A team of scientists has developed an unsupervised multi-scale machine learning technique that can automatically and specifically capture biomedical events or concepts directly from raw data. They have initiated the multi-disciplinary platform: Berkeley Biomedical Data Science Center (BBDS), which aims at facilitating and nurturing data-intensive biomedical science. They will apply this technique to three ongoing projects related to cancer risk assessment and diagnosis, as well as personalized medicine.
Biosciences Area FY17 LDRD Projects
The projects of 13 Biosciences Area scientists and engineers received funding through the FY17 Laboratory Directed Research and Development (LDRD) program. The funded projects cover a broad range of topics including the study of microbiomes in relation to their environment, plants, and gut health; catalysis for solar conversion to energy; and genomic expression in tissue. Among them were three projects related to Lab-wide initiatives. Together, these efforts account for 17.5% of the $25.2 million allocated. Lab-wide, a total of 88 projects were selected from a field of 166 proposals.
Genes, Early Environment Sculpt the Gut Microbiome
Researchers from Berkeley Lab’s Biological Systems & Engineering (BSE) Division and the Department of Energy’s Pacific Northwest National Laboratory found that genes and early environment play big roles in shaping the gut microbiome. The microbes retained a clear “signature” formed where the mice were first raised, and the characteristics carried over to the next generation. The findings, published on November 28 in the journal Nature Microbiology, could potentially be used to develop designer diets optimized to an individual’s microbiome.
The BSE research team included first author Antoine Snijders, corresponding author Jian-Hua Mao, and Sasha Langley. Read more on the Berkeley Lab News Center.
Study Finds Potential New Biomarker for Cancer Patient Prognosis
A new study, led by Gary Karpen of the Biological Systems & Engineering (BSE) Division, links the overexpression of 14 genes related to cell division to cancer patients’ prognosis and response to specific treatments. The researchers said the findings, published today in the journal Nature Communications, could lead to a new biomarker for the early stages of tumor development. The information obtained could help reduce the use of cancer treatments that have a low probability of helping.
The research team included lead author Weiguo Zhang and Jian-Hua Mao of BSE; collaborators Wei zhu and Anshu Jain; and Ke Liu and James (Ben) Brown of the Environmental Genomics & Systems Biology Division. Read more on the Berkeley Lab News Center.
Genetic Factors That Influence Body Weight, Neurological Disorders Identified
A new study has identified genetic factors that influence motor performance and body weight in a genetically diverse group of mice. The Lab researchers also found the genes identified in the mice overlap significantly with genes related to neurological disorders and obesity in people. Jian-Hua Mao and Antoine Snijders in the Biological Systems and Engineering Division led the Biosciences research team, which included colleagues in their division (Sasha Langley, Yurong Huang, Michael Hang, Kristofer Bouchard, and Gary Karpen) and the Environmental Genomics and Systems Biology Division (Susan Celniker and Ben Brown). Read more at the Berkeley Lab News Center.
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