Laboratory of Computational Proteomics


A plot suggesting a comparison of histograms for identification

Mass spectrometry based proteomics is widely used in biological research. We develop methods for protein identification, quantitation, and for validation of the results, including algorithms for for finding and integrating mass spectrometric peptide peaks, detecting interference to obtain a robust measure of the amount of proteins present in samples, searching protein sequence collections and spectral libraries as well as validation of the results using expectation values, rho-diagrams, and spectrum databases.

We develop computational methods for integration of genomics, transcriptomics, proteomics and metabolomics data within the NCI funded Clinical Proteomic Tumor Analysis Consortium (CPTAC) and NYU Cancer Institute. In these projects we develop methods for analysis, integration and visualization of multi-omics tumor data to gain understanding of cancer biology and to discover and verify biomarkers for guiding treatment.

A heatmap showing how integrative data can be visualized and analyzed
A plot showing simulated data compared to experimental data

Modeling and Simulation of biological systems. We develop models of biological systems and use computer simulations to test the models and compare them to experimental data.