James P Brody
professor, Biomedical Engineering
The Henry Samueli School of Engineering
The Henry Samueli School of Engineering
Ph.D., Princeton University, 1994, Physics
B.S., Massachusetts Institute of Technology, 1989, Physics
B.S., Massachusetts Institute of Technology, 1989, Physics
University of California, Irvine
Natural Sciences II, Room 3111
Mail Code: 2715
Irvine, CA 92697
Natural Sciences II, Room 3111
Mail Code: 2715
Irvine, CA 92697
Research Interests
cancer, genetic risk scores
Websites
Research Abstract
The prediction of an individual's observable traits (phenotype) from their genetic makeup (genotype) is a cornerstone of personalized medicine and modern biology. However, this goal is severely hampered by the modest accuracy of current predictive tools, known as polygenic risk scores (PRS). Existing methods, which are largely based on linear models of single nucleotide polymorphisms (SNPs), have reached a performance plateau, with their predictive accuracy, as measured by the Area Under the Curve (AUC), stagnating far below theoretically possible limits. This critical limitation stems from the “big-p, little-n” (p>>n) problem, a fundamental challenge in genomics where the millions of potential genetic predictors (p) vastly outnumber the available patient samples with a given trait (n). This dimensionality barrier has, until now, precluded the effective use of powerful, non-linear machine learning (ML) models that are capable of capturing the complex, interacting (epistatic) nature of genetic architecture.
The overall goal of my research program is to develop and validate a novel, generalizable framework to dramatically increase the predictive accuracy of genetic risk scores by fundamentally re-engineering the genotype-to-phenotype problem. We are working overcome the p>>n barrier through a two-pronged strategy: (1) reducing predictor dimensionality ('p') using novel, information-rich genomic representations, and (2) augmenting sample size ('n') using biologically plausible synthetic data.
The overall goal of my research program is to develop and validate a novel, generalizable framework to dramatically increase the predictive accuracy of genetic risk scores by fundamentally re-engineering the genotype-to-phenotype problem. We are working overcome the p>>n barrier through a two-pronged strategy: (1) reducing predictor dimensionality ('p') using novel, information-rich genomic representations, and (2) augmenting sample size ('n') using biologically plausible synthetic data.
Awards and Honors
2025-2026 UCI Academic Senate Midcareer Faculty Award for Service
2025 Excellence in Digital Learning Award
2024 UC Irvine Faculty Academy for Teaching Excellence
2022 UCI Samueli School of Engineering Innovation in Teaching Midcareer Award
2025 Excellence in Digital Learning Award
2024 UC Irvine Faculty Academy for Teaching Excellence
2022 UCI Samueli School of Engineering Innovation in Teaching Midcareer Award
Short Biography
I was born and raised near Mt. Clemens, Michigan, a few miles outside of Detroit. The two most popular career choices for my high school classmates at L'Anse Creuse High were the auto industry or the military. I never knew anyone with a PhD, much less a university professor. I was unusual and had the opportunity to go to MIT to study physics. That education instilled in me a curiosity-driven mindset and a core belief in understanding problems through quantification and measurement. This perspective has been the common thread throughout my career, from a Ph.D. in experimental biophysics at Princeton to co-founding a microfluidics company at the University of Washington, then a period as a research scientist at Caltech, and to UC Irvine.
Today, my research program is driven by the conviction that revolutionary advances in computing can be applied to massive biomedical datasets to solve problems in medicine that have seen disappointingly little progress. My work focuses on two related questions: how accurately can we predict a person’s traits from their DNA alone, and whether any discernible genetic differences exist between cohorts of people. By developing and applying novel computational tools to these questions, I aim to help usher in a new era of data-driven medicine.
I joined UCI as the first faculty hire for its new Biomedical Engineering department. Being part of a founding team immersed me in the essential work of academic service. Because the department was new, needs were everywhere. I started off by writing the proposal to establish our new graduate program, which soon led to chairing the School of Engineering’s graduate committees. I have also served as the chair of our department’s and School’s undergraduate committee, and on campus-wide bodies like CORCL, SCoC, CEP, and APRB, often assuming leadership roles. This work has been incredibly rewarding, allowing me to help shape the academic and curricular infrastructure of our program while learning from amazing colleagues across the university. This experience has given me a deep appreciation for the previous UC Academic Senate leaders who built this system that we take for granted.
