Marta Belchior Lopes

The paper introduces DisTwiner, a method for subgroup-aware gene selection in scRNA-seq data, showing it captures biologically relevant aging pathways in macrophages.

This study evaluates a urinary FABP3/APOA1 ratio as a predictor of renal recovery after severe AKI, showing high accuracy in both discovery and validation cohorts.

This paper updates TCGA glioma classifications to align with WHO-2016 and WHO-2021 guidelines using molecular profiling data, achieving high reclassification rates.

This study evaluates unsupervised variable selection methods for high-dimensional omics data and introduces TRIM-IT, a tool that identifies glioblastoma subtypes with distinct molecular profiles and survival outcomes.

This study develops MINGLE, a multi-omics integration tool, to identify glioma-type-specific biomarkers by analyzing heterogeneous glioma data.

This paper uses network analysis to identify key genes and patient subgroups in gliomas, revealing molecular heterogeneity and potential biomarkers.

This study integrates multi-omics data from TCGA to classify glioma types and identify novel biomarkers using DIABLO, finding key pathways and genes associated with glioblastoma and lower-grade gliomas.

This paper introduces sparse network-based regularization for survival analysis, improving predictive performance and interpretability in breast cancer transcriptomic data.