Daniela Besozzi

This paper develops and validates a 9-gene Breast Cancer Purity Score to improve prognostication by accounting for tumour purity in breast cancer datasets.

SMGen generates synthetic biochemical reaction network models for benchmarking, showing it can create models with 512 species and reactions in under 7 seconds.

FiCoS is a GPU-powered deterministic simulator for biochemical networks that provides fine- and coarse-grained parallelization, achieving up to 855x speedup over CPU-based simulators.

The paper introduces scAEspy, a tool using autoencoders to improve scRNA-seq data integration and cell-type identification by outperforming existing batch-effect removal methods.

ACDC automates cell detection and counting in time-lapse microscopy images, achieving high accuracy without large annotated datasets.