Élisabeth Rémy

The paper introduces scBOLT, a framework for inferring Boolean networks from multi-condition single-cell transcriptomes, improving computational tractability for large-scale models.

The paper constructs a logical model of the myelofibrotic microenvironment to predict how TPO and TLR signaling disrupt stem cell crosstalk and drive disease progression.

The paper develops a logical model of Fe-S cluster biogenesis in E. coli to analyze how environmental stressors like iron deprivation and oxidative stress regulate this process.

The paper develops a Boolean network model of early hematopoiesis aging using scRNA-seq data and literature, identifying key regulatory changes in aged HSCs.

The paper analyzes single-cell RNA-seq data from young and aged mouse HSCs to show delayed differentiation and cell cycle imbalance in aged HSCs.

This study benchmarks nine joint multi-omics dimensionality reduction methods using simulated and real cancer data, finding intNMF excels in clustering and MCIA shows consistent performance across contexts.

This study profiles the proteomes and phosphoproteomes of four prostate cell lines to identify differentially expressed proteins and phosphosites associated with resistance and cancer progression.

The paper extends the random walk with restart algorithm to multiplex and heterogeneous biological networks to improve disease gene prediction.