Noemi Andor

This study models how resource limitations and chromosomal instability influence ploidy evolution in cancer cells across in vitro and in vivo settings.

This study identifies three phases of UV-induced skin carcinogenesis using a mouse model, showing the emergence of large clades, clonal selection, and lesion formation.

This study shows that higher ploidy reduces gemcitabine potency and delays cell death by altering drug exposure kinetics and response timing.

The paper introduces ECO-K, an inverse game theory framework to infer subpopulation interactions from single-cell sequencing data in TNBC, revealing frequency-dependent selection driven by karyotypic diversity.

The paper introduces CLONEID, a framework for organizing clone-resolved data to enable longitudinal genotype-to-phenotype mapping in experiments with repeated molecular and phenotypic measurements.

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

PloiViT is a transformer-based model that quantifies tumor ploidy from pathology slides, outperforming traditional methods and achieving low prediction error across multiple cancer types.

The paper models clonal interference in cancer cell lines using phenotypic data to predict growth rate and carrying capacity differences between karyotypes.

This paper introduces HEMnet, a deep learning model that transfers molecular labels from immunohistochemistry to H&E images to identify cancer cells without manual annotation.

The paper combines single cell DNA-Seq and RNA-Seq in gastric cancer to reveal subclonal genomic instability and gene expression patterns, showing evidence of tumor evolution.

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

SVEngine simulates genome structural variations with cancer clonal evolution features, producing sequence data with variants and ground truth BED files.