Livia Perfetto

The paper uses proteomics to identify metabolic vulnerabilities in FLT3-ITD AML cells, showing lipid restriction restores midostaurin sensitivity.

This study investigates how kinase inhibitors reshape the immunopeptidome in CML by altering HLA-I peptide presentation through three molecular mechanisms.

PatientProfiler integrates multi-omic data to generate patient-specific mechanistic models and prognostic biomarkers for breast cancer.

NetworkCommons integrates prior knowledge, omics data, and network inference methods to build and evaluate context-specific biological networks.

The paper identifies BCR::ABL1-independent survival mechanisms in CML using phosphoproteomics and computational analysis, highlighting FLT3 as a therapeutic target for TKI-resistant cases.

SignalingProfiler 2.0 integrates proteogenomic data with causal networks to generate mechanistic signaling models that recapitulate drug-perturbed phenotypes in breast cancer cells.

The paper curates causal gene-protein interactions linked to autism and develops tools to explore their functional relationships with phenotypes and pathways.

The paper analyzes microRNA interactions in three rare disorders to assess data availability and annotation consistency across databases.

The paper presents a computational framework for analyzing SARS-CoV-2-host interactions to identify drug targets and model disease mechanisms.

The paper curates and expands the yeast complexome, showing increased genetic interactions and functional links among complex members.

The paper demonstrates how fine-tuning BioBERT can accurately identify functional protein links from text, improving upon conventional methods and offering guidelines for data creation.

The paper curates a dataset of physical molecular interactions between SARS-CoV-2, SARS-CoV-1, and other Coronaviridae proteins, providing a resource for studying virus-host interactions.

Myo-REG integrates and curates molecular interactions and signaling pathways involved in muscle regeneration, providing a web portal for exploring cell-cell and intracellular interactions.

The paper introduces CausalTAB, an updated format for representing causal signaling interactions, enhancing the precision and coverage of signaling network modeling.

The paper presents a dataset of 28,000 annotations describing how amino acid mutations affect protein interactions, available through the IntAct website.