Biomedical Computation

Faculty

Name	Links	Interests	Current/previous BMC advisor	Informatics	Simulation	Cell/Mol	Organs
BMC Co-Directors
Russ Altman Genetics, Bioengineering, CS	home lab SoM	The Helix Group at Stanford focuses on the creation and application of computational tools to solve problems in biology and medicine. Current application projects include the study of structure-function relationships in macromolecular structure, understanding the structure and folding of RNA molecules, and analyzing the relationship of genotype and phenotype, particularly with respect to the response to drugs. Techniques used include knowledge representation, database design, machine learning, natural language processing, physics-based simulation and graph-based modeling/analysis.	yes	Inf		Cell/Mol
Daphne Koller CS	home lab	Our main research focus is on dealing with complex domains that involve large amounts of uncertainty. Our work builds on the framework of probability theory, decision theory, and game theory, but uses techniques from artificial intelligence and computer science to allow us to apply this framework to complex real-world problems. Most of our work is based on the use of probabilistic graphical models such as Bayesian networks, influence diagrams, and Markov decision processes. Within that topic, our work touches on many areas: representation, inference, learning, and decision making. One main focus has been the extension of the representational power of the probabilistic graphical modeling language, to encompass a much richer set of domains.	yes	Inf		Cell/Mol

BMC Potential Advisors (SoE Faculty) These faculty members may serve as official acadmic advisors for BMC students. Students need to find an academic advisor in order to declare BMC
Name	Links	Interests	Current/previous BMC advisor	Informatics	Simulation	Cell/Mol	Organs
Tom Andriacchi ME	lab SoE	The primary mission of the BioMotion Research Group is to study normal and pathological function which can be ultimately applied to the improved evaluation and treatment of musculoskeletal disease and injury. The goals are addressed by studying normal subjects and patients with injury or disease that influence the normal function of the musculoskeletal system. In addition, the BioMotion group is committed to the development of improved methods for the measurement and analysis of human movement. The BioMotion laboratory is an important component in the overall biomechanics research within the department.			Sim		Organs
Serafim Batzoglou CS	lab	I am interested in the applications of computer science to molecular biology. My current research focuses on alignment algorithms, comparative genomics, sequence assembly, gene regulation, and networks of protein interactions.	yes	Inf		Cell/Mol
Gill Bejerano DevBio, CS	lab	We specialize in computational genomics, backed by a powerful in-house (hundreds of CPUs, teras of bytes) compute cluster, as well as an affiliation with Stanford's Computer Science department and close ties with the UCSC genome browser group. Our lab space, however, combines both dry and wet benches, and resides within Stanford's department of Developmental Biology, allowing us to benefit from close collaboration with neighboring top notch experimental labs. Combined, we practice 21st century Biology - utilizing powerful algorithms and hardware to sift through the multitudes of available data; and taking resulting hypotheses to the lab. Few scientific fields can currently offer similar opportunities, literally ranging from rewriting basic science to innovating bedside medicine.		Inf		Cell/Mol
Kwabena Boahen Bioengineering	lab SoM	Brains in Silicon: We have crafted two complementary objectives: To use existing knowledge of brain function in designing an affordable supercomputer�one that can itself serve as a tool to investigate brain function�feeding back and contributing to a fundamental, biological understanding of how the brain works. We model brains using an approach far more efficient than software simulation: We emulate the flow of ions directly with the flow of electrons�don't worry, on the outside it looks just like software.			Sim		Organs
Atul Butte SMI, CS	lab SoM	The long-term research goal of the Butte Lab is to develop bioinformatics methods in integrative biology, or reasoning over the many available genome-scale measurement and experimental modalities, and apply these methods to study complex disorders in genomic medicine, especially obesity and type 2 diabetes mellitus.		Inf		Cell/Mol	Organs
Jennifer Cochran Bioengineering	lab SoE	The Cochran laboratory uses interdisciplinary approaches in chemistry, engineering, and biophysics to study complex biological systems. Our main goals are to develop new technologies for basic science and biomedical applications. Clinical applications of our research involves bone and wound healing, biomimetic corneas, neural cell regeneration, and cancer imaging and therapy. Our research is driven by the philosophy that in order to control physiological processes it is necessary to understand the molecular mechanisms that drive these processes. We are interested in elucidating molecular details of receptor-mediated cell signaling events; at the same time developing protein and polymer-based tools that will allow us to manipulate cellular processes on a molecular level. For biomedical applications, we are combining rational design and combinatorial methods to create designer protein therapeutics and diagnostic agents.	yes		Sim	Cell/Mol
Marcus Covert Bioengineering	lab SoE	Our research focuses on systems biology, the interface between high-throughput molecular biology and large-scale predictive computer simulations. We build computational models of complex biological processes, and use these models to guide an experimental program. Such an approach leads to a relatively rapid identification and validation of previously unknown components and interactions. Biological systems of interest include metabolic, regulatory and signaling networks as well as cell-cell interactions. Current research involves the dynamic behavior of NF-kappaB, an important family of transcription factors whose aberrant activity has been linked to oncogenesis, tumor progression, and resistance to chemotherapy.			Sim	Cell/Mol
Scott Delp ME	lab SoE	The Neuromuscular Biomechanics Lab combines experimental and computational approaches to study movement. We investigate the form and function of biomechanical systems ranging from molecular motors to persons with movement disorders. We seek fundamental understanding of the mechanisms involved in the production of movement, and are motivated by opportunities to improve treatments for individuals with cerebral palsy, stroke, osteoarthritis, and Parkinson�s disease.	yes		Sim		Organs
David Dill CS	lab SoE	Professor Dill has research interests in a variety of areas. His areas include computational systems biology as well as the theory and application of formal verification techniques to system designs, which encompass hardware, protocols, and software. He has also done research in asynchronous circuit verification and synthesis, and in verification methods for hard real-time systems.	yes	Inf	Sim	Cell/Mol
Daniel Fisher Applied Physics, Biology, Bioengineering	lab	Primary research interests are the dynamics of evolutionary processes. These include theoretical work on general issues and models in evolutionary dynamics, especially quantitative aspects, collaborations with experimental groups on laboratory evolution of microbes and on field studies of microbial diversity, improved methods for analysis of DNA sequence data to understand variations, and repertoire and dynamics of the immune system. Dynamics of cellular processes is also an active interest. Some collaborations with experimental neuroscience groups are being carried out.			Sim	Cell/Mol	Organs
Leo Guibas CS, EE	lab SoE	Professor Guibas heads the Geometric Computation group in the Computer Science Department of Stanford University and is a member of the Computer Graphics and Artificial Intelligence Laboratories. He works on algorithms for sensing, modeling, reasoning, rendering, and acting on the physical world. Professor Guibas' interests span computational geometry, geometric modeling, computer graphics, computer vision, sensor networks, robotics, and discrete algorithms --- all areas in which he has published and lectured extensively.		Inf	Sim	Cell/Mol
KC Huang Bioengineering	lab SoM	My laboratory employs diverse interdisciplinary methods of inquiry to understand the relationships among cell shape detection, determination, and maintenance in bacteria. Cell shape plays a critical role in regulating many physiological functions, yet little is known about how the wide variety of cell shapes are determined and maintained. Inside the cell, many proteins organize and segregate, but how they detect and respond to the cellular morphology to end up at the right place at the right time is also largely mysterious. We utilize a combination of analytical, computational, and experimental approaches to probe physical mechanisms of shape-related self-organization in protein networks, membranes, and the cell wall. Current topics of interest are (i) cell-wall biosynthesis, (ii) the regulation and mechanics of cell division, (iii) membrane organization, and (iv) membrane-mediated protein interactions. Ultimately, the manipulation of cell shape may provide a direct tool for engineering complex cellular behaviors.			Sim	Cell/Mol
