Eric Lock, PhD
Associate Professor, Division of Biostatistics
PhD, Statistics, University of North Carolina, 2012
BA, Mathmatics, Hamilton College, 2006
Postdoctoral Associate, Statistical Genomics, Duke University, 2014
Summary
I develop methods for the analysis of multi-faceted high-dimensional data. These methods are usually motivated by applications in molecular biology, especially in "omics" fields such as genomics, metabolomics, and proteomics. My focus is in the integrated analysis of data that are from multiple sources (e.g., gene expression, metabolomics, imaging) or measured in multiple dimensions (e.g., multiple tissue types or body regions), which are often necessary to capture every facet of a complex biological system. I also have in interest in exploratory factorization and clustering methods, and Bayesian nonparametric inference.
Expertise
Statistical genomics, high-dimensional data, machine learning, data integration, systems biology, bayesian, exploratory data analysis
Awards & Recognition
Delta Omega, Honorary Society in Public Health, 2019
Research
Research Funding Grants
- 2019–2024, NIH NIGMS, "Identifying Biomarkers for Multi-Source, Multi-Way Data," Principal Investigator
- 2020-2025, NIH NHGRI, "Tensor Array Methods for RNA-Seq Analysis," Subcontract PI
- 2018-2023, NIH NHLBI, "Sphingolipids in HIV-associated Chronic Obstructive Pulmonary Disease", Co-Investigator
- 2017-2022, NIH NICHD, "Detection and Correction of Iron Deficiency Induced Abnormal Brain Metabolism", Biostatistician
- 2018–2020, NIH NCI, "Bidimensional integration for pan-omics pan-cancer analysis," Principal Investigator
- 2015–2018, NIH, "Biomarkers for Multi-Source, Multi-Way Data," Principal Investigator
- 2016–2021, NIH, "Evaluating Natural Experiments in Healthcare to Improve Diabetes Prevention and Treatment," Co-Investigator
Publications
See a full list of my publications on Google Scholar
Select Recent Publications
- Park J and Lock EF. Integrative Factorization of Bidimensionally Linked Matrices.Biometrics, 76 (1): 61-74, 2020. (link)
- Lock EF. Tensor-on-tensor regression. Journal of Computational and Graphical Statistics, 27 (3): 638-647, 2018. (link)
- Lyu T, Lock EF, Eberly LE. "Discriminating sample groups with multi-way data," Biostatistics, Jan 2017
- Lock EF, Dunson DB. "Bayesian genome- and epigenome-wide association studies with gene level dependence," Biometrics, Jan 2017
- O'Connell MJ, Lock EF. "R.JIVE for exploration of multi-source molecular data," Bioinformatics, June 2016
Books and Book Chapters
- EF Lock and AB Nobel. Exploratory methods to integrate multisource data. In GC Tseng, D Ghosh & XJ Zhou (Eds), Integrating Omics Data, pp. 242-268. Cambridge University Press, Cambridge, UK. 2015.
- RH Lock, PF Lock, KL Morgan, EF Lock, and DF Lock. Statistics: Unlocking the Power of Data. John Wiley & Sons, Hoboken, NJ, 2012.
Teaching
Courses
- PubH 7401, Fundamentals of Biostatistical Inference
- PubH 8442, Bayesian Decision Theory and Data Analysis
Media
In The News
SPH News
In The Media
- New methods will simplify biological data analysis (Minnesota Daily)