Michael E. Riffle

The paper introduces the Findings Workflow, a framework that enhances reproducibility and trust in LLM-assisted scientific analysis by structuring the process with provenance tracking and collaborative features.

CasanovoGUI provides a user-friendly desktop interface for Casanovo, a deep learning model for de novo peptide sequencing, simplifying setup and result interpretation.

Mass spectrometry of Mag-Net-enriched plasma extracellular vesicles from 86 C57BL/6J mice reveals 272 age-correlated proteins, sex-divergent trajectories, and an age clock with 2.75-month mean absolute error.

This study maps phosphorylation and oxidation changes across the spatiotemporal gradient of the pig lens using proteomic analysis.

The paper presents two large-scale proteomics datasets from mice exposed to varying X-ray doses and time points, enabling biomarker discovery and machine learning applications for radiation exposure assessment.

The paper identifies age-related molecular changes in mouse spleens using proteomics and transcriptomics, showing cell-type-specific remodeling and gender differences in post-transcriptional buffering.

This study presents a comprehensive proteomic dataset of human omental and subcutaneous adipose tissue across a wide BMI range to uncover depot-specific biological changes associated with adiposity.

This study investigates whether protein quantification and physical normalization are necessary in proteomics by comparing normalized and unnormalized sample inputs, showing that computational normalization can reduce variability in some cases.

The paper improves Casanovo, a deep learning de novo peptidesequencer, by enhancing interpretability, generalizing its use in database search, speeding up performance, and adding tools for adoption and result interpretation.

Carafe generates high-quality in silico spectral libraries for DIA proteomics by training deep learning models directly on DIA data, improving fragment ion intensity prediction and peptide detection.

This study identifies ATRN and ATRNL1 as transmembrane adapters that recruit MGRN1 to ubiquitinate and degrade MC1R and MC4R, expanding the known substrate repertoire of MGRN1.

This paper evaluates FDR control in mass spectrometry proteomics tools, finding that none consistently control FDR at the peptide level in DIA data, especially for single-cell datasets.

The paper shows that centromeric DNA sequences enhance force transmission through the inner kinetochore via the Okp1/Ame1 complex.

This paper introduces a method to improve quantitation in DIA proteomics by imputing peptide retention time boundaries, leading to more accurate quantifications and better estimation of radiation exposure.

This study identifies molecular biomarkers of coral resilience to thermal bleaching by comparing proteomic, microbiome, and physiological traits of surviving and dying corals.

The paper describes a high-resolution microbial metagenome dataset collected over 22 days during a phytoplankton bloom cycle, including gene abundances and time-matched environmental data.

The paper introduces a framework for quality control in quantitative proteomics, combining internal and external QC measures with tools for data analysis and deposition.

This paper introduces a workflow for improved XL-MS data analysis using PASEF, integrating MeroX and Skyline for better identification of cross-linked products.

This paper evaluates six metaproteomics tools for functional annotation using GO terms, finding differences in sensitivity and specificity, and integrates two into Galaxy for broader accessibility.