Bio-X
Showing 831-840 of 1,081 Results
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Noah Rosenberg
Stanford Professor of Population Genetics and Society
Current Research and Scholarly InterestsHuman evolutionary genetics, mathematical models in evolution and genetics, mathematical phylogenetics, statistical and computational genetics, theoretical population genetics
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David Rosenthal
Professor of Pediatrics (Pediatric Cardiology)
Current Research and Scholarly InterestsResearch interests include the study of Heart Failure, Cardiomyopathy and ventricular dysfunction in children, from a clinical perspective. Investigations include clinical trials of medications, cardiac resynchronization, and mechanical circulatory support.
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Jason B. Ross, MD, PhD
Assistant Professor of Radiation Oncology (Radiation Therapy)
Current Research and Scholarly InterestsMy laboratory studies studying normal, dysfunctional, and malignant stem cells in the context of aging, cancer, and cancer therapies.
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Stephen J. Roth
Professor of Pediatrics (Cardiology)
Current Research and Scholarly InterestsRandomized Therapeutic Trials in Pediatric Heart Disease, NIH/U01 GrantNo. HL68285 2001-2006.
Heparin and the Reduction of Thrombosis (HART) Study. Pediatric Health Research Fund Award, Stanford Univ Sch of Medicine, 2005-2006.
A Pilot Trial fo B-type Natriuretic Peptide for Promotion of Urine Output in Diuretic-Resistant Infants Following Cardiovascular Surgery.Pediatric Health Research Fund Award, Stanford Univ Sch of Medicine, 2005-2006. -
Theodore Roth
Assistant Professor of Pathology
Current Research and Scholarly InterestsThe Roth Lab develops, applies, and translates scalable genetic manipulation technologies in primary human cells and complex in vivo tissue environments. Working with students, trainees, and staff with backgrounds across bioengineering, genetics, immunology, oncology, and pathology, the lab has developed CRISPR-All, a unified genetic perturbation language able to arbitrarily and combinatorially examine genetic perturbations across perturbation type and scale in primary human cells. Ongoing applications of CRISPR-All in the lab have revealed surprising capacities to synthetically engineer human cells beyond evolved cellular states. These new capacities to perturb human cell’s genetics beyond their evolved functionality drives ongoing work to understand the biology and therapeutic potential of synthetic cell state engineering - in essence learning how to build new human genes tailor made for a specific cell and specific environment to drive previously inaccessible therapeutic cellular functions.
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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 and of Radiology (Integrative Biomedical Imaging Informatics at Stanford), Emeritus
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 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
Current Research and Scholarly InterestsWe use chemical tools to decipher the roles of key signaling networks in choanoflagellates, single-celled organisms that are the closest living relatives of animals. Choanoflagellates produce molecular signals essential for intercellular communication in animals and the presence of these molecules in choanoflagellates suggests that signaling components needed to communicate between cells is evolutionarily ancient. We aim to uncover new understanding of animal development, physiology and disease.
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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.