Oussama Khatib CS	home lab SoE	Khatib's research is in autonomous robots, human-centered robotics, human-friendly robot design, dynamic simulations, and haptic interactions. His exploration in this research ranges from the autonomous ability of a robot to cooperate with a human to the haptic interaction of a user with an animated character, virtual prototype, or surgical instrument.	yes		Sim		Organs
Ellen Kuhl ME	lab SoE	One of the most challenging applications of the mechanics of solid materials today is certainly the field of computational biomechanics, a well-recognized, fast-growing but not yet clearly defined subject that is unquestionably an interdisciplinary science par excellence. It provides a vast number of new and fascinating areas of application such as the internal and external remodeling of bones, the healing of fracture, the growth of tumors, wound healing of the epidermis, the regeneration of microdamaged muscles, functional adaptation and general repair processes of the cardiovascular system to name but a few. Besides a basic knowledge in medicine, biology and chemistry, research in the field of computational biomechanics requires a profound theoretical background in thermodynamics, continuum mechanics and structural mechanics paired with the ability to develop efficient robust and stable computational simulation tools. Our ultimate goal is to establish an interactive computer-based biomechanical lab that supports the solution of medically and technologically challenging biomechanical problems.	yes		Sim		Organs
Jean-Claude Latombe CS	lab SoE	The goal of my research is to create autonomous agents that sense, plan, and act in real and/or virtual worlds. My work focuses on designing architectures and algorithms to represent, sense, plan, control, and render motions of physical objects. A key underlying issue is to efficiently capture the connectivity of configuration or state spaces that are both high-dimensional and geometrically complex. Specific topics include: motion planning in the presence of multiple constraints (obstacle avoidance, maintenance of equilibrium, as well as kino-dynamic, visibility, and contact constraints), assembly sequence planning, making decisions under sensing and control uncertainty, construction of 3-D geometric models of complex environments, visual tracking of rigid, articulated and deforming objects, and reasoning in multiple-agent worlds. Applications include: robot-assisted medical surgery, integration of design and manufacturing, graphic animation of digital actors, study of molecular motions (folding, binding). My current projects study legged robots navigating on steep terrain, sensing and manipulation of deformable objects, structure and motion of proteins, and surgical simulation.	yes	Inf	Sim	Cell/Mol
Marc Levenston ME	home lab SoE	The research activities of the Soft Tissue Biomechanics Laboratory focus on the function, degeneration and regeneration of articular cartilage and fibrocartilage, with an emphasis on understanding the complex interactions between biophysical and biochemical cues in controlling cell behavior. Our approach combines contemporary approaches from a variety of disciplines including experimental and theoretical mechanics, cell and tissue culture, imaging, biochemistry and molecular biology.			Sim		Organs
Adrian Lew ME	lab SoE	At the Laboratory for Virtual Experiments in Mechanics, we work on the modeling and simulation of soft solid materials.			Sim
Mark Musen SMI, CS	lab SoE	Mark Musen's laboratory concentrates on the study of components for building knowledge-based systems, controlled terminologies and ontologies, and technology for the Semantic Web. For two decades, Musen's group has worked to elucidate reusable building block of intelligent systems, and to develop scalable computational architectures for systems that can address significant application tasks in biomedicine. An important element of that work has led to the development of the Prot�g� system, an open-source platform used around the world for the construction and maintenance of electronic knowledge bases, ontologies, and Semantic Web applications. Other research concerns the use of knowledge-based data integration and analysis techniques for bioterrorism surveillance and for reasoning about human anatomy and potential anatomic injuries.	yes	Inf			Organs
Sandy Napel Radiology, EE	lab	My primary interests are in developing diagnostic and therapy-planning applications and strategies for the acquisition and visualization of multi-dimensional medical imaging data. Examples are: creation of three-dimensional images of blood vessels using CT, visualization of complex flow within blood vessels using MR, computer-aided detection and characterization of lesions (e.g., colonic polyps, pulmonary nodules) from cross-sectional image data, visualization and automated assessment of 4D ultrasound data, and fusion of images acquired using different modalities (e.g., CT and MR). I have also been involved in developing and evaluating techniques for exploring cross-sectional imaging data from an internal perspective, i.e., virtual endoscopy (including colonoscopy, angioscopy, and bronchoscopy), and in the quantitation of structure parameters, e.g., volumes, lengths, medial axes, and curvatures. Finally, I am also interested in creating workable solutions to the problem of "data explosion," i.e., how to look at the thousands of images generated per examination using modern CT and MR scanners.	yes	Inf	Sim		Organs
Manu Prakash Bioengineering	lab	We are a curiosity driven research group working in the field of physical biology. Our approach brings together experimental and theoretical techniques from soft-condensed matter physics, fluid dynamics, theory of computation and unconventional nano-fabrication to open problems in biology: from organismal to cellular and molecular scale. We design and build precision instrumentation to probe and perturb biological machines and their synthetic analogues. Along the way, we invent novel technologies with clinical applications with a current focus on resource poor settings.			Sim	Cell/Mol
Ingmar Riedel-Kruse Bioengineering	lab	Our lab combines basic research and engineering approaches by working on two (overlapping) questions: How to gain a quantitive, biophysical understanding of embryology as needed for medicine and tissue engineering? And, How to design and utilize biotic games to solve challenges in education and large scale biomedical research?			Sim	Cell/Mol
Kenneth Salisbury CS, Surgery	home lab	Most of our group's work focuses on the physical interaction between human beings and computer-driven actuators. This includes both haptics and human-friendly robotics. Haptics is roughly defined as using force-feedback to simulate interaction with virtual objects. Haptics research in the Salisbury group is geared toward simulating complex manual tasks for surgical simulation and collaborative, networked environments. We experiment with several commercially available haptic interfaces - primarily the PHANToM haptic device from SensAble Technologies, Inc. and the Delta haptic device from Force Dimension, Inc. - in addition to developing our own haptic interface hardware. The Human-Friendly Robot project aims to design safe, efficient mechanisms that will allow robots to be placed in direct contact with human beings. Projects are underway that explore all levels of human-friendly robotics, from mechanism design to control to high-level interactions.			Sim		Organs
Krishna Shenoy EE	home lab	Professor Shenoy heads the Neural Prosthetic Systems Laboratory at Stanford University. His research group conducts neuroscience (systems & cognitive neuroscience) and neuroengineering (electrical, bio, and biomedical engineering) research. The group investigates the neural basis of motor preparation and generation, and designs neural prosthetic systems to assist disabled patients.	yes		Sim		Organs
Terry Winograd CS	home lab	Professor Winograd's focus is on human-computer interaction design, with a focus on the theoretical background and conceptual models. He directs the teaching programs and HCI research in the Stanford Human-Computer Interaction Group. He is also a founding faculty member of the Hasso Plattner Institute of Design at Stanford (the "d.school").		Inf

Other affiliated Faculty These faculty members are not in the School of Engineering, but work or have interests in BMC-related fields. They may provide additional useful information about the field and may serve as research mentors. Faculty members not in SoE may serve as co-academic advisors.
