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.
The DePace lab studies the mechanism and evolution of gene regulation using the early development of 12 Drosophila species as a model system. Their goal is to understand how regulatory information is encoded in the genome, how it is deciphered as gene expression patterns in space and time, and how it changes during evolution.
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 Gunawardena lab studies information processing in mammalian cells using a combination of experimental, theoretical and computational approaches.
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.
Dr. Klein is fascinated by the question of how stem cells choose between alternative fates in developing and adult tissues.
The Kishony lab is interested in understanding the system-level architecture of genetic networks and the interplay between their design and the evolutionary process. They combine theoretical and experimental approaches to study epistasis networks – networks that describe how perturbations (mutations or drugs) in a given biological system combine to aggravate or alleviate each other’s effect on a phenotype.
The Lahav lab studies the temporal dynamics of biological signals by combining quantitative live imaging of single human cells with mathematical modeling. They primarily study the signaling pathway of the tumor suppressor p53, with the goal of understanding how the dynamic behavior of p53 is controlled, and how dynamics affects cell fate decisions.
Eric S. Lander received his B.A. in mathematics from Princeton University in 1978 and his Ph.D. in mathematics from Oxford in 1981, as a Rhodes Scholar. Heserved as assistant and associate professor of managerial economics at the Harvard Business School from 1981 to 1990. In 1986, he joined the Whitehead Institute for Biomedical Research and founded the Whitehead/MIT Center for Genome Research in 1990. Lander became the founding director of the newly created Broad Institute of Harvard and MIT in 2003. He is also professor of biology at MIT and member of Whitehead.
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.
My lab is interested in the structure, dynamics, and function of the cytoskeleton. We use imaging-based assays in living cells and in vitro extracts, in conjunction with molecular biology and biochemical fractionation approaches, as well as theory and modeling. Most of of the lab works on cell division in some way. One major focus is on the mechanism of mitotic spindle assembly in Xenopus egg extracts.
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.
The Paulsson laboratory 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.
Our group is interested in understanding how small molecules perturb complex in vivo processes. By conducting high-throughput chemical screens with intact, living zebrafish, we discover small molecules that alter these organismal processes. The novel small molecules become powerful probes for studying the phenomena of interest.
The Shah lab is interested in understanding how molecular events drive the behavior of cell-scale structures. They use molecular techniques and modern biophysical tools to develop quantitative models of endogenous and synthetic cellular networks.
The Silver Lab works at the interface between systems and synthetic biology to design and build biological systems in both mammalian and prokaryotic cells. Some current projects include analysis of cells that remember past events, cell-based computation and therapeutics, and metabolic engineering for bio-energy and sustainability.
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 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.
Lecturers & Instructors
Dr. Apfeld is interested in the relationship between age-dependent cellular events and the lifespan of multicellular organisms. He is developing methodologies to make age a quantifiable observable in the nematode C. elegans, a well-studied organism of 703 somatic cells and an average lifespan of only two weeks.
The MacBeath lab is interested in identifying, characterizing, and perturbing large collections of proteins or protein domains as a first step in understanding how the cell exploits molecular recognition to regulate complex processes such as protein trafficking, intercellular communication, growth factor signaling, and apoptosis.
Laura Maliszewski, PhD joined HMS in September 2012 to manage the development of the Laboratory of Systems Pharmacology and the Harvard Program in Therapeutic Science. She served previously as an Officer in the Science and Innovation Network of the UK Foreign and Commonwealth Office, developing a broad portfolio of research collaborations in regenerative medicine, health economics and stratified medicine.
I am a computational biologist interested in how to read the genome and interpret its variation. Recently, we have used evolutionary couplings determined from genomic sequencing to accurately protein 3D structure from sequences alone, including the experimentally challenging transmembrane proteins. Continuing from this my lab aims to predict alternative conformations and plasticity of proteins, and the consequences of protein genetic variation on pharmacological intervention.
