Using the structure and dynamics of biological systems for clinical benefit, especially in immunology, cancer, and infectious disease.
The complexity and heterogeneity of biological systems are formidable obstacles that must be overcome for achieving a more quantitative and predictive understanding of physiology and phenotypes on the cellular or organism scale. Such a level of understanding has remained largely elusive in biology, despite the extraordinary level of detail to which molecular interactions have been characterized over the past decades, as it often remains unclear how to harness detailed molecular knowledge to achieve this goal.
The Baym Lab focuses on the evolution of antibiotic resistance, with a goal of developing practical interventions to reduce or reverse resistance. We use a combination of experimental evolution of resistance and computational genomics on clinical samples to learn how resistance evolves and how we might intervene in this process.
Quantitative modeling of complex phenomena in science and engineering.
The Bulyk Lab investigates transcriptional regulation. We are particularly interested in transcriptional enhancers and the interactions between sequence-specific transcription factors and their DNA binding sites. For these studies, we develop genomic, proteomic, and computational technologies and approaches and apply them to a wide variety of biological organisms including the yeast S. cerevisiae, the fruit fly D. melanogaster, mouse and human.
New "omic" measurement technologies (such as FISSEQ) and synthesis and modeling/CAD/analysis tools for gene therapy, whole brain, embryonal and ecological systems.
We develop high-resolution genomic approaches to understand the molecular mechanisms that control transcription and co-transcriptional processes, such as nascent elongating transcript sequencing (NET-seq), which provides a quantitative measure of RNA polymerase density across the genome with single nucleotide precision.
The Cluzel laboratory studies biological signal integration and genetic networks at the single-cell level. We use real-time systems analysis to investigate how single cells respond to information in their environment. Our systems of interest include multi-drug resistance in E. coli and S. aureus, transcriptional dynamics of flagellar genes in bacteria, and degeneracy in the genetic code.
The Cohen lab develops physical tools to study molecules and cells. We work on imaging voltage in brains, hearts, embryos, and microorganisms; we study DNA mechanics; we study the effects of weak magnetic fields on chemical reactions; and we study the fundamental physics of light-matter interactions.
The Denic lab takes advantage of novel methodologies for studying large-scale genetic interactions in budding yeast as well as mass spectrometry-based characterization of natively-isolated protein complexes in order to identify the essential components required for several membrane-associated cellular processes. We then carry out targeted and systematic biochemical reconstitution strategies using the identified components in order to go from parts lists to functional and mechanistic insights.
Our long-term goal is to understand how regulatory DNA dictates transcriptional network behavior and, ultimately, organismal phenotype and evolution. Our approach is mechanistically motivated: we believe that understanding the molecular mechanisms that drive transcription will lead to models of gene regulation that can predict the functional consequences of regulatory sequence changes and guide production of new types of regulatory circuits.
Mathematical models of evolutionary dynamics, theoretical population genetics, and experimental evolution, all with the goal of understanding how natural selection shapes genetic variation.
The Doyle lab’s research is focused on two areas: (i) design of algorithms for biomedical devices, and (ii) the application of control & dynamics tools to problems in systems biology, including circadian gene regulation and biomarker identification.
Exploring the molecular logic of olfactory signaling underlying the coding of odorant- and pheromone-mediated signals and studying the developmental processes that ensure appropriate neuronal connections between the olfactory sensory neurons and the brain.
My research currently focuses on the development of computational methods for RNA, protein, and genome sequence analysis, using probabilistic modeling approaches. Two areas of particular interest are remote protein homology detection, and RNA structure and sequence analysis.
The Extavour lab focuses primarily on the evolution and development of reproductive systems, including both the germ line and the somatic components of the gonad.
Towards a detailed mechanistic understanding, the Fischer lab has set out to reconstitute complex biochemical processes in recombinant systems and to study the structure function and regulation of ubiquitin ligases. We currently focus on modular systems, such as Cullin RING ligases, which enable more straight forward dissection of function due to the inherent modularity of the multi-component ligase complex. We employ structural biology tools (X-ray crystallography and single particle cryo-EM) combined with biophysical and functional assays.
