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UCLA has received a $4.6 million grant from The Warren Alpert Foundation to establish th
More than four years after the world first learned about COVID that led to an unprecedented global health crisis in modern history and upended life as we knew it, UCLA researchers behind the SwabSeq COVID-19 PCR test came together November 13 in honor of SwabSeq’s third anniversary and its milestone of reaching 2 million processed tests.
Biobanks that collect deep phenotypic and genomic data across many individuals have emerged as a key resource in human genetics. However, phenotypes in biobanks are often missing across many individuals, limiting their utility. We propose AutoComplete, a deep learning-based imputation method to impute or ‘fill-in’ missing phenotypes in population-scale biobank datasets.
Three PhD students supported by the Biomedical Data Science for Precision Health Equity training program, along with PI Professor Bogdan Pasaniuc (Computational Medicine) and Professor Alex Bui (Radiological Sciences, Bioengineering), attended the NLM T15 Training Conference, held at S
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.
Recent Biomathematics Ph.D. graduate Alexander Fisher (now an Assistant Professor at Duke) has received the Publisher's Award for Excellence in Systematic Research from The Society of Systematic Biologists. The award is presented to the two best papers based on student research published in Systematic Biology during the previous year.
Recent scientific discoveries have shown that Neanderthal genes comprise some 1 to 4% of the genome of modern non-Africans, but the question remained open on how much those genes are still actively influencing human traits — until now.
Genome-wide association studies (GWAS) are an important tool for disease mapping but are under-explored for populations of individuals with mixed genetic ancestries (admixed). This work provides guidance on method selection and shows that differences in allele frequency and/or causal effects by ancestries impact statistical power for GWAS in admixed populations.
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.