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Announcing the Data Science in Biomedicine MS program

The Department of Computational Medicine is pleased to announce a new online, self-supporting graduate program called the Master of Science in Data Science in Biomedicine. The program will combine foundational training in all areas of data science including machine learning, statistics, data mining, algorithms and analytics with understanding of application areas including genomics, medical imaging, and analysis of electronic health records as well as other types of medical data (wavefor

Walsh Awards Seminar - May 15 at 12 pm

Please join us on May 15 for the prestigious, honorary John H. Walsh Young Investigators Research Prize Seminar.

Dr. Valerie A. Arboleda presents her research on Unraveling the Influence of Genetics in Human Disease.

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Dr. Weizhe Hong presents his research on Understanding the Social Brain.

Monday, May 15, 2023
Noon to 1:15 pm
NRB Auditorium

Lunch is provided after the seminar for all those who register for in-person attendance:

Jingyi Jessica Li is the 2023 recipient of the Overton Prize

The Overton Prize recognizes the research, education, and service accomplishments of early to mid-career scientists who are emerging leaders in computational biology and bioinformatics. The Overton Prize was instituted in 2001 to honor the untimely loss of G. Christian Overton, a leading bioinformatics researcher and a founding member of the ISCB Board of Directors.

Computational Medicine Faculty Continues to Grow

Computational Medicine continues to expand its faculty by recruiting professors with primary appointments in other departments and recent PhDs as Assistant Adjunct Professors. The new faculty complement the research of our current faculty and students and contribute to the community by serving on committees and participating in CGSI and other activities. Their affiliation with Comp Med also supports collaboration across disciplines, departments, and schools.

Next-generation statistical simulator gives medical and biological researchers a benchmarking tool capable of closely mimicking single-cell and spatial genomics data

David Sampson | dsampson@mednet.ucla.edu

UCLA researchers have developed an “all-in-one,” next-generation statistical simulator capable of assimilating a wide range of information to generate realistic synthetic data and provide a benchmarking tool for medical and biological researchers who use advanced technologies to study diseases and potential therapies. Specifically, the new computer-modeling – or “in silico” – system can help researchers evaluate and validate computational methods.

UCLA study shows accuracy of genetically based disease predictions varies from individual-to-individual

David Sampson | DSampson@mednet.ucla.edu

Polygenic scores – estimates of an individual’s predisposition for complex traits and diseases – hold promise for identifying patients at risk of disease and guiding early, personalized treatments, but UCLA experts found the scores fail to account for the wide range of genetic diversity across individuals in all ancestries.

UCLA biobank study reveals disease risk, health care use among LA’s diverse population

A new study of UCLA Health’s large genetic biobank is giving researchers new insights into the disease risks faced by the region’s diverse communities and their access to health care. The effort, published in Nature Medicine, may prove useful in developing personalized medicine and treatment approaches to groups often overlooked by the medical system.

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