I earned my Diplom in Molecular Biology from the RWTH Aachen in Germany and an M.S. in Biochemistry at UC Riverside in 1998. I received my Ph.D. in 2005 from the Rockefeller University in New York working in the Laboratory of Cellular and Structural Biology with Dr. Mike Rout. In 2006 I joined Dr. Peter Sorger’s laboratory as a postdoctoral fellow. I was promoted to Instructor in the Systems Biology Department at Harvard Medical School in 2009.
Dr. Peshkin is integrating diverse evolutionary and developmental clues to understand signaling pathways. He is particularly excited about informing experimental design by the Bayesian analysis framework.
Dr. Shamu is the Director of the ICCB-Longwood Screening Facility. The ICCB-Longwood Investigator Initiated Screening Program assists academic researchers in carrying out high-throughput screens of chemical and RNAi libraries to identify new tools for biological research. In addition to her expertise in implementing new high throughput assay technologies, Dr.Shamu is active in the development of data standards and repositories for large-scale datasets from high-throughput assays.
Dr. Xie's research has been mainly focused on developing customized image analysis solutions for quantitative imaging projects carried out across HMS. In biology and medical research, imaging has always been the most direct and informative readout. With the heavy investment in imaging platforms at HMS in recent years, the data being collected has quickly exceeded the capability for manual quantification. In addition to the fact that very limited number of existing solutions is available for common image analysis problem, the fact that every imaging project is designed to extract unique information making the development of customized solutions almost always a necessity.Dr. Xie has been working with the researchers at HMS and affiliated hospital to help extract data from their fluorescence images, time-lapse videos, EM images, etc. Education on image analysis to distribute his expertise has also been a main focus of his work here.
James J. Collins is an Investigator of the Howard Hughes Medical Institute, and a William F. Warren Distinguished Professor, University Professor, Professor of Biomedical Engineering, Professor of Medicine and Co-Director of the Center for BioDynamics at Boston University. He is also a core founding faculty member of the Wyss Institute for Biologically Inspired Engineering at Harvard University.
The Mahadevan group is interested in understanding the organization of matter in space and time, particularly at the scale observable by our unaided senses. We use a combination of techniques to pursue this, ranging from simple observations of phenomena to quantitative experiments and theory.
Dr. AlQuraishi's research interests lie at the intersection of systems and structural biology. He aims to obtain a systems-level understanding of biological processes through a molecular-level understanding of biological structures and their interactions. Towards that end he is developing computational methods for predicting the binding partners and quantitative binding affinities of biological molecules from their atomic structure. His work combines recent advances in machine learning and artificial intelligence with concepts from statistical mechanics and biophysics.
Dr. Loose's research goal is to investigate the mechanisms of biochemical self-organization. He is particularly interested in how minimal protein systems are able to organize intracellular space and how these biochemical modules are conserved or change during evolution. For this he mainly uses biochemical approaches and microscopic techniques.
Evolution is notoriously hard to predict primarily because a key population genetic term remains undefined: the fitness landscape. While often depicted in two dimensions, with hills and valleys, true fitness landscapes are many-dimensional with complicated interactions that cannot be described by the simple slopes of a hill. Until recently, the technology did not exist to permit direct experimental determination of landscapes. And even now, the technology is slow and much too laborious to capture the enormous size and dimensionality of landscapes.
One of the fundamental problems in biology is how the individual components of a cell act together to form the dynamic and responsive structure that is a living cell. E. coli is an excellent model system for studying basic questions of cellular self organisation due to the topological simplicity that results from a lack of membrane-bound subcellular organelles, the extensive knowledge of components that comes from decades of dedicated research, as well as the fact that as a single celled organism it is not subjected to organism-level complexity.
Dr. Wapinski's interests lie at the intersection of functional genomics and evolution. In the past he worked on studying how genomes and regulatory networks have evolved across large evolutionary distances through gene duplications and losses and by the re-wiring of regulatory circuitry.