Lauren G. Fields

This study benchmarks four spectral prediction platforms for neuropeptidomics, finding no single model captures neuropeptide fragmentation well and highlighting the importance of neutral loss fragments and hybrid libraries.

This paper uses 12-plex DiLeu labeling to quantitatively analyze the feeding neuropeptidome across multiple tissues and timepoints in Cancer borealis, revealing distinct regulatory patterns and functional specificity of peptide variants.

The paper develops a hybrid sequencing platform to identify endogenous peptides in crustaceans, revealing novel peptides and conserved homologies across species.

The paper introduces cNPDB, a database of crustacean neuropeptides, providing annotated sequences, properties, and structural predictions to support research and cross-species studies.

EndoGenius identifies and quantifies endogenous peptides from mass spectrometry data using a pipeline for spectral library building and motif extraction.

The paper introduces a novel peptidomics framework, EndoGenius, paired with DIA-NN, to identify neuropeptides in Cancer borealis with a 100-fold increase in detection.