The Fontana lab combines experimental and theoretical approaches to address fundamental problems in systems biology as they relate to aging (C.elegans), plasticity in molecular signaling, and the evolvability of phenotype.
The Garner lab studies the organization, structure, and dynamics of the prokaryotic cytoplasm. Generally, we are interested in elucidating how small collections of genes are able to impart long range order to cells. Currently, we are using a combination of sub-diffraction imaging, particle tracking, and biochemistry to dissect the mechanistic process of how cells grow and divide. We can observe single molecules of the cell wall synthesis machinery move directionally around the cell circumference, and we are working to understand how these motions create the emergent shape of cells and how they are relate to the control of cell growth.
In the Gibbs Lab, we utilize the bacterium Proteus mirabilis as a model system of self versus non-self recognition.
We study how pathogens evolve and spread through populations, using genomics, mathematical modeling, and epidemiological tools.
The Gray lab studies how transcriptional networks rewire neuronal circuits.
The Gunawardena lab studies information processing in mammalian cells using a combination of experimental, theoretical and computational approaches.
The Hekstra lab focuses on the study of the mechanics of biomolecules, and more generally the role of physical and evolutionary forces in shaping biological systems.
The Higgins lab combines medical insight, dynamic systems theory, and experiments utilizing microfluidics, video processing, flow cytometry, simulation, and large-scale analysis of medical databases to measure and model the dynamics of human pathophysiologic processes.
The Hoekstra Lab uses wild mice as a model to understand how genetic variation translates to natural variation in morphology and behavior.
In the Hormoz lab, we combine experiments and theory to understand the complex dynamics of cell state transitions in development and in disease. To do so, we expand and combine emerging experimental techniques.
The Huttenhower lab focuses on the human microbiome, computational metagenomics, sequencing-based microbial community studies, and large-scale biomolecular network analysis.
The Kirschner lab studies spatial organization and temporal control in several different biological contexts, including the cell cycle, the cytoskeleton, and embryonic development. They also study a number of important signaling pathways, notably the Wnt pathway and various post-translational modification systems.
Dr. Klein is fascinated by the question of how stem cells choose between alternative fates in developing and adult tissues.
The Lahav lab is using quantitative live-imaging and computational approaches to study how individual human cells “make decisions” in response to external and internal signals. We focus on networks related to cancer development including the DNA damage response and the network regulating the tumor suppressor protein p53.
The Levine lab studies coordinated regulation at the mRNA level and coordination between regulatory modules.
The Losick lab seeks to elucidate the regulatory network that governs the conversion of a growing cell into a spore in the bacterium Bacillus subtilis. This developmental process is orchestrated by the programmed expression of over five hundred genes and involves multiple, novel signal transduction pathways, a bistable switch and dynamic changes in the subcellular localization of regulatory and morphogenetic proteins.
My lab is trying to understand how the cell achieves accurate control of protein degradation and how its failure may lead to neurodegeneration and aging.
Evolution has deposited rich information in the genomes of all species over time, as a result of mostly hidden functional constraints. The Marks lab will provide mathematical and computational bridge that can exploit this information to address critical challenges in biomedical research such as the consequences of human genetic variation, mutation effect on disease likelihood, drug resistance and drug response.
The Megason lab is interested in how the program contained in the genome is executed during development to turn an egg into an embryo. We use confocal/2-photon imaging of living, transgenic zebrafish embryos to watch biological circuits function in vivo and use these data in cell-based, quantitative modeling.
We are interested in using the tools of theoretical evolutionary biology, applied mathematics, statistics, and computational biology to address important questions in cancer research.
We work on fundamental questions of how cells are spatially organized applied problems in pharmacology and drug development. We ask how systems comprising microtubules, binding proteins and motors self-organize to promote cell division in frog eggs using microscopy and biochemistry. We work on the pharmacology of microtubule-targeting drugs, and to development new drug that combat cancer and inflammation by modulating innate immunity.
The Mootha lab aims to characterize the structure and dynamic properties of the biological networks underlying mitochondrial function, link variation in these parameters to genetic variation, and exploit the network properties of the organelle to design therapies for human disease.
