Author Biographies

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Cristina Correia is an Assistant Professor in the Department of Molecular Pharmacology and Experimental Therapeutics at Mayo Clinic and works with Dr. Li's team in Systems Biology and Dr. Kaufmann's team in Ovarian Cancer, Lymphoma, and drug resistance mechanisms. Dr. Correia's research focuses on the fundamental problems that affect most patients during the management of disease: heterogeneous responses to treatment, drug resistance, and acquired drug resistance that arises under the selective pressure of therapy. Specifically, she focuses on applied systems biology approaches using machine learning and artificial intelligence models to identify new makers of drug response, with a desire to translate these findings as quickly as possible into clinical practice. Dr. Correia's extensive work addresses cancer and drug mechanisms, omics, and omics integration (RNA sequencing, Whole Exome Sequencing, Methylation arrays, SNP arrays, RPPA, proteomics, SNP arrays, RPPA, genome-wide shRNA and CRISPR screens, single-cell omics). Dr. Correia is an expert in network biology and the development of innovative network tools, using machine learning and artificial intelligence system tools to dissect cancers and aging diseases like NetDecoder, P-Map, RSI, PERMUTOR, and recently using the artificial neural network encoder (ANNE) and the invariant stoichiometric gene associations LIFE and SPIN-AI (submitted).
Choong Yong Ung is an Assistant Professor at Mayo Clinic with more than 20 years of experience in developing algorithms in the areas of bioinformatics, systems biology, and Artificial Intelligence (AI). He obtained his BSc at the University of Malaya, Malaysia, and PhD at the National University of Singapore. His early research focused on developing machine learning algorithms to characterize the pharmacological properties of drugs. Since 2013, after joining Hu Li's lab, his research has aimed to uncover the systems mechanisms that govern the genotype-phenotype interactions that shape emergent properties in biological phenotypes, including complex disease traits and drug response phenotypes.
Shizhen Zhu, M.D., Ph.D., is a biomedical researcher who is particularly motivated by work that has the potential to improve public health by advancing our understanding of cancer for the eventual development of improved therapeutics. She obtained her Ph.D. in Cell Signaling and Developmental Biology at the Department of Biological Sciences, National University of Singapore. Dr. Zhu's laboratory utilizes a functional genomics approach and a robust zebrafish model system to explore how findings emerging from integrative genomic studies contribute to the pathogenesis of neuroblastoma and different types of cancers and to translate the knowledge gained from experimental studies into effective therapies for these malignancies.
Daniel D Billadeau, Ph.D., has a long-standing research interest in understanding the mechanisms that regulate the activation of cytotoxic T cells and natural killer (NK) cells, with a specific focus on the proteins involved in cell-mediated killing and the release of lytic granules from these two effector cell populations. In addition, Dr. Billadeau's laboratory is focused on identifying proteins that contribute to cancer development, in particular pancreatic adenocarcinoma, which can be targeted by small molecule inhibitors. He is a Consultant at Division of Oncology Research, Department of Oncology, an Enterprise Deputy Director at Basic Research, Mayo Clinic Comprehensive Cancer Center, a Consultant of Department of Biochemistry and Molecular Biology and Department of Immunology, a Chair at the Department of Immunology and a Professor of Biochemistry and Molecular Biology. He obtained his PhD in Pathobiology at the University of Minnesota.
Dr. Hu Li is a Professor at the Mayo Clinic College of Medicine and Science. His research team seeks novel systems biology perspectives in order to understand the complex and nonlinear behavior of biological systems. His lab is interested in AI, machine learning, systems biology, systems pharmacology, and individualized systems medicine. Dr. Li's team is active in developing innovative systems biology, AI, and machine learning algorithms guided by novel conceptual frameworks to unlock the "manifoldness" nature of biological systems, disease development, and therapeutics and drug discovery.
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