News @ Berkeley Biomedical Data Science Center

A team of scientists at Berkeley Lab has developed an unsupervised multi-scale machine learning technique that can automatically and specifically capture biomedical events or concepts directly from raw data.

Genetics and birthplace have a big effect on the makeup of the microbial community in the gut, according to research published in the journal Nature Microbiology.

The findings by a team of scientists from the Department of Energy’s Pacific Northwest National Laboratory (PNNL) and Lawrence Berkeley National Laboratory (Berkeley Lab) represent an attempt to untangle the forces that shape the gut microbiome, which plays an important role in keeping us healthy. (Related news link)

Scientists, led by Jian-Hua Mao, from the U.S. Department of Energy’s Lawrence Berkeley National Laboratory (Berkeley Lab) have uncovered new clues about the risk of cancer from low-dose radiation, which in this research they define as equivalent to 100 millisieverts or roughly the dose received from ten full-body CT scans. They studied mice and found their risk of mammary cancer from low-dose radiation depends a great deal on their genetic makeup.

Lawrence Berkeley National Laboratory (Berkeley Lab) researchers have been awarded $1.3 million for two sets of studies to better understand the health impacts of thirdhand smoke, the noxious residue that clings to virtually all indoor surfaces long after the secondhand smoke from a cigarette has cleared out. Berkeley Lab geneticist and BBDS Scientist, Jian-Hua Mao, will use a genetically diverse population of mice to investigate how components of thirdhand smoke cause genetic damage.

Berkeley Lab scientists led the development of an algorithm and a computational pipeline that analyzes large sets of tumor images. Their work will help scientists learn more about the genetic and molecular mechanisms that control tumor signatures. It will also shed light on whether tumor subtype can predict the effectiveness of therapies. The research was led by Hang Chang, Ju Han, Leandro Loss, and Bahram Parvin of the Life Sciences Division, as well as scientists from several other institutions.

Many neurological disorders, such as Parkinson’s disease and Alzheimer’s disease, are marked by impaired motor skills. In addition, growing evidence suggests there’s a link between some neurodegenerative diseases and body weight. A recent NIH study, for example, found that adults who are obese or overweight at midlife may be at risk for earlier onset of Alzheimer’s disease.

BBDS researchers in the Biological Systems and Engineering Division have developed a 12-gene score tied to the odds of relapse-free breast cancer survival. The scoring system is based on an analysis of large genomic datasets and patient
data, and it could eventually be developed for clinical use.

Researchers, led by Jian-Hua Mao, from the Lawrence Berkeley National Laboratory published a study Monday that found an overlap between genetic factors in mice that are linked to body weight and motor coordination.

Resarch team led by researchers from the Lawrence Berkeley National Laboratory has identified a new type of biomarker that may help predict prognosis and response to chemotherapy and radiation therapy for several types of cancer. The biomarker is a score based on the expression levels of a set of genes involved in partitioning chromosomes during cell division. This score, the researchers found, could identify tumors that would likely not respond to certain treatments and those that would be sensitive. The score could also predict patients’ outcomes with or without treatment.

BioSig3D is a computational platform for high-content screening of three-dimensional cell culture models that are imaged in full 3-D volume. It is primarily used for the study of aberrant organization that is typically caused by cancer. It will also enable the evaluation and quantification of the effects of perturbagens, such as radiation exposures and environmental toxins, in a more effective model system.