We use budding yeast in three different ways: 1) to experimentally evolve novel traits, such as multicellularity and circadian clocks, 2) to test our understanding of interesting biological traits by trying to engineer them, and 3) to dissect the regulation of cell biologically interesting processes like polarization, energy homeostasis, and the regulation of the cell cycle.
Combining quantitative experiments and theory to understand the architecture and dynamics of self-organizing, subcellular structures, particularly the metaphase spindle.
Mathematical models of biological systems and evolutionary phenomena, including evolution of cooperation, population structure, evolutionary game theory, evolutionary graph theory, virus infections and somatic evolution of cancer.
The Paulsson lab is interested in the sources and consequences of biological noise. They derive mathematical methods to interpret and analyze noise, develop experimental methods to count molecules in single cells, and combine theory and experiment to study the behavior of the simplest natural and engineered networks.
The research in our lab is directed towards answering two questions: How do cells and organisms process signals from their environment? and How do the underlying molecular pathways evolve?
The Regev lab uses systematic computational and experimental approaches to understand biological circuits on a genome-wide scale. Focusing on carefully selected cell systems, we measure the output of a circuit using genomic tools, generate a computational model that explains our observations, and experimentally perturb key components to test and refine the model.
We use statistical genetics and ancient DNA to student human history and biology.
The Sabeti's lab aims to study the effect of natural selection on the human genome and on the genomes of other organisms and uncover the traits that have emerged to shape these species, and to understand mechanisms of evolutionary adaptation in humans and pathogens.
The Sander lab focuses on computational & systems biology, statistical physics, and cancer therapeutics.
The Shakhnovich Biophysics Lab works on a broad range of topics from Molecular Evolution and Origins of Life to Drug Discovery. Our approach integrates theoretical, computational and experimental work.
The Shih lab designs principles for self-assembling molecular machines, primarily using structural DNA nanotechnology to build our model systems. We seek to apply our knowledge towards construction of artificial systems that help solve problems of biological and medical interest. Currently we focus on single-macromolecule identification and structure determination and on vaccine nanocarriers. For many applications, our present capabilities are too primitive. Thus we also investigate enabling technologies for increasing the complexity of programmable self-assembled systems.
The Silver Lab works at the interface between systems and synthetic biology to design and build biological systems in mammalian and prokaryotic cells. Current projects include cell-based computing, synthetic chromosomes, novel biological therapeutics and engineering sustainability.
The Singer Lab centers on elucidating the function and underlying regulation of the immune component in tissue, focusing on cancer and autoimmunity. To this end my group designs and implements statistical and machine-learning frameworks for the analysis ofhigh-throughput data from mouse model s and patient cohorts, generated within our lab or by collaborators. In our work we iterate between study design, data generation, data analysis and experimental validation.
The Sorger lab applies experimental and computational methods to the analysis of mechanical and regulatory processes controlling eukaryotic cell division. They seek to construct data-driven, systems-wide models of cellular function that contain detailed mechanistic information on the activities of individual proteins.
The Springer lab is interested in how evolution shapes and constrains how organisms respond to their environment. They analyze cellular responses in several related yeast species using a combination of in vivo fluorescence, synthetic and genetic approaches, and numerical and analytical modeling.
The primary focus of research in the lab is on genetic variation, including the biology and evolution of mutation, the effect of variation on molecular function and structure, population genetics as a lens on evolution, and the maintenance and allelic architecture of complex traits. We develop computational and statistical methods for sequencing studies. We also have projects in cancer genomics and applied human genetics. The lab encompasses a wide range of skills, backgrounds, and interests spanning these topics.
The Weissleder lab is interested in the development of novel in vivo imaging methods for studying complex human diseases such as cancer and infectious diseases. The lab is also involved in translating these discoveries into the development of new diagnostic devices and drugs.
The Yin lab’s research lies at the interface of information science, molecular engineering, and biology. They are generally interested in developing programmable molecular systems and technology inspired by biology.
The Zhuang research lab works on the forefront of single-molecule biology and bioimaging, developing and applying advanced optical imaging techniques to study the behavior of individual biological molecules and complexes in vitro and in live cells.