Bio-X
Showing 821-830 of 1,062 Results
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Grant M. Rotskoff
Assistant Professor of Chemistry
BioGrant Rotskoff studies the nonequilibrium dynamics of living matter with a particular focus on self-organization from the molecular to the cellular scale. His work involves developing theoretical and computational tools that can probe and predict the properties of physical systems driven away from equilibrium. Recently, he has focused on characterizing and designing physically accurate machine learning techniques for biophysical modeling. Prior to his current position, Grant was a James S. McDonnell Fellow working at the Courant Institute of Mathematical Sciences at New York University. He completed his Ph.D. at the University of California, Berkeley in the Biophysics graduate group supported by an NSF Graduate Research Fellowship. His thesis, which was advised by Phillip Geissler and Gavin Crooks, developed theoretical tools for understanding nonequilibrium control of the small, fluctuating systems, such as those encountered in molecular biophysics. He also worked on coarsegrained models of the hydrophobic effect and self-assembly. Grant received an S.B. in Mathematics from the University of Chicago, where he became interested in biophysics as an undergraduate while working on free energy methods for large-scale molecular dynamics simulations.
Research Summary
My research focuses on theoretical and computational approaches to "mesoscale" biophysics. Many of the cellular phenomena that we consider the hallmarks of living systems occur at the scale of hundreds or thousands of proteins. Processes like the self-assembly of organelle-sized structures, the dynamics of cell division, and the transduction of signals from the environment to the machinery of the cell are not macroscopic phenomena—they are the result of a fluctuating, nonequilibrium dynamics. Experimentally probing mesoscale systems remains extremely difficult, though it is continuing to benefit from advances in cryo-electron microscopy and super-resolution imaging, among many other techniques. Predictive and explanatory models that resolve the essential physics at these intermediate scales have the power to both aid and enrich the understanding we are presently deriving from these experimental developments.
Major parts of my research include:
1. Dynamics of mesoscale biophysical assembly and response.— Biophysical processes involve chemical gradients and time-dependent external signals. These inherently nonequilibrium stimuli drive supermolecular organization within the cell. We develop models of active assembly processes and protein-membrane interactions as a foundation for the broad goal of characterizing the properties of nonequilibrium biomaterials.
2. Machine learning and dimensionality reduction for physical models.— Machine learning techniques are rapidly becoming a central statistical tool in all domains of scientific research. We apply machine learning techniques to sampling problems that arise in computational chemistry and develop approaches for systematically coarse-graining physical models. Recently, we have also been exploring reinforcement learning in the context of nonequilibrium control problems.
3. Methods for nonequilibrium simulation, optimization, and control.— We lack well-established theoretical frameworks for describing nonequilibrium states, even seemingly simple situations in which there are chemical or thermal gradients. Additionally, there are limited tools for predicting the response of nonequilibrium systems to external perturbations, even when the perturbations are small. Both of these problems pose key technical challenges for a theory of active biomaterials. We work on optimal control, nonequilibrium statistical mechanics, and simulation methodology, with a particular interest in developing techniques for importance sampling configurations from nonequilibrium ensembles. -
Daniel Rubin
Professor of Biomedical Data Science, of Radiology (Integrative Biomedical Imaging Informatics at Stanford), of Medicine (Biomedical Informatics Research) and, by courtesy, of Ophthalmology
Current Research and Scholarly InterestsMy research interest is imaging informatics--ways computers can work with images to leverage their rich information content and to help physicians use images to guide personalized care. Work in our lab thus lies at the intersection of biomedical informatics and imaging science.
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Mirabela Rusu
Assistant Professor of Radiology (Integrative Biomedical Imaging Informatics) and, by courtesy, of Urology and of Biomedical Data Science
Current Research and Scholarly InterestsDr. Mirabela Rusu focuses on developing analytic methods for biomedical data integration, with a particular interest in radiology-pathology fusion. Such integrative methods may be applied to create comprehensive multi-scale representations of biomedical processes and pathological conditions, thus enabling their in-depth characterization.
