Current Projects

The Payne lab has had a significant focus in algorithms and data analysis to better understand cancer. As part of the CPTAC consortium for 10 years, we worked with proteomically and genomically characterized samples to understand how DNA mutations lead to cellular dysfunction (https://pubmed.ncbi.nlm.nih.gov/27372738/, https://pubmed.ncbi.nlm.nih.gov/32059776/, https://pubmed.ncbi.nlm.nih.gov/37582339/ ). We have leveraged this data to identify novel sources of regulation for tumors (https://pubmed.ncbi.nlm.nih.gov/40674356/). We have a strong collaborative relationship with the Huntsman Cancer Institute to understand the treatment pathways for cancer patients and how to better learn from the treatment outcomes of large synthetic cohorts.

Key Questions:

1. What mutations and proteome states are correlated with a good survival?
2. How does proteogenome measurement improve diagnosis and treatment?
3. How can we compare patients with diverse treatment pathways?

Tissues and biofluids are typically comprised of a diverse mix of cell types, each uniquely contributing to the emergent properties of the multicellular community. Even cells of the same cell type exist within distinct cellular neighborhoods and therefore feel unique environmental stimuli. Thus to understand biological states and responses to perturbation, it is critical to measure single cells. Leveraging decades of experience in proteomics algorithm development, the lab has pursued a wide variety of data analysis topics (https://pubmed.ncbi.nlm.nih.gov/36828128/) to improve protein identification and quantification in this challenging yet important data type.

Key Questions:

1. How can we improve both the depth of protein coverage and also the sample throughput of mass spectrometry based single cell proteomics?
2. How can we create and appropriately use an atlas of single cell proteomics experiments?
3. What tools are lacking to make single cell proteomics an easy and intuitive technology?

A unique part of the Brigham Young University mission is the on focus undergraduate education and experiential learning. Bioinformatics is an emerging discipline in the Life Sciences and many students haven’t been exposed and thus don’t know that it is a perfect fit for their love of life sciences and skills in math. In addition to teaching classes at BYU and mentoring a large lab of energetic undergraduates, I have tried to improve access to educational materials about bioinformatics and computational proteomics to help those around the world find the science domain that fits them best.
- Tools for proteomics (https://github.com/PayneLab/ProteomicsEducation)
- Tools for cancer bioinformatics (https://paynelab.github.io/biograder/bio462)