Simion D. Kreimer

This paper evaluates the use of HTA protease in combination with trypsin for proteomic analysis, showing increased protein and modification identifications and improved quantification.

This paper uses single-cell proteomics to identify novel cell phenotypes in Marfan mouse aorta, revealing sex differences and angiotensin signaling roles in aneurysm formation.

The paper identifies 70 extracellular proteins interacting with AMPARs during synaptic plasticity, showing OBCAM and NTM regulate AMPAR mobility.

This study profiles the proteome of ovarian cancer tumors before and after chemotherapy, revealing how HRD status affects immune pathways and identifies potential therapeutic targets.

This paper develops a rapid proteomics method using HTA protease and LC-MS to quantify blood biomarkers in under an hour.

This paper uses machine learning to differentiate between descending thoracic aortic diseases using plasma proteomic data, identifying key proteins and pathways associated with each condition.

This study adapts high-field asymmetric ion mobility spectrometry (FAIMS) coupled with mass spectrometry to improve cardiac muscle proteome coverage with reduced sample handling and processing time compared to traditional methods.

This study evaluates imputation methods for proteomic datasets, finding that local and global methods perform best in different contexts and that fragment-level imputation improves accuracy.

The paper identifies mitochondrial respiratory chain complex I and quality control dysregulation in TAZ-deficient cells and shows partial remediation via cardiolipin modulation.