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Portrait Adele Doyle

Cells in living organisms are surrounded by physical cues, such as mechanical forces, material properties and electrical cues. These cues vary depending on their location in the body, so that different cells experience a variety of types, magnitudes, and dynamics of mechanical input. The ability of cells to take reliable decisions about cell behavior based on local physical cues is a key component of equilibrium in living organisms. However, the origin of specialized mechanosignaling in cells is not well understood. How do stem cells and other progenitor cells determine how to respond to physical cues in site-appropriate ways? When is specialized mechanosignaling necessary for successful embryonic development and organism homeostasis?

Our group studies how stem cells learn to respond to mechanical forces and electrical cues during the development and maintenance of the nervous and cardiovascular organ systems. We use approaches from biology, engineering, and computer science to study the molecular circuits that enable specialized mechanosignaling. We seek quantitative insights to help design cell and regenerative medicine therapies for neural and vascular applications.

Adele Doyle Research: Figure 2
Many genes involved in sensing and responding to physical cues, such as mechanical forces or electrical cues, are also involved in human diseases.

Future Projects and Goals

Our group uses tools from biomedical engineering, regenerative medicine, mechanobiology, and quantitative systems biology to study the mechanobiology of stem cells. Our ongoing and future research investigates the molecular circuits that allow cells to interpret mechanical forces and other physical cues (e.g. electrical cues), which are necessary for human development and health, especially relating to regenerative medicine. We investigate these circuits in the cardiovascular system and nervous system to determine how specialized responses to mechanical forces and physical cues are encoded in cells. Projects often involve both experimental and computational approaches. Collaborations with other groups are welcome.

Methodological and Technical Expertise

  • Stem Cells
  • Systems Biology
  • Engineered Cell Culture Systems (bioreactors, microscale devices)
  • Molecular Biology (RNA, protein)
  • Computational Biology & Bioinformatics


as of July 2021
Research Group Leader at the Cluster of Excellence Physics of Life, hