From the moment that a tumor is born, it is evolving across several levels: including at the genetic, epigenetic, metabolic, and microenvironmental levels. The central goal of the Jones Lab is to develop innovative computational and technological approaches to uncover the mechanisms of tumor evolution, with the ultimate aim of identifying new therapeutic targets and creating predictive models to monitor tumor initiation and progression. Matthew Jones’s research integrates advances in computation and high-throughput technologies to investigate the molecular mechanisms underlying the spatiotemporal dynamics of copy-number alterations (particularly extrachromosomal DNA) in cancer populations, develop new methods to trace cellular lineages; and elucidate the principles by which tumors are organized over time. 

Bruce Walker’s research focuses on mechanisms of immune control in chronic infection, focusing in particular on persons who control HIV infection spontaneously without the need for medication. The focus of the Walker Lab includes mechanisms of action of cytotoxic T cells, and mechanisms of T cell dysfunction using blood and lymph node samples collected from infected persons. The laboratory also focuses on hyperacute HIV infection through a collaboration in KwaZulu Natal South Africa where Dr. Walker helped build research capacity.  

James Collins's research focuses on synthetic biology and systems biology, with a particular focus on using network biology approaches to study antibiotic action, bacterial defense mechanisms, and the emergence of resistance. The Collins Lab has has created genetic toggle switches, RNA switches, programmable cells, genetic counters, genetic timers, kill switches for microbes, engineered bacteriophage to combat bacterial infections, and tunable mammalian genetic switches, each with broad applications in medicine and biotechnology. They have also shown that deep learning approaches can be used to discover and design novel antibiotics for treating resistant bacterial infections.

The Edelman Laboratory unites clinicians, engineers, and scientists from academia, industry, and medicine, who guided by a mechanistic understanding of biological and physical systems translate fundamental discoveries into tangible clinical advances. Projects range from examining fundamental basis of dynamical systems and complex diseases, to the interplay of mechanical support devices and native physiology, to investigation of the cellular and molecular mechanisms that govern vascular disease. Using the spectrum of resources from AI to imaging, single cell analysis to clinical trials the Lab transforms complex biological insights into innovative solutions that improve patient outcomes and redefine the boundaries between science and medicine.

Professor Gabrieli’s research focuses on the neural mechanisms of memory, cognition, and emotion in the human brain, and how those mechanisms are disrupted in neurological and psychiatric disorders.

Professor Gehrke’s research interests center on molecular aspects of host-pathogen interactions and on the pathogenesis of RNA viruses. Current experimental work focuses on understanding how viruses that are closely related in genetic sequence cause highly variable disease outcomes. Examples include Zika virus, which is correlated with birth defects including microcephaly, as well as dengue fever virus, which is in most cases a self-limited disease that does not cause congenital abnormalities. Cerebral organoids grown from human embryonic stem cells or human induced pluripotent stems cells closely mimic the human brain and serve as models for defining virus tropisms (which cells are infected) and subsequent effects on cell growth or cell death. Collaborative work with other IMES faculty permits three-dimensional imaging of virus infections, and single cell sequence analysis distinguishes transcriptional profiles in infected and uninfected cells.

Research in the Computational Cardiovascular Research Group is focused on three areas: 1) Understanding conformational changes in biomolecules that play an important role in common human diseases, 2) Using machine learning to develop models that identify patients at high risk of adverse clinical events, and 3) Developing new methods to discover optimal treatment strategies for high risk patients.  The group uses an interdisciplinary approach combining computational modeling and machine learning to accomplish these tasks.

High throughput sequencing of RNA populations revealed the generation of small RNAs from divergent transcription in mammalian cells. The role of this pervasive transcription is under investigation. We are investigating the roles of divergent transcription in the activity of super-enhancers of transcription. These super-enhancers form condensates with many properties expected of liquid-liquid phase transitions. Such condensates concentrate the multitude factors and RNA polymerases for initiation of a burst of transcription.

