Alvaro Sebastian Vaca Jácome

This paper develops a mass spectrometry-based method to profile single-cell histone post-translational modifications, demonstrating its ability to detect treatment responses and chromatin heterogeneity.

The paper introduces a cloud-based implementation of the AvG algorithm for DIA data analysis, improving efficiency and accessibility for large datasets.

The paper introduces a computational method to generate causal explanations for proteomic profiles by integrating molecular data with prior biological pathway knowledge, demonstrating its application in various biological contexts.

Avant-garde improves DIA data analysis by refining signals, reducing interference, and controlling false discovery rates through a data-driven approach.

Specter improves DIA proteomics by directly deconvoluting spectra using linear algebra, enhancing sensitivity for similar peptides and challenging cases.