faculty

Chair

    Marc W. Kirschner Ph.D.

    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.

Department Faculty

    Angela DePace Ph.D.

    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.

    Roy Kishony Ph.D.

    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.

    Galit Lahav Ph.D.

    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 Ph.D.

    In creating the Broad Institute, Lander and colleagues have nucleated a community of researchers from the Cambridge-Boston area to tackle complex problems related to developing comprehensive tools for genomic medicine and applying them to the study of disease. This research effort requires cooperation across scientific disciplines from basic biology to chemistry, basic science to clinical science, and collaboration across institutions.

    Sean G. Megason Ph.D.

    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.

    Timothy J. Mitchison Ph.D.

    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.

    Vamsi Mootha M.D.

    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.

    Johan Paulsson Ph.D.

    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.

    Randall T. Peterson, Ph. D.

    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.

    Jagesh V. Shah Ph.D.

    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.

    Pamela A. Silver Ph.D.

    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.

    Peter Sorger Ph.D.

    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.

Lecturers & Instructors

    Gavin MacBeath Ph.D.

    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 Ph.D.

    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.

    Debora Marks, Ph.D.

    One million human genomes, will it make a difference?

     

    The large and growing volume of genome information, from all forms of life, presents unprecedented opportunities for computational biologists. The challenge for our scientific generation is to turn an avalanche of sequence information into meaningful discovery of biological principles, predictive methods, or strategies for molecular manipulation for therapeutic and biofuel discovery. 

    The Marks lab is a new interdisciplinary lab dedicated to developing rigorous computational approaches to critical challenges in biomedical research, particularly on the interpretation of genetic variation and its impact on basic science and clinical medicine. To address this we develop algorithmic approaches to biological data aimed at teasing out causality from correlative observations, an approach that has been surprisingly successful to date on notoriously hard problems. In particular, we developed methods adapted from statistical physics and graphical modeling to disentangle true contacts from observed evolutionary correlations of residues in protein sequences.  Remarkably, these evolutionary couplings, identified from sequence alone, supplied enough information to fold a protein sequence into 3D.  The software and methods we developed is available to the biological community on a public server that is quick and easy for non-experts to use. In this evolutionary approach to accurately we have predicted the 3D structure of hundreds of proteins and large pharmaceutically relevant membrane proteins. Many of these were previously of unknown structure and had no homology to known sequences; two of the large membrane proteins have now been experimentally validated. We have now applied this approach genome wide to determine the 3D structure of all protein interactions that have sufficient sequences and can demonstrate the evolutionary signature of alternative conformations. 

     

    The vision for the Marks lab is to build computational methods that address three critical challenges (i) protein conformational plasticity in health and disease, (ii) genome-wide evaluation of mutations on disease likelihood, antibiotic resistance and personal drug response, and (iii) synthetic protein design.

    Mario Niepel Ph.D.

    A key challenge in treating cancer is the wide range of effectiveness of current targeted therapeutics and the rapid development of resistance. I am trying to understand the mechanisms of drug responses and development of resistance using established breast cancer cell lines as a model system, since they mirror much of the behavior and heterogeneity of primary disease. I mainly study therapeutic drugs and ligands to receptor tyrosine kinases that modulate signaling through the ErbB family and the PI3K/AKT signaling pathways, which are particularly important in the development and treatment of breast and ovarian cancer. Ultimately, a detailed understanding of drug action will move us towards the development of a more personalized medicine, where tumors from each patient are analyzed on a molecular level so they can be treated with specifically tailored drugs or combinations that have been predicted to maximize efficacy and minimize the risk of resistance and toxicity.

    I focus most of my work on proteins, rather than genomic measures, since they are both the key effectors of cellular function and the targets of the drugs. In my research I combine a variety of protein profiling methods, detailed measurements of phenotypic responses, and biochemical investigation into drug action. I analyze the data by statistical and computational methods to identify both predictors of drug response and the causal determinants drug sensitivities.

    Caroline Shamu Ph.D.

    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.

Affiliated Faculty

    James Collins Ph.D.

    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.

    L. Mahadevan Ph.D.

    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.

Department Fellows

    Mohammed AlQuraishi PhD.

    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.

    Martin Loose Ph.D.

    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.

     

    Justin Meyer, Ph.D.

    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.

    Jeanne Salje Ph.D.

    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.