Biomedical Modeling Research Overview
Biomedical modeling imploys the use of computer simulations, discrete mathematics and numerical methods in order to mimic dynamic biomedical systems. Among other purposes simulations and models are often used in order to support and strengthen experimental conclusions as well as to provide a more accurate model of behavior in tough to image systems. Here at Stony Brook, advances are made using our own Seawulf Computing Cluster, and the New York Blue Super Computer, currently the fastest super computer available for non-classified research.
Analysis of human exposures to toxic, carcinogenic or hazardous conditions, and the potential consequences of these exposures. Product and process designs for reduction or elimination of conditions associated with workplace and residential injury. Development of medical devices directed toward intervention in preventable conditions and diseases (e.g. osteoporosis, bone and muscle atrophy in space, musculo-skeletal disorders in paraplegia).
Faculty Research Interests
Laufer Center - Room 115C
Henry Laufer Endowed Associate Professor
Summary : The goal of my laboratory is to develop synthetic gene circuits (small constructs built from genes and their regulatory regions), and use them for biological discovery and practical applications (such as therapeutic gene expression control). For example, using synthetic gene circuits in yeast cells, we could demonstrate that noise (nongenetic cellular diversity) can aid microbial survival during antibiotic treatment and thereby enable the development of drug resistance. We have designed "linearizer" gene circuits in yeast cells that can tune a protein's level precisely, such that the protein concentration is proportional to an extracellular inducer and uniform within a cell population. We have moved this synthetic gene circuit into mammalian cells and can now tune the expression of a cancer-related genes precisely, to investigate how the level of tumor progression-related proteins affects invasion, migration and other metastasis-related cell behaviors. In the future, similar gene circuits may enable novel approaches to gene therapy. Our research is inherently interdisciplinary, since we use mathematical and computational models in combination with single-cell level measurements to characterize the dynamics of synthetic and natural gene networks, and to understand the cellular and multicellular behaviors they confer.
Health Sciences Tower
Professor & Vice Chair for Research
Summary : Benveniste's Laboratory focuses on (1) exploring, characterizing and understanding diagnostic MR contrast parameters suitable to visualize neuro-pathology in neurodegenerative diseases; (2) investigate transgenic animal models were specific genes are modified to understand mechanism(s) and treatment of addiction and of drug-induced neurotoxicity using high resolution MR imaging, (3) advance technologies in molecular MR imaging.
Health Sciences Tower 15-090
Summary : Despite major progress, cardiovascular diseases remain the leading cause of death in the western world. One of the major culprits in cardiovascular disease and in devices designed to treat or restore impaired cardiovascular function is the non-physiological flow pattern that enhances the hemostatic response mainly through platelet activation. Platelets have long been regarded as the preeminent cell involved in physiologic hemostasis and pathologic thrombosis. An innovative technique for measuring flow induced platelet activation has been developed, and its utility demonstrated in experiments conducted in recirculation devices (models of arterial stenosis, Left Ventricular Assist Device (LVAD), and mechanical heart valves). The mechanisms by which the non-physiologic flow patterns induce platelet activation and generate free emboli, that enhance the risk of cardioembolic stroke, was demonstrated in vivo with mechanical heart valves implanted in a sheep model. The results of this research will aid in elucidating physical forces that regulate cellular function in flowing blood, and may be applied to improve the design of blood recirculating devices and to develop more potent drugs for treating cardiovascular diseases.
