Lincoln Harris

The paper introduces Lupine, a deep learning method for imputing missing values in TMT proteomics data, showing improved accuracy and identification of differentially expressed proteins across cancer 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 paper evaluates proteomics imputation methods using downstream-centric criteria and finds that MissForest performs best, though imputation may not improve differential expression detection.

This study uses single-cell RNA-sequencing to analyze cell type-specific responses to young or aged blood in heterochronic parabiosis, identifying mitochondrial function as a key factor in rejuvenation.