Attendees are required to wear masks regardless of vaccination status
Microbes dominate life on Earth. Understanding the environment-specific microbial molecular functionality is, therefore, a critical challenge for the analysis of microbiome behavior and response to stimuli such as dietary or climate changes. Using available state-of-the-art techniques, we showed that different environments, whether diseased host gut or seasonal terrestrial changes, display unique microbial functional signatures. We further developed a model of the bacterial language of life, which allows embedding metagenomic read data for multiple downstream tasks and analyses. Embedding distances, for example, correspond to the differences in environmental niches from which metagenomes were sampled. Furthermore, models using read embeddings can annotate metagenome molecular functionality, highlighting genes that likely carry out known functions via novel sequence. Our LookingGlass language model is thus a promising starting point for more in-depth exploration of the prokaryotic living space.
Dr. Yana Bromberg received her Bachelor’s degrees in Biology and Computer Sciences from the State University of New York at Stony Brook and a Ph.D. in Biomedical Informatics from Columbia University, New York. She is currently a Professor in the Department of Biochemistry and Microbiology and an adjunct Professor int the Department of Genetics at Rutgers University. She is also a fellow of the Institute for Advanced Study at the Technical University of Munich, Germany and the vice-president of the Board of Directors of the International Society for Computational Biology (ISCB).
Dr. Bromberg is known for her seminal work on a machine learning-based method for screening for effects of genetic variation (SNAP). This work has led to Dr. Bromberg’s current interests in the analyses of human genomes and associated microbial metagenomes for disease predisposition. Broadly, research in the Bromberg lab is focused on the molecular functional annotation of genes, genomes, and metagenomes in the context of specific environments and diseases. The lab also studies evolution of life’s electron transfer reactions in Earth’s history and as potentially applicable to other planets.
The newest lab contribution to science is Ava,Dx, a machine learning-based method for analyzing Crohn’s Disease genomic determinants. The lab’s microbiome analysis tool, mi-faser, is also recent and quickly becoming popular with over 19,000 hits since its 2017 publication. Dr. Bromberg's work has been recognized by several awards, including the NSF CAREER award, the Rutgers Board of Trustees Research fellowship for Scholarly Excellence, the PhRMA foundation young investigator research starter award, and the Hans-Fischer award for outstanding early career scientists. This work has been funded by various agencies including the NSF, NIH, NASA, and a number of private foundations. Dr. Bromberg is frequently invited to talk about her research in conferences all over the world and has, to-date, co-authored over 80 peer reviewed scientific articles.