Health Sciences Tower 10-020
Summary : Depression is a complex, heterogeneous disorder. It is most likely for this reason that neuroimaging has yet to uncover a clinically useful diagnostic or prognostic aid for people living with this disease, despite providing an unprecedented level of detail about the living human brain. As a biomedical engineers, we have the ability to incorporate the most current and technically advanced procedures in mathematics, image processing, and statistics in order to improve outcomes for patients diagnosed with Major Depressive Disorder (MDD) and other mental illnesses. My focus is to use advanced image processing algorithms to uncover the neurobiology of mental illness, and help improve both diagnosis and treatment. This includes: (1) developing algorithms to combine high dimensional multimodal data. Our group has a large repository of structural and functional Magnetic Resonance Images (MRI), Diffusion Tensor Images (DTI), and Positron Emission Tomography (PET) images of subjects with mental illness and controls. Fusing information from multiple modalities in a meaningful way may lead to personalized medicine options for those suffering from MDD and other illnesses; (2) Visualizing neurotransmitter systems in vivo. Examining neurotransmitter systems with PET can help us understand more about the pathophysiology of mental illness; and (3) Extracting the most accurate quantitative information from brain images using improved imaging sequences such as Diffusion Spectrum Imaging (DSI) and Arterial Spin Labeling (ASL). These high resolution imaging sequences can help us get the most complete and accurate view of the brain. Through advanced imaging techniques and image processing algorithms, we can help improve the lives of those suffering with MDD and other disorders.
Laufer Center - 5252
Summary : Ken A. Dill is interested in the physics of how proteins fold; the microscopic origins of the unusual physical properties of water; the foundations and applications of variational entropy-based principles in statistical physics; and how the laws of physics constrain and enable the biological properties and evolution of cells.
Summary : The primary role of this laboratory is to study basic physiological flow phenomena, both experimentally and numerically, as well as cellular and tissue engineering as applied to the vascular system. and to suggest ways of improving the functioning of cells, tissues and organs in the body. These physiological flows include blood flow in the heart, blood flow in arteries, veins and the microcirculation, air flow in the respiratory airways, and urine flow in the kidney and urethra. This laboratory simulates systems through the use of computers, assisting life scientists to better understand physiological functions without having to rely entirely on living systems as experimental models. The use of mathematical analysis helps minimize animal experimentation. Other projects are the investigation of hemodynamics as a regulator of vascular biology, the mathematical modeling of the dynamic response of mammalian cells, the role of flow and the associated shear stress on vascular endothelial biology, prosthetic circulatory devices and the tissue engineering of blood vessel substitutes. The laboratory is also engaged in the evaluation of critical conditions that lead to failure of biological organs, such as the heart and the coronary circulation, failure of circulatory prosthetic devices as stents, heart valves and grafts. To facilitate in vitro and in vivo studies, the laboratory develops new investigative techniques, noninvasive diagnostic methods, and advance, multi-dimensional numerical modeling.
Bioengineering Building - Room 213
Summary : Research in this laboratory focuses on the identification of precise parameters that define skeletal tissue quantity and quality and their perturbation to applied physical stimuli. To this end, state of the art imaging techniques (e.g., microCT or synchrotron infrared spectroscopy) are combined with molecular (e.g., RT-PCR), genetic (e.g., QTL), and engineering techniques (e.g., finite element modeling) to determine genes, molecules, forces, as well as chemical and structural matrix properties. An example for a recent study includes the demonstration that extremely small amplitude oscillatory motions (~ 100µm), inducing negligible deformation in the matrix, can serve as an anabolic stimulus to osteoblasts in vivo, producing a structure that is mechanical stronger and more efficient to withstand forces. Recent results also indicate that there is not only a genetic basis for bone architecture, but also that the sensitivity of bone tissue to both anabolic and catabolic stimuli is influenced by subtle genetic variations. The identification of the specific chromosomal regions that modulate this differential sensitivity is in progress. Clinically, our studies may lead to the development of effective prophylaxes and interventions for osteoporosis, without side-effects and tailored towards the genetic make-up of an individual.
Computer Sciences - 203G
Distinguished Professor & Chair
Summary : Arie Kaufman is the director of the Center of Visual Computing (CVC) and the director of the Cube project for volume visualization supported by the National Science Foundation, Department of Energy, Office of Naval Research, Hughes Aircraft Company, Hewlett-Packard Company, Silicon Graphics Company, Howard Hughes Medical Institute, and many others. His research interests include computer graphics and specifically computer graphics architectures, algorithms, and languages; visualization including volume visualization and scientific visualization; user interfaces; virtual reality; and multimedia. Kaufman is the editor-in-chief of the IEEE Transaction on Visualization and Computer Graphics. He has lectured widely and published numerous technical papers in these areas, including the IEEE tutorial book on Volume Visualization. He has been the papers chair and program cochair for Visualization 1990-1994 and the chairman of the IEEE CS Technical Committee on Computer Graphics.