The interdisciplinary research in the Shalek Lab aims to create and implement new approaches to elucidate cellular and molecular features that inform tissue-level function and dysfunction across the spectrum of human health and disease. Professor Shalek’s research encompasses both the development of broadly enabling technologies as well as their application to characterize, model, and rationally control complex multicellular systems. Current studies with partners around the world seek to methodically dissect human disease to understand links between cellular features and clinical observations, including how: immune cells coordinate balanced responses to environmental changes with tissue-resident cells; host cell-pathogen interactions evolve across time and tissues during pathogenic infection; and, tumor cells evade homeostatic immune activity.

The human microbiome is remarkably personalized—even people living together harbor distinct microbial communities. On the skin, individuals in a family often share the same species yet harbor distinct but dynamic strain-level communities. This personalization may explain why most microbiome therapies fail to consistently engraft across patients. The Lieberman Lab seeks to understand how ecology and evolution shape these personalized communities, and the role of this personalization on human health. 

The Mirny lab combines quantitative, typically physics-rooted, approaches with analysis of genomics data to address fundamental problems in biology, most recently they focused on two problems: (1) higher-order chromatin structure; (2) evolution of cancer during neoplastic progression. Studies of the Mirny lab on chromosomes aim to characterize 3D architecture of the genome and processes that lead to its organization and reorganization in the cell cycle and development. Works of the Mirny lab on cancer aim at understanding the role of multiple “passenger” genetic events, such as individual mutations and chromosomal alterations, in cancer progression.

Are the mechanics and energetic requirements of human performance across the continuum of gravity from microgravity (0 G) to lunar and Martian gravity levels (1/6 G and 3/8 G, respectively) to hypergravity (>1 G) altered from the 1 G mechanics and energetics? The multidisciplinary research effort combines aerospace bioengineering, human-in-the-loop dynamics and control modeling, biomechanics, human interface technology, life sciences, and systems analysis and design. The research studies are carried out through flight experiments, ground-based simulations, and mathematical and computer modeling. Other research efforts include advanced space suit design and navigation aids for EVA astronauts.

Research in the Therapeutic Technology Design and Development Lab incorporates soft robotics, unique fabrication methods and computational analysis tools into the device design process to develop novel strategies for organ assist and tissue repair. We design and develop implantable medical devices that augment or assist native function.

Thomas’s research interests focus on signal processing, mathematical modeling, and model identification to support real-time clinical decision making, monitoring of disease progression, and titration of therapy, primarily in neurocritical and neonatal critical care. In particular, Thomas is interested in developing a mechanistic understanding of physiologic systems, and in formulating appropriately chosen computational physiologic models for improved patient care. His research is conducted in close collaboration with colleagues at MIT and clinicians from Boston-area hospitals.

The Bhatia Laboratory engineers micro and nanotechnologies, also called “tiny technologies,” to address complex challenges in human health ranging from cancer to liver disease and acquired infections. Operating at the interface of living and synthetic systems, the Bhatia group uses these miniaturization tools to improve areas of medicine including diagnostics, drug delivery, tissue regeneration, and disease modeling.

Focusing on the interface of fluid dynamics and epidemiology, The Fluid Dynamics of Disease Transmission Laboratory, within the Fluids and Health Network, led by Prof. Bourouiba, aims to elucidate the fundamental physical mechanisms shaping the transmission dynamics of pathogens in human, animal, and plant populations where drops, bubbles, multiphase and complex flows are at the core, in addition to broader questions at the intersection of health, broadly defined, and fluid physics.

Using combinations of likelihood, Bayesian, state-space, time-series and point process approaches, a primary focus of the research in my laboratory is the development of statistical methods and signal-processing algorithms for neuroscience data analysis.  We use a systems neuroscience approach to study how the state of general anesthesia is induced and maintained. To do so, we are using fMRI, EEG, neurophysiological recordings, micro dialysis methods and mathematical modeling in interdisciplinary collaborations with investigators in HST, the Department of Brain and Cognitive Sciences at MIT, Massachusetts General Hospital, and Boston University. 

The Chung Lab is an interdisciplinary research team devoted to developing and applying novel technologies for integrative and comprehensive understanding of large-scale complex biological systems. Specifically, they develop a host of methods that may enable rapid identification of multi-scale functional networks and interrogation of their system-wide, multifactorial interactions.