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The Saunders Lab aims to advance our understanding of the bacterial domain of life using high throughput genetics to map the molecular interactions that underly cellular physiology.

The main focus in our laboratory is the identification and physiological characterization of adipocyte-specific gene products and the elucidation of pathways that are an integral part of the complex set of reactions that drive adipogenesis.

What are the causes and consequences of cytoskeletal diversification?

We aim to globally understand how the physical and chemical properties of materials affect interactions with biological systems in the context of improving therapies.

We investigate epigenome regulation of nervous system development and homeostasis. We are particularly interested in understanding how disruption of these mechanisms lead to neurological disorders.

We investigate genetic and molecular basis of phenotypic diversity observed in nature by using a range of methodologies such as whole genome sequencing, fluidics, long-term evolution experiments, and large-scale combinatorial mutagenesis. 

The Tu Lab is investigating how a variety of cellular processes and decisions are coordinated with metabolic state, and how the dysregulation of these mechanisms might be linked to disease and aging.

Our research revolves around using state-of-the-art bioinformatics and biostatistics approaches to study the implications of tumor immunology for tumorigenesis, metastasis, prognosis, and treatment response in a variety of cancers.

The over-arching theme of the Weaver Lab is to deeply understand how proteolytic factors mediate diverse physiological functions.

We are interested in understanding at a cellular level the neural control of energy balance and glucose metabolism, and elucidating how these events may participate in human disease.

Wilson Lab

The long-term goal of our lab is to understand the functions of ecDNA and how ecDNA is maintained in cancer. 

Our team is interested in developing computational models to predict patient outcomes, which will allow clinicians to tailor treatment plans for individual patients.

I am interested in developing computational models and algorithms for big data to predict patients' outcomes, which can help clinicians to tailor treatment plans for individual patients.

The lab focuses on developing bioinformatics algorithms and deep learning models to identify new disease genes and therapeutic targets for human diseases, as well as development and maintenance of data management system for genomic and clinical databases.

We are interested in how metabolism regulates various behaviors. We use two invertebrate model systems of C. elegans and D. melanogaster, ultimately aiming to unveil conserved neuro-molecular mechanisms throughout animals including mammals.

The central theme of our research program in our laboratory is to explore the co-evolution between tumor cells and the tumor microenvironment (TME) during the development of therapeutic resistance and metastatic relapse.

Our lab combines normative theories and biologically plausible neural circuit models to study the principles of neural information processing, in order to answer how perception, cognition, and behavior emerge from neural circuits. 

Our aim is to develop computational methods to unveil the hidden biological circuitries behind the data, from understanding sequence-based regulations to the evolution of genomes and their impact to diseases.

Our lab is interested in understanding the relationship between injury, regeneration, and cancer. We are focused on identifying the genes and mechanisms that regulate regenerative capacity in the liver and understanding how these contribute to hepatocellular carcinoma development.