Cold Spring Harbor Labs
Summary : I am interested in gaining a fundamental understanding of the behavior of complex biological systems, both from a mechanistic, physico-chemical perspective, and from an engineering perspective emphasizing function. I am also interested in applying this knowledge to help improve therapies for brain disorders. My research combines a number of approaches, including theoretical work, informatics, and experimental work. My theoretical interests are primarily in formalizing the treatment of biological function using ideas and methods from engineering. The informatics component of my research is devoted to the development of computational tools for analyzing neurobiological data, particularly electrophysiological data from experiments designed to probe cognitive phenomena. In addition, I am working on building knowledge bases to integrate information from the neuroscientific literature, both for the research and medical communities. I have an experimental research program studying memory formation in the fruitfly, integrating information across genetic, neural and behavioral levels. In collaborative research, I study song development in the zebra finch. My research is highly interdisciplinary and has a broad scope. I am also interested in the communication of science to a general audience.
Computer Sciences - 261
Summary : Klaus Mueller's areas of interest are medical, scientific and information visualization, visual analytics, medical imaging, computer graphics, virtual and augmented reality, and high-performance computing. He has pioneered the use of programmable commodity graphics hardware boards (GPUs) for the acceleration of a wide variety of computer tomographic (CT) reconstruction algorithms and medical physics phenomena. Applications include diagnostic imaging, radiotherapy, electron microscopy, ultrasound tomography for breast mammography, and others. In the visual analytics area he works on devising new high-dimensional data visualization frameworks and combining them with statistical pattern recognition and machine learning to create intuitive interactive analytical reasoning environments for medical professionals. He is also working towards a comprehensive visual data mining environment for neuroscientists, called BrainMiner, to enable a more targeted and experiential derivation of brain functional models from large collections of knowledge and data.
Bioengineering Building - Room 215
Summary : Early diagnostic of osteoporosis allows for accurate prediction of fracture risk and effective options for early treatment of the bone disease. A new ultrasound technology, based on focused transmission and reception of the acoustic signal, has been developed by Dr. Qin and his team which represents the early stages of development of a unique diagnostic tool for the measure of both bone quantity (density) and quality (strength). These data show a strong correlation between non-invasive ultrasonic prediction and micro-CT determined bone mineral density (r>0.9), and significant correlation between ultrasound and bone stiffness (r>0.8). Considering the ease of use, the non-invasive, non-radiation based signal, and the accuracy of the device, this work opens an entirely new avenue for the early diagnosis of metabolic bone diseases.
Mathematics Tower 1-111
Summary : Rob Rizzo works in Computational Structural Biology. His research group seeks to understand the atomic basis for molecular recognition for specific biological systems involved in human disease such as HIV/AIDS, cancer, and influenza with the ultimate goal of developing new and improved drugs. Computational methods are used to model how molecules interact at the atomic level with a given drug target. The resultant 3D structural and energetic information is used to quantify and rationalize drug-binding for known systems and to make new predictions.
Bioengineering Building - Room 217A
Distinguished Professor & Chair
Summary : Encouraging results show that the application of extremely low level strains to animals and humans will increase bone formation, and thus may represent the much sought after "anabolic" stimulus in bone. More than 15 years of research into non-invasive, non-pharmacological intervention to control osteoporosis, was referenced in Dr. Rubin's paper published in the journal Nature (August 9, 2001; 412:603-604). Dr. Rubin's studies suggest that gentle vibrations on a regular basis will help strengthen the bones in osteoporosis sufferers and increase bone formation. In his study, adult female sheep treated with gentle vibration to their hind legs for 20 minutes daily showed almost 35% more bone density. Clinical trials have been completed on post-menopausal women, children with cerebral palsy, and young women with osteoporosis, all with encouraging results. In expanding the research platform into other physiologic systems, current work demonstrates that these low-level signals influence mesenchymal stem cell differentiation, such that their path to adipocytes is suppressed, and markedly reduces adipose tissue.
