Simon Daled

This paper develops a method to identify species in mixed palaeoproteomic samples by analyzing both physical and genetic mixtures, revealing new faunal information from ancient bone fragments.

The paper constructs a multi-omics biomolecular network in AML using proteins, metabolites, and histone PTMs to reveal functional entanglement between biomolecules.

ClassiCOL improves species classification from ancient collagen LC-MS/MS data by resolving peptide ambiguity through isoBLAST and taxonomic branching analysis.

The paper presents a comprehensive benchmark dataset for evaluating label-free quantification methods across various proteomics acquisition strategies.

The paper provides a roadmap for selecting a bottom-up mass spectrometry protocol for histone analysis by comparing four methods and introducing a new enzyme.

The paper removes the dependency on DDA libraries in DIA by using predicted spectral libraries, making the workflow deterministic and improving standardization in clinical proteomics.

The paper introduces ion-networks, a data format for DIA MS that captures full data integrity by representing reproducible fragment ions and their consistent co-elution across runs.