Dr. Labus is an Adjunct Professor in the Vatche and Tamar Manoukian Division of Digestive Diseases in the Department of Medicine at University of California, Los Angeles (UCLA). She is the Director of the Integrative Biostatistics and Bioinformatics Core in the G. Oppenheimer Center for Neurobiology of Stress at UCLA and the UCLA Brain-Gut-Microbiome Center.
Dr Labus is a biostatistician with expertise in biostatistics, bioinformatics, treatment-outcome research, pain neuroscience, multimodal brain imaging, microbiome, metabolomics, and multi-omics integrative analysis. Her current research focused is on determining biological markers of disease, including chronic pain, obesity and Alzheimer’s disease. Using state-or-the-art computational, biostatistical, and bioinformatics approaches, she assesses the interaction between various levels of biological data (e.g., microbiome, metabolomics, immune markers, multimodal brain imaging data) with clinical data. The overall goal of her systems-based approach is to identify and target the key regulators of multi-omics-biological disease-interaction networks in order to understand the underlying pathophysiological mechanisms and provide new targets for treatment.
Dr. Labus is an Adjunct Professor in the Vatche and Tamar Manoukian Division of Digestive Diseases in the Department of Medicine at University of California, Los Angeles (UCLA). She is the Director of the Integrative Biostatistics and Bioinformatics Core in the G. Oppenheimer Center for Neurobiology of Stress at UCLA and the UCLA Brain-Gut-Microbiome Center.
Dr Labus is a biostatistician with expertise in biostatistics, bioinformatics, treatment-outcome research, pain neuroscience, multimodal brain imaging, microbiome, metabolomics, and multi-omics integrative analysis. Her current research focused is on determining biological markers of disease, including chronic pain, obesity and Alzheimer’s disease. Using state-or-the-art computational, biostatistical, and bioinformatics approaches, she assesses the interaction between various levels of biological data (e.g., microbiome, metabolomics, immune markers, multimodal brain imaging data) with clinical data. The overall goal of her systems-based approach is to identify and target the key regulators of multi-omics-biological disease-interaction networks in order to understand the underlying pathophysiological mechanisms and provide new targets for treatment.