Giulia Calia

HIVE integrates single-stress transcriptomics data to identify gene signatures responding to multifactorial stress combinations in plants.

The paper introduces MOnSTER, a tool for clustering and scoring protein sequence motifs, and applies it to identify specific motifs in plant-parasitic nematode effectors.

The paper introduces LEAPH, a machine learning tool for predicting phytoplasma effector proteins, and EffectorComb, an app for analyzing these predictions, identifying 2089 putative effectors across 13 proteomes.