That same drive to build and innovate has shaped my approach to teaching. Early on I tried to benchmark my teaching by using a standard test from the physics educational literature. It was shocking how little of an effect my teaching had on a student’s knowledge of the subject and final grade. While I was going through this process, I noticed a profile in the Wall Street Journal about an alumnus of our Biomedical Engineering program. He was a highly successful engineer. I searched back through my records and found that he barely passed my class. In fact, I had emailed him suggesting he leave engineering and transfer to a different major. This led me to rethink the very definition of student success. I have moved away from a singular focus on test scores and toward a new philosophy centered on creating engaging, memorable learning experiences that could be refined using evidence of student interaction. This led me to develop a large, online general-education course centered on the question “What is biomedical engineering?” The class teaches students through a narrative history of diabetes, using documentary-style videos instead of traditional lectures. The course has reached over 20,000 students.
Today, my research program is driven by the conviction that revolutionary advances in computing can be applied to massive biomedical datasets to solve problems in medicine that have seen disappointingly little progress. My work focuses on two related questions: how accurately can we predict a person’s traits from their DNA alone, and whether any discernible genetic differences exist between cohorts of people. By developing and applying novel computational tools to these questions, I aim to help usher in a new era of data-driven medicine.
I joined UCI as the first faculty hire for its new Biomedical Engineering department. Being part of a founding team immersed me in the essential work of academic service. Because the department was new, needs were everywhere. I started off by writing the proposal to establish our new graduate program, which soon led to chairing the School of Engineering’s graduate committees. I have also served as the chair of our department’s and School’s undergraduate committee, and on campus-wide bodies like CORCL, SCoC, CEP, and APRB, often assuming leadership roles. This work has been incredibly rewarding, allowing me to help shape the academic and curricular infrastructure of our program while learning from amazing colleagues across the university. This experience has given me a deep appreciation for the previous UC Academic Senate leaders who built this system that we take for granted.
That same drive to build and innovate has shaped my approach to teaching. Early on I tried to benchmark my teaching by using a standard test from the physics educational literature. It was shocking how little of an effect my teaching had on a student’s knowledge of the subject and final grade. While I was going through this process, I noticed a profile in the Wall Street Journal about an alumnus of our Biomedical Engineering program. He was a highly successful engineer. I searched back through my records and found that he barely passed my class. In fact, I had emailed him suggesting he leave engineering and transfer to a different major. This led me to rethink the very definition of student success. I have moved away from a singular focus on test scores and toward a new philosophy centered on creating engaging, memorable learning experiences that could be refined using evidence of student interaction. This led me to develop a large, online general-education course centered on the question “What is biomedical engineering?” The class teaches students through a narrative history of diabetes, using documentary-style videos instead of traditional lectures. The course has reached over 20,000 students.
Publications
James P Brody, Engagement and Demographics in an Online General Education Course in Biomedical Engineering ASME Open J. Engineering ASME. January 2025 4 044502.
Yasaman Fatapour and James P Brody, Improved breast cancer risk prediction using chromosomal-scale length variation. Hum Genomics 19, 65 (2025).
Yasaman Fatapour and James P Brody, “A compact encoding of the genome suitable for machine learning prediction of traits and genetic risk scores,” BioData Mining 18, 44 (2025).
Kamran A. Ali, Reecha D. Shah, Anukriti Dhar, Nina M. Myers, Cameron Nguyen, Arisa Paul, Jordan E. Mancuso, A. Scott Patterson, James P. Brody, and Diane Heiser, “Ex Vivo Discovery of Synergistic Drug Combinations for Hematologic Malignancies,” SLAS Discovery, 29:2, 2024.
Kalan Leaks, Trina Norden-Krichmar, and James P. Brody, “Predicting Moderate Drinking Behaviors in NHANES Participants using Biochemical and Demographical Factors with Automated Machine Learning,” Alcohol, 113:1, 2023.