Name	Links	Interests	Current/previous BMC advisor	Informatics	Simulation	Cell/Mol	Organs
Doug Brutlag Biochemistry	lab	Our group's primary research objective is to understand the flow of genetic information from the genome to the phenotype of an organism. This includes understanding the sequence-structure dependencies and the structure-function dependencies of macromolecules. These goals represent the bioinformatic and functional-genomic approach to predicting structure and function from sequence. Specifically, we develop computer representations that can discover structural and functional properties of DNA, RNA and protein from sequences and from first principles. We spend much of our time learning the first principles of molecular and structural biology from known examples. We are also interested in predicting the interactions between ligands and proteins and between two interacting proteins. Given the structure, function and interactions of the proteins in a cell, we will eventually be able to simulate the metabolism of the organism.		Inf		Cell/Mol
Mike Cherry Genetics	lab SoM	Our largest area of research is the study of the yeast genome by applying bioinformatic techniques. The Saccharomyces Genome Database (SGD) is the result of this effort. This NIH National Genome Research Resource, a public Web site, provides information on yeast genes, their products and their interactions. My group is ever expanding SGD to capture the new results from functional genomics, the systematic study of the processes that occur within an organism. The second area of research is in the creation of ontologies to aid communication between biologists and genomic databases. We are founding members of the Gene Ontology (GO) Collaboration. The GO collaboration is developing three independent ontologies that can be used for gene product annotation (www.GeneOntology.org). As members of the consortium we are developing the terms, databases and software.		Inf		Cell/Mol
Parvati Dev Medicine	lab SoM	Stanford University Medical Media and Information Technology (SUMMIT) group is dedicated to putting Stanford University at the forefront of medical and lifesciences education through the innovative use of information technology. Our group creates new technologies that help faculty, students and researchers develop innovative, interactive teaching software, and researches methods of making these technologies easy and effective for authors as well as students.		Inf
Marcus Feldman Biology	lab	Dr. Feldman's specific areas of research include the evolution of complex genetic systems that can undergo both natural selection and recombination, and the evolution of learning as one interface between modern methods in artificial intelligence and models of biological processes, including communication. He also studies the evolution of modern humans using models for the dynamics of molecular polymorphisms, especially DNA variants. He helped develop the quantitative theory of cultural evolution, which he applies to issues in human behavior, and also the theory of niche construction, which has wide applications in ecology and evolutionary analysis. He also has a large research program on demographic issues related to the gender ratio in China.		Inf		Cell/Mol
Wm. LeRoy Heinrichs Ob/Gyn	lab	For the past several years Dr. Heinrichs has coordinated the development of 3D models of human anatomy, creating virtual organs for teaching and simulating videoendoscopic surgery. Dr. Heinrichs has also researched and developed prototypes of surgical simulators for medical education in private and university contexts.			Sim		Organs
Teri Klein Genetics	home	My research interests extend over the broad spectrum of pharmacogenetics, computational biology and bioinformatics. Applications include the development of a pharmcogenetics knowledge base, structure-function relationships, de novo modeling and the structural basis of disease.			Sim	Cell/Mol
Henry Lowe SMI	SoM	My research in the field of biomedical informatics over the past 25 years has focused on the development of novel uses of information technology and computer science to improve human health. My interests include the Electronic Health Record (EHR), biomedical knowledge representation, imaging informatics, Internet applications in healthcare, cancer informatics and the use of information technology to support translational research.		Inf			Organs
Vinod Menon Psychiatry and Behavioral Sciences	lab SoM	Our laboratory is dedicated to the investigation of brain function and dysfunction using a systems neuroscience approach. We use neuroimaging (fMRI, sMRI, DTI, and EEG) as well as behavioral, psychological and computational methods in our research. Various collaborative studies in our laboratory focus on the cognitive neuroscience of memory, attention, adaptive behavior, music and language, multisensory integration, and affective information processing. Across a wide range of studies, our overarching goal is (1) to better understand the integrated functioning of large-scale distributed brain networks and (2) to understand how disruptions in brain function and connectivity impact behavior.			Sim		Organs
Stephen Montgomery Pathology, Genetics	lab SoM	Our lab focuses on understanding the mechanisms by which genetic variation influences human traits. We utilize high throughput next generation sequencing to interrogate genomes and genome function in combination with utilizing and developing novel bioinformatics and statistical genetics tools. We envision a future where when one goes to the clinic, not only can we access the genome, but we can access layers of cellular phenotypes which will allow us to make unprecedented predictions regarding genetic risk.		Inf		Cell/Mol
