocessing transformations improve the discovery of biological and technical effects in microenvironment microarray data.

This study investigates factors affecting the reproducibility of in vitro drug-response assays across multiple centers, identifying context-sensitive factors that impact results.

The paper investigates context-specificity in signaling networks using phosphoprotein profiling in breast cancer cell lines under various stimuli and kinase inhibition.