School of Medicine
Showing 1-10 of 29 Results
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Stephen J. Galli, MD
Mary Hewitt Loveless, MD, Professor in the School of Medicine and Professor of Pathology and of Microbiology and Immunology
On Partial Leave from 10/01/2024 To 12/05/2024Current Research and Scholarly InterestsThe goals of Dr. Galli's laboratory are to understand the regulation of mast cell and basophil development and function, and to develop and use genetic approaches to elucidate the roles of these cells in health and disease. We study both the roles of mast cells, basophils, and IgE in normal physiology and host defense, e.g., in responses to parasites and in enhancing resistance to venoms, and also their roles in pathology, e.g., anaphylaxis, food allergy, and asthma, both in mice and humans.
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Kristen N Ganjoo
Professor of Medicine (Oncology)
Current Research and Scholarly InterestsGiant cell tumor of the bone
Gastrointestinal stromal tumors
Soft tissue sarcoma
Osteosarcoma -
Xiaojing Gao
Assistant Professor of Chemical Engineering
Current Research and Scholarly InterestsHow do we design biological systems as “smart medicine” that sense patients’ states, process the information, and respond accordingly? To realize this vision, we will tackle fundamental challenges across different levels of complexity, such as (1) protein components that minimize their crosstalk with human cells and immunogenicity, (2) biomolecular circuits that function robustly in different cells and are easy to deliver, (3) multicellular consortia that communicate through scalable channels, and (4) therapeutic modules that interface with physiological inputs/outputs. Our engineering targets include biomolecules, molecular circuits, viruses, and cells, and our approach combines quantitative experimental analysis with computational simulation. The molecular tools we build will be applied to diverse fields such as neurobiology and cancer therapy.
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Chris Garcia
Younger Family Professor and Professor of Structural Biology
Current Research and Scholarly InterestsStructural and functional studies of transmembrane receptor interactions with their ligands in systems relevant to human health and disease - primarily in immunity, infection, and neurobiology. We study these problems using protein engineering, structural, biochemical, and combinatorial biology approaches.
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Christopher Gardner
Rehnborg Farquhar Professor
Current Research and Scholarly InterestsThe role of nutrition in individual and societal health, with particular interests in: plant-based diets, differential response to low-carb vs. low-fat weight loss diets by insulin resistance status, chronic disease prevention, randomized controlled trials, human nutrition, community based studies, Community Based Participatory Research, sustainable food movement (animal rights and welfare, global warming, human labor practices), stealth health, nutrition policy, nutrition guidelines
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Charles Gawad
Associate Professor of Pediatrics (Hematology/Oncology)
BioOur lab works at the interface of biotechnology, computational biology, cellular biology, and clinical medicine to develop and apply new tools for characterizing genetic variation across single cells within a tissue with unparalleled sensitivity and accuracy. We are focused on applying these technologies to study cancer clonal evolution while patients are undergoing treatment with the aim of identifying cancer clonotypes that are associated with resistance to specific drugs so as to better understand and predict treatment response. We are also applying these methods to understand how more virulent pathogens emerge from a population of bacteria or viruses with an emphasis on developing a deeper understanding of how antibiotic resistance develops.
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Michael Gensheimer
Clinical Associate Professor, Radiation Oncology - Radiation Therapy
Current Research and Scholarly InterestsIn addition to my clinical research in head and neck and lung cancer, I work on the application of computer science and machine learning to cancer research. I develop tools for analyzing large datasets to improve outcomes and safety of cancer treatment. I developed a machine learning prognostic model using data from around 13,000 patients with metastatic cancer which performs better than traditional models and physicians [PubMed ID 33313792]. We recently completed a prospective randomized study in thousands of patients in which the model was used to help improve advance care planning conversations.
I also work on the methods underpinning observational and predictive modeling research. My open source nnet-survival software that allows use of neural networks for survival modeling has been used by researchers internationally. In collaboration with the Stanford Research Informatics Center, I examined how electronic medical record (EMR) survival outcome data compares to gold-standard data from a cancer registry [PubMed ID 35802836]. The EMR data captured less than 50% of deaths, a finding that affects many studies being published that use EMR outcomes data. -
Andrew Gentles
Associate Professor (Research) of Pathology, of Medicine (BMIR) and, by courtesy, of Biomedical Data Science
Current Research and Scholarly InterestsComputational systems biology
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Olivier Gevaert
Associate Professor of Medicine (Biomedical Informatics) and of Biomedical Data Science
Current Research and Scholarly InterestsMy lab focuses on biomedical data fusion: the development of machine learning methods for biomedical decision support using multi-scale biomedical data. We primarily use methods based on regularized linear regression to accomplish this. We primarily focus on applications in oncology and neuroscience.
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Amato J. Giaccia
Jack, Lulu and Sam Willson Professor, Professor of Radiation Oncology, Emeritus
Current Research and Scholarly InterestsDuring the last five years, we have identified several small molecules that kill VHL deficient renal cancer cells through a synthetic lethal screening approach. Another major interest of my laboratory is in identifying hypoxia-induced genes involved in invasion and metastases. We are also investigating how hypoxia regulates gene expression epigenetically.