Wei Li (left, Ya Cui, Wenbin Ye and Jason Sheng Li

Apr 05, 2024

UC Irvine-led research team builds first tandem repeat expansions genetic reference maps

A research team led by the University of California, Irvine has built the first genetic reference maps for short lengths of DNA repeated multiple times which are known to cause more than 50 lethal human diseases, including amyotrophic lateral sclerosis, Huntington’s disease and multiple cancers.
Pedro Ortega (left), Remi Buisson (middle) and Ambrocio Sanchez (right)

Mar 18, 2024

UC Irvine-led research team discovers role of key enzymes that drive cancer mutations

A research team led by the University of California, Irvine has discovered the key role that the APOBEC3A and APOBEC3B enzymes play in driving cancer mutations by modifying the DNA in tumor genomes, offering potential new targets for intervention strategies.
person starting race on bike

Mar 13, 2024

2024 registration opens for 8th Annual UCI Anti-Cancer Challenge

The 2024 UCI Anti-Cancer Challenge will take place on Saturday, Oct. 5 for its eighth year dedicated to raising funds and awareness for critical cancer research. Registration for the annual event launched on World Cancer Day, inviting individuals to ride, run or walk in-person at UCI Aldrich Park or participate virtually.
Front of UCI Hospital

Feb 28, 2024

UCI Health named a top hospital by Newsweek

UCI Health is also recognized as a global infection prevention leader.
Chao Bldg 23

Feb 27, 2024

National Cancer Prevention Month with Dr. Alexandre Chan, Dr. Shawn Griffin, and Dr. Mahtab Jafari

Dr. Alexandre Chan, Dr. Shawn Griffin, and Dr. Mahtab Jafari are three of the many faculty members in the UC Irvine School of Pharmacy & Pharmaceutical Sciences who advance the field of cancer research and work with patients to help minimize their risk for cancer, as well as help to prevent further health issues in people who are currently fighting cancer or are cancer survivors.
headshot of min zhang and dabao zhang

Feb 21, 2024

UC Irvine co-led study that uses artificial intelligence to identify unwanted variations in blood samples by 95%

A new study led by co-corresponding authors, Min Zhang, MD, PhD, and Dabao Zhang, PhD, professors of epidemiology and biostatistics at the University of California, Irvine’s Program in Public Health, used artificial intelligence (AI) to analyze ‘big data’ sets of biological samples to reduce unwanted variations by more than 95%.