Hugo Tovar

The paper introduces a uniform method for inferring regulatory networks across cancer subtypes, showing it is adequate for multi-cohort analysis despite not being statistically superior.

This paper derives a metabolic cost-based model for optimal vascular tree shear stress profiles and shows how staged growth and fluctuating demand influence vascular topology.

This study uses machine learning to identify myeloid malignant transcriptional profiles in FA patients' bone marrow using scRNAseq data, achieving high sensitivity and specificity for MDS and AML detection.

The paper identifies new senescent cell anti-apoptotic pathways and senolytics using transcriptomic data and network-based methods, validating Fluorouracil's senolytic activity through multiple targets.

ExtendAlign improves alignment accuracy for dissimilar short sequences by correcting errors in existing alignments.

The paper identifies master regulators of signaling pathways in breast cancer, finding that nine of the top ten are involved in embryonic development processes.