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Florentine Rutaganira
Assistant Professor of Biochemistry and of Developmental Biology
BioDr. Rutaganira uses choanoflagellates—the closest living single-celled relatives to animals—to study the origin of animal cell communication. Dr. Rutaganira applies chemical, genetic, and cell biological tools to probe choanoflagellate cell-cell communication, with implications for understanding not only animal cell signaling, but also the origin of multicellularity in animals.
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Brian Rutt
Professor of Radiology (Radiological Sciences Lab), Emeritus
Current Research and Scholarly InterestsMy research interests center on MRI research, including high-field and high-resolution MRI technology development as well as applications of advanced MRI techniques to studying the brain, cardiovascular system and cancer.
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Raya Saab
Lindhard Family Professor of Pediatric Cancer Biology
BioOur laboratory focuses on investigating molecular mechanisms of oncogene-induced tumorigenesis and tumor suppressor pathways, and oncogenic signaling in the pediatric solid tumor rhabdomyosarcoma. Our earlier work identified the tumor suppressors p53 and p18Ink4c as inhibitors of Cyclin D1-driven tumorigenesis in a pineoblastoma model, through senescence induction, and highlighted distinct roles for the the RB and p53 pathways in induction and maintenance of oncogene-induced senescence. We also identified CDK2 as a potential target for inducing senescence in premalignant lesions to inhibit tumor progression.
Our current focus is on studying oncogenic signaling and tumor suppression in the childhood tumor rhabdomyosarcoma, to identify key mediators of invasion and metastasis, which is the most common cause of treatment failure clinically. We use preclinical in vitro and in vivo models, including murine and human cell lines, and mouse models of disease.
We have recently uncovered a paracrine role for rhabdomyosarcoma-secreted exosomes in impacting biology of stromal cells. Rhabdomyosarcoma-derived exosomes carry specific miRNA cargo that imparts an invasive and migratory phenotype on normal recipient fibroblasts, and proteomic analysis revealed specific and unique pathways relevant to the two different molecular rhabdomyosarcoma subtypes that are driven by distinct oncogenic pathways. We identified that the driver oncogene in fusion-positive rhabdomyosarcoma, PAX3-FOXO1, modulates exosome cargo to promote invasion, migration, and angiogenic properties, and identified specific microRNA and protein cargo acting as effectors of PAX3-FOXO1 exosome-mediated signaling, including modulation of oxidative stress response and cell survival signaling.
Our ongoing work is focused on interrogating specific paracrine signaling pathways and molecular mechanisms of metastatic disease progression in rhabdomyosarcoma, for potential therapeutic targeting. -
Chiara Sabatti
Professor of Biomedical Data Science and of Statistics
Current Research and Scholarly InterestsStatistical models and reasoning are key to our understanding of the genetic basis of human traits. Modern high-throughput technology presents us with new opportunities and challenges. We develop statistical approaches for high dimensional data in the attempt of improving our understanding of the molecular basis of health related traits.
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Amin Saberi
Professor of Management Science and Engineering
BioAmin Saberi is Professor of Management Science and Engineering at Stanford University. He received his B.Sc. from Sharif University of Technology and his Ph.D. from Georgia Institute of Technology in Computer Science. His research interests include algorithms, design and analysis of social networks, and applications. He is a recipient of the Terman Fellowship, Alfred Sloan Fellowship and several best paper awards.
Amin was the founding CEO and chairman of NovoEd Inc., a social learning environment designed in his research lab and used by universities such as Stanford as well as non-profit and for-profit institutions for offering courses to hundreds of thousands of learners around the world. -
Debra Safer
Professor of Psychiatry and Behavioral Sciences (General Psychiatry and Psychology-Adult)
Current Research and Scholarly InterestsPrimary research interests include the nature and treatment of eating disorders
(particularly bulimia nervosa and binge eating disorder), the development and treatment of obesity, and the development and treatment of problematic eating patterns in patients following bariatric surgery. -
Marc R. Safran, MD
Professor of Orthopaedic Surgery
Current Research and Scholarly InterestsDr. Safrans practice focuses on arthroscopic management of hip problems as well as articular cartilage regeneration, shoulder surgery and athletic shoulder and elbow problems. He is actively involved in research in these areas.