Michael J. MacCoss

The paper develops a deep learning-enhanced fragment ion indexing method to reduce memory usage in tandem mass spectrometry searches while maintaining search accuracy and speed.

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.

The paper shows that FABP1 affects CYP2C9-mediated drug metabolism in human liver models, improving prediction accuracy when included in physiologically based models.

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

Bromo, a pairwise transformer, ranks a protein's peptide precursors by expected mass spectrometry response, beating XGBoost, PREGO and PeptideRanger on held-out yeast data, and can be fine-tuned per instrument.

This study shows that reducing huntingtin in the liver causes inflammation and damage, highlighting safety concerns for HTT-lowering therapies.

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.

This study revisits resonance-excitation collision-induced dissociation (reCID) for DIA proteomics, showing it can achieve performance comparable to HCD with optimized settings and libraries.

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.

Carafe2 generates high-quality in silico spectral libraries for timsTOF DIA proteomics by fine-tuning deep learning models on DIA data, outperforming DDA-trained models in multiple applications.

This study compares the effects of two IL-6 inhibitors on serum extracellular vesicles using proteomics, finding distinct protein pathway alterations.

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 develops scalable targeted proteomics assays using the Stellar mass spectrometer for analyzing biofluids, demonstrating high sensitivity and multiplexing capabilities.

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 paper evaluates a prototype Orbitrap Astral Zoom mass spectrometer for quantitative proteomics, showing improved performance in ion detection and quantitative precision compared to the standard Orbitrap Astral MS.

This study shows that Kif9 regulates centriolar satellite positioning and mitotic progression by affecting centrosome maturation and proteostasis.

The paper investigates how knocking out the doublesex gene in Drosophila affects metabolomic differences between sexes, finding that dsx significantly influences sex-specific metabolites across tissues.

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.

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 determines the structure of the human E3 ligase SIFI, revealing its mechanism for ubiquitinating multiple substrates to silence the integrated stress response.

The paper demonstrates using data-independent acquisition (DIA) to select peptides for targeted proteomics assays, achieving comparable quantitative precision to existing methods.

The paper develops a method to assess solution properties of designed proteins using mass spectrometry and peptide barcoding, enabling analysis of large protein libraries.

The paper introduces a new MS platform with enhanced acquisition rates and real-time chromatogram alignment, enabling high multiplex targeted proteomics with improved sensitivity and throughput.

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

The paper shows that a second X chromosome in aging mice improves cognition, with female gonads and sex chromosomes contributing to cognitive resilience.