Charmeine Ko and James P Brody, “A Genetic Risk Score Using Human Chromosomal-Scale Length Variation Can Predict Breast Cancer,” Human Genomics 17. (53) 2023.
Yasaman Fatapour, Arash Abiri, Edward Kuan, James P Brody, “Development of a supervised machine learning model to predict locoregional reappearance of oral tongue squamous cell carcinoma,” Cancers 2023 15(10), 2769.
Yasaman Fatapour and James P. Brody. “Genetic Risk Scores and Missing Heritability in Ovarian Cancer,” Genes 2023, 14(3), 762; https://doi.org/10.3390/genes14030762
Christopher Toh and James P. Brody, “A genetic risk score using human chromosomal-scale length variation can predict schizophrenia“. Sci Rep 11, 18866 (2021).
James P. Brody, “Insulin was discovered 100 years ago – but it took a lot more than one scientific breakthrough to get a diabetes treatment to patients,” ASBMB Today August 2021. Originally written for The Conversation, then syndicated through AP news. The article also appeared on many other sites including: Yahoo News, and Sina Technology (translated to Mandarin)
James P. Brody, “Comment on ‘comparative analysis of triple-negative breast cancer transcriptomics of Kenyan, African American and Caucasian women’ by Saleh et al.,” Translational Oncology, 2021 Sep; 14(0):101164 (2021).
Charmeine Ko and James P. Brody, “A genetic risk score for glioblastoma multiforme based on copy number variations,” Cancer Treat Res Commun., 27:100352 (2021).
Christopher Toh and James P. Brody, “Genetic risk score for ovarian cancer based on chromosomal-scale length variation,” BioData Min. Mar 9; 14(1):18 (2021).
Christopher Toh and James P. Brody, “Evaluation of a genetic risk score for severity of COVID-19 using human chromosomal-scale length variation,” Human Genomics 14:36 (2020).
Chris Toh and James P. Brody, “Applications of Machine Learning in Healthcare” Chapter 4 in Smart Manufacturing – When Artificial Intelligence Meets the Internet of Things, IntechOpen, 2020.
Buyung Zhang and James P Brody, “Artificial Intelligence,” Chapter 14 in Engineering-Medicine: Principles and Applications of Engineering in Medicine, CRC Press, 2019. https://doi.org/10.1201/9781351012270
Chris Toh and James P. Brody, “Analysis of copy number variation from germline DNA can predict individual cancer risk,” doi: https://doi.org/10.1101/303339, 2018.
Trevor Sughrue, Michael A. Swiernik, Yang Huang and James P. Brody, “Laboratory tests as short-term correlates of stroke,” BMC Neurology (2016) 16:112.
Trevor Sughrue and James P. Brody, “Breast tumor laterality in the United States depends upon the country of birth, but not race,” PLoS One 9 (8) 2014.
James P. Brody, “The age-specific incidence anomaly suggests that cancers originate during development.” Biophysical Review and Letters, 1-12, 2014.
Yager; Paul; Weigl; Bernhard H.; Brody; James P.; Holl; Mark R. US Patent No. 5,716,852 Microfabricated diffusion based chemical sensor, February 10, 1998.
Brody, James P. US Patent No. 5,726,404 Valveless liquid microswitch, March 10, 1998.
Brody, James P.; and Osborn, Thor D. US Patent No. 5,922,210 Tangential flow planar microfabricated fluid filter and method of using thereof,July 13, 1999.
Yager; Paul; Brody; James P.; Holl; Mark R.; Forster; Fred K.; Galambos; Paul C.; US Patent No. 5,932,100, Microfabricated differential extraction device and method, August 3, 1999.
Yager; Paul; Brody; James P.; US Patent No. 5,971,158 Absorption-enhanced differential extraction device,October 26, 1999.
Weigl; Bernhard H.; Yager; Paul; Brody; James P.; Holl; Mark R.; Kenny; Margaret; Schutte; David; Hixson; Gregory; Zebert; Diane; Kamholz; Andrew; Wu; Caicai, Altendorf, Eric. US Patent No. 5,972,710, Microfabricated diffusion based chemical sensor,October 26, 1999.