Art Owen Statistics	home			Inf
David Paik Radiology, Biomedical Informatics	lab SoM	The Paik Lab research interests lie at the intersection of radiology, molecular biology and informatics. We focus on developing and validating computational methodologies for extracting useful information content from anatomic, functional and molecular images, drawing upon image processing, computer vision, computer graphics, computational geometry, machine learning, biostatistics, modeling and simulation. The lab also works on integrating image-based information with non-imaging biomedical information such as genomics and proteomics.	yes	Inf
Vijay Pande Chemistry	lab SoM	Many of the wonders associated with biomolecules rests in their functionality, but before they can carry out any function, many of these molecules must accomplish another amazing feat: them must first assemble themselves. Moreover, these molecules must build complex structures quickly and reliably. It is intriguing to consider how can one design molecules to self assemble? Actually, this is an extremely old problem: for billions of years, Nature has been honing its skills at molecular design. Can we benefit from Nature's billion year investment in R & D of molecular self assembly? Our main research interests revolve around the related questions of how do these processes work, how did these processes evolve, and how can we mimic these processes in de novo deigned biological and synthetic biomimetic systems? Computer simulation is particularly well suited to address these questions, as it naturally lends itself to thermodynamic, kinetic, and atomic level structural details.			Sim	Cell/Mol
Sylvia Plevritis Radiology	home	My research program takes a systems engineering approach to the study of cancer. Our projects range from developing computational models of cancer biology to developing decision analytic models that inform health policies for cancer control. Recently, we started to model signaling pathways perturbed in the cancer process with the goal of discovering molecular mechanisms underlying cancer initiation and progression and identifying molecular targets for therapy. We have been developing stochastic models of the natural history of cancer and derive estimates of the rates that cancer progresses from non-metastatic to metastatic states using clinical data. We embed our disease models of cancer into population-level simulation models that predict patient outcomes under differing medical interventions; here our work is primarily focused on simulating cancer screening trials and predicting the effectiveness and cost-effectiveness of new cancer imaging technologies.			Sim		Organs
Alan Reiss Psychiatry and Behavioral Sciences
Daniel Rubin Radiology	lab SoM	Our research group uses computational methods to leverage the information in radiology images to enable biomedical discovery and to guide physicians in personalized care. Just as biology has been revolutionized by online genetic data, our goal is to advance radiology by making the content in images computable and to electronically correlate images with other clinical data such as pathology and molecular data. Our work develops and translates basic biomedical informatics methods to improve radiology practice and decision making in several areas: tools to efficiently and thoroughly capture the semantic terms radiologists use to describe lesions; standardized terminologies to enable radiologists to describe lesions comprehensively and consistently; image processing methods to characterize the shape of lesions; content-based image retrieval with structured image information to enable radiologists to find similar images; methods to enable physicians to quantitatively and reproducibly assess tumor burden in images and to more effectively monitor treatment response in cancer treatment; natural language techniques to enable uniform indexing, searching, and retrieval of radiology information resources such as radiology reports; and decision support applications that relate radiology findings to diagnoses to improve diagnostic accuracy.
Mark Schnitzer Applied Physics, Biological Sciences	lab	Dr. Schnitzer has longstanding interests in neural circuit dynamics and optical imaging, and his laboratory has three major research efforts: 1) In vivo fluorescence imaging and behavioral studies of cerebellar-dependent motor control and motor learning. 2) Development and application of fiber-optic fluorescence microendoscopy imaging techniques for studies of learning and memory in behaving mice and for clinical uses in humans. 3) Development of high-throughput, massively parallel imaging techniques for studying brain function in large numbers of Drosophila concurrently.			Sim	Cell/Mol	Organs
Nigam Shah Biomedical Informatics	lab SoM	The Shah laboratory studies ontology based approaches to annotate, index, integrate and analyze diverse information types available in biomedicine for the purpose of enabling data-driven decision making in medicine and health care. My research interest is to make biomedical information actionable.		Inf			Organs
Arend Sidow Pathology	lab	We have a diverse research program at the interface of computational and functional genomics, with a focus on the interaction between function, variation, and evolution.		Inf		Cell/Mol
Rob Tibshirani Statistics	lab	Applied statistics and data mining, with applications to bioinformatics, and especially microarray data.		Inf