Computer Science Department
Distinguished Teaching Professor
Summary : Steven Skiena is a Distinguished Teaching Professor of Computer Science at Stony Brook University. He is a co-founder and the Chief Science Officer of General Sentiment, a social media and news analytics company. His research interests include algorithm design and its applications to biology. Skiena is the author of several popular books in the fields of algorithms, programming, and mathematics. The Algorithm Design Manual is widely used as an undergraduate text in algorithms and within the tech industry for job interview preparation.
Bioengineering Building - Room G13
Summary : Nature's ability to assemble simple molecular building blocks into highly ordered materials, such as those found in cell membranes, cell nuclei, cytoskeleton, cartilage, or bone presents many fascinating and unanswered questions. We are interested in how to tune the interactions of water-soluble building blocks so as to induce their self-assembly into useful microstructures much needed for the next generation of controlled drug delivery, biosensors and DNA sequencing applications. In particular, we are working on long-range ordered polyelectrolyte-surfactant microemulsions that are used as templates for solid nanoporous materials using polymerization and/or cross-linking strategies. Such materials, because of their well-ordered porous structure, will allow more efficient molecular separation and drug delivery. In addition, we are developing biosensors that are based on biopolymer chiral liquid crystals and quantum dot colloidal crystals. In both cases the softness of the systems allows the induction of a strong optical response to external stimuli. Such sensors should be able to quantitatively detect and measure analyte concentrations at hormonal levels.
Health Sciences Tower 4-141
Summary : Medical imaging techniques have undergone substantial growth in recent years, in both the research and clinical arenas. The standard anatomical imaging modalities of computed tomography (CT) and magnetic resonance imaging (MRI) have been complemented by quantitative functional approaches like positron emission tomography (PET) and single photon emission computed tomography (SPECT). Our lab develops new instrumentation and processing techniques not only to enhance the functional capabilities of PET, but also to combine it with synergistic modalities such as MRI to provide unprecedented, multidimensional information for cancer diagnosis, brain research, and many other applications. We have developed a miniaturized brain scanner for rodents (RatCAP) which avoids the potentially confounding effects of general anesthesia in rat brain studies, and even allows for the simultaneous study of behavior along with neurochemistry by PET. We have also developed new approaches for very high spatial resolution in PET, including a solid-state imager using cadmium zinc telluride (CZT) which achieves sub-mm resolution, and a monolithic scintillator detector with depth-encoding capability via a novel maximum likelihood positioning algorithm. And we have developed multiple imaging systems for simultaneous imaging with PET and high-field MRI, including a rodent brain scanner, a whole-body rodent system, and a prototype clinical breast imager. The research encompasses the development of new detector materials and concepts, low-noise microelectronic signal processing, high-throughput data acquisition methods, Monte Carlo simulation, and new data processing techniques to optimize the extraction of quantitative information from the PET data.
Bioengineering Building - Room 109
Summary : Cardiovascular disease is the leading cause of death in the United Sates, and coronary artery disease is the most common type of cardiovascular disease. Shear stress induced by blood flow plays an important role in the initiation and development of atherosclerosis, the major reason for coronary artery disease. Circulating platelets and vascular endothelial cells are very sensitive to their mechanical environment; any change can affect their functions and interactions significantly. My major research interest is to investigate how altered blood flow and stress distribution affect platelet and endothelial cell behavior and lead to cardiovascular disease initiation. Computational fluid dynamics modeling, along with in vitro and ex vivo experiments, are carried out to study platelet and endothelial cell responses under physiologically relevant dynamic conditions. Biomarkers associated with platelet and endothelial cell activation are of special interest to us. We also work on numerical models to describe platelet coagulation kinetics and platelet adhesion to injured blood vessel wall under dynamic flow conditions.