Weigl; Bernhard H.; Yager; Paul; Brody; James P. US Patent No. 6,159,739 Device and method for 3-dimensional alignment of particles in microfabricated flow channels, December 12, 2000.
Brody, James P.; and Osborn, Thor D. US Patent No. 6,387,290 Tangential flow planar microfabricated fluid filter, May 14, 2002.
Weigl; Bernhard H.; Yager; Paul; Brody; James P.; Holl; Mark R.; Forster; Fred K. ; Altendorf; Eric; Galambos; Paul C.; Kenny; Margaret; Schutte; David; Hixson; Gregory; Zebert; Diane; Kamholz; Andrew; Wu; Caicai US Patent No. 6,454,945 Microfabricated Devices and Methods, September 24, 2002.
Quake; Stephen R. and Brody, James P. US Patent No. 6,614,598 Microlensing particles and applications.September 2, 2003.
Yager, Paul and Brody, James P. US Patent No. 6,695,147, Absorption Enhanced Differential Extraction Device, February 24, 2004.
Quake; Stephen R., van Dam, Michael, Brody, James P. and Shafee, Rebecca. US Patent No. 6,947,846 Non metric tool for predicting gene relationships from expression data.September 20, 2005.
Quake; Stephen R. and Brody, James P. US Patent No. 6,958,865 Microlicensing particles and applications.October 25, 2005.
Quake; Stephen R and Brody, James P. US Patent No. 7,248,413 Microlensing particles and applications.July 24, 2007.
Yasaman Fatapour and James P Brody, Improved breast cancer risk prediction using chromosomal-scale length variation. Hum Genomics 19, 65 (2025).
Yasaman Fatapour and James P Brody, “A compact encoding of the genome suitable for machine learning prediction of traits and genetic risk scores,” BioData Mining 18, 44 (2025).
Kamran A. Ali, Reecha D. Shah, Anukriti Dhar, Nina M. Myers, Cameron Nguyen, Arisa Paul, Jordan E. Mancuso, A. Scott Patterson, James P. Brody, and Diane Heiser, “Ex Vivo Discovery of Synergistic Drug Combinations for Hematologic Malignancies,” SLAS Discovery, 29:2, 2024.
Kalan Leaks, Trina Norden-Krichmar, and James P. Brody, “Predicting Moderate Drinking Behaviors in NHANES Participants using Biochemical and Demographical Factors with Automated Machine Learning,” Alcohol, 113:1, 2023.
Charmeine Ko and James P Brody, “A Genetic Risk Score Using Human Chromosomal-Scale Length Variation Can Predict Breast Cancer,” Human Genomics 17. (53) 2023.
Yasaman Fatapour, Arash Abiri, Edward Kuan, James P Brody, “Development of a supervised machine learning model to predict locoregional reappearance of oral tongue squamous cell carcinoma,” Cancers 2023 15(10), 2769.
Yasaman Fatapour and James P. Brody. “Genetic Risk Scores and Missing Heritability in Ovarian Cancer,” Genes 2023, 14(3), 762; https://doi.org/10.3390/genes14030762
Christopher Toh and James P. Brody, “A genetic risk score using human chromosomal-scale length variation can predict schizophrenia“. Sci Rep 11, 18866 (2021).
James P. Brody, “Insulin was discovered 100 years ago – but it took a lot more than one scientific breakthrough to get a diabetes treatment to patients,” ASBMB Today August 2021. Originally written for The Conversation, then syndicated through AP news. The article also appeared on many other sites including: Yahoo News, and Sina Technology (translated to Mandarin)
James P. Brody, “Comment on ‘comparative analysis of triple-negative breast cancer transcriptomics of Kenyan, African American and Caucasian women’ by Saleh et al.,” Translational Oncology, 2021 Sep; 14(0):101164 (2021).
Charmeine Ko and James P. Brody, “A genetic risk score for glioblastoma multiforme based on copy number variations,” Cancer Treat Res Commun., 27:100352 (2021).
Christopher Toh and James P. Brody, “Genetic risk score for ovarian cancer based on chromosomal-scale length variation,” BioData Min. Mar 9; 14(1):18 (2021).
