Brown Group @ LBNL
Brown Group Research
 

Environmental & Exposure Biology, Toxicology, and Molecular Bionomics

Statistical Machine
Learning

Genome Dynamics

Exposure biology is one of the most powerful tools we can apply to study complex biological systems. In genetics, we perturb systems one gene or one genic locus at a time. In exposure biology, we use exogenous stressors to perturb entire pathways or organ systems, altering the expression of hundreds of genes. Observing adaptive and toxic responses through the lens of omics is providing new insights into levels of biological organization extending beyond individual cells or organisms, linking the biology of the nucleus to ecosystem dynamics. By developing and applying
Next generation sequencing, high-throughput structural biology, and high-throughput genome engineering have opened a host of new, foundational opportunities and challenges in the analysis of organismal, bionomic, and environmental systems. We develop new techniques, approaches, and algorithms in statistical machine learning to solve otherwise intractable problems in bioinformatics. Our principle focus is the mapping of interactions between features defined on genomes with respect to organismal or ecological traits. We work on integrating high-dimensional
Transcriptional initiation is followed by hierarchical regulation mediated by RNA binding proteins, including the rate of RNA polymerization, splice site selection, concurrent co-transcriptional chromatin modifications that enforce or re-enforce promoter and splice site selections, polyadenylation, localization, stabilization, translational initiation and so forth. Covalent modifications to RNA and protein products add layers of combinatorial complexity that radically outstrip the sophistication of extant, dynamical models of gene expression, with feedback between nearly all
innovative computational tools to the analysis of well-designed toxicological experiments, my group is working to establish exposure biology as foundational science. We view toxicology as systems-level genetics, and posit that it has a major role to play in the elucidation of processes ranging from development to speciation. Hence, the intrinsic societal values present in understanding the effects of environmental challenges on human and ecosystem health comes in addition to potentially transformative impacts on basic science. How do organisms coordinate metabolic and transcriptional responses in real time during acute insults or chronic climatological shifts? How do the adaptive responses of individuals impact populations, and what are the trans-generational consequences of punctate exposures? Nearly every cell in our bodies suffers tens of thousands of DNA damage events per day – hence, these questions regard processes that are fundamental to the nature of life, not exceptional to rare or adverse conditions. Our principle focus in this area is on leveraging longitudinal perturbation data to understand how genetic and epigenetic information is used by cells to adapt to environmental and ecosystem dynamics. Dr. Brown leads integrative analysis for the Consortium for Environmental Omics and Toxicology (CEOT) and works as part of the Microbes to Biomes Initiative.
molecular datasets, such as modENCODE, with high-content phenomics to simultaneously identify relationships between genomic information and complex phenotypes. We are leveraging phylogenomic toxicology (exposure biology in a multi-species setting) to identify gene and metabolic networks with “orthologous functions” in distantly related metazoans. This work has important implications for the future of chemical safety assessment and drug design. We are developing new tools for computational biology and statistical machine learning, including new forms of tensor regression for multi-species analysis, quantum-computing enabled pathway discovery, and “Introspective Learning Machines” (ILMs) that leverage iterative data exploration strategies to map and exploit structure in high-content datasets. Philosophically, we view dimensionality as a boon, not a curse.
processes. We focus particularly on the role of RNA binding proteins and
chromatin in co-transcriptional splicing, and the feedback from RNA and
protein-mediated splicing events and updates to chromatin state,
including work on the functions of enhancer RNAs (eRNAs). We also work
to understand translational regulation for genes encoding small open
reading frames (smORFs) and long non-coding RNAs (lncRNAs). Dr. Brown
co-chairs the RNA-Chromatin Integration Project within the ENCODE
Consortium with Dr. Roderic Guigo of the CRG.
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