Christopher Toh and James P. Brody, “Evaluation of a genetic risk score for severity of COVID-19 using human chromosomal-scale length variation,” Human Genomics 14:36 (2020).
Chris Toh and James P. Brody, “Applications of Machine Learning in Healthcare” Chapter 4 in Smart Manufacturing – When Artificial Intelligence Meets the Internet of Things, IntechOpen, 2020.
Buyung Zhang and James P Brody, “Artificial Intelligence,” Chapter 14 in Engineering-Medicine: Principles and Applications of Engineering in Medicine, CRC Press, 2019. https://doi.org/10.1201/9781351012270
Chris Toh and James P. Brody, “Analysis of copy number variation from germline DNA can predict individual cancer risk,” doi: https://doi.org/10.1101/303339, 2018.
Trevor Sughrue, Michael A. Swiernik, Yang Huang and James P. Brody, “Laboratory tests as short-term correlates of stroke,” BMC Neurology (2016) 16:112.
Trevor Sughrue and James P. Brody, “Breast tumor laterality in the United States depends upon the country of birth, but not race,” PLoS One 9 (8) 2014.
James P. Brody, “The age-specific incidence anomaly suggests that cancers originate during development.” Biophysical Review and Letters, 1-12, 2014.
Yager; Paul; Weigl; Bernhard H.; Brody; James P.; Holl; Mark R. US Patent No. 5,716,852 Microfabricated diffusion based chemical sensor, February 10, 1998.
Brody, James P. US Patent No. 5,726,404 Valveless liquid microswitch, March 10, 1998.
Brody, James P.; and Osborn, Thor D. US Patent No. 5,922,210 Tangential flow planar microfabricated fluid filter and method of using thereof,July 13, 1999.
Yager; Paul; Brody; James P.; Holl; Mark R.; Forster; Fred K.; Galambos; Paul C.; US Patent No. 5,932,100, Microfabricated differential extraction device and method, August 3, 1999.
Yager; Paul; Brody; James P.; US Patent No. 5,971,158 Absorption-enhanced differential extraction device,October 26, 1999.
Weigl; Bernhard H.; Yager; Paul; Brody; James P.; Holl; Mark R.; Kenny; Margaret; Schutte; David; Hixson; Gregory; Zebert; Diane; Kamholz; Andrew; Wu; Caicai, Altendorf, Eric. US Patent No. 5,972,710, Microfabricated diffusion based chemical sensor,October 26, 1999.
Weigl; Bernhard H.; Yager; Paul; Brody; James P. US Patent No. 6,159,739 Device and method for 3-dimensional alignment of particles in microfabricated flow channels, December 12, 2000.
Brody, James P.; and Osborn, Thor D. US Patent No. 6,387,290 Tangential flow planar microfabricated fluid filter, May 14, 2002.
Weigl; Bernhard H.; Yager; Paul; Brody; James P.; Holl; Mark R.; Forster; Fred K. ; Altendorf; Eric; Galambos; Paul C.; Kenny; Margaret; Schutte; David; Hixson; Gregory; Zebert; Diane; Kamholz; Andrew; Wu; Caicai US Patent No. 6,454,945 Microfabricated Devices and Methods, September 24, 2002.
Quake; Stephen R. and Brody, James P. US Patent No. 6,614,598 Microlensing particles and applications.September 2, 2003.
Yager, Paul and Brody, James P. US Patent No. 6,695,147, Absorption Enhanced Differential Extraction Device, February 24, 2004.
Quake; Stephen R., van Dam, Michael, Brody, James P. and Shafee, Rebecca. US Patent No. 6,947,846 Non metric tool for predicting gene relationships from expression data.September 20, 2005.
Quake; Stephen R. and Brody, James P. US Patent No. 6,958,865 Microlicensing particles and applications.October 25, 2005.
Quake; Stephen R and Brody, James P. US Patent No. 7,248,413 Microlensing particles and applications.July 24, 2007.
Link to this profile
https://faculty.uci.edu/profile/?facultyId=5018
https://faculty.uci.edu/profile/?facultyId=5018
Last updated
10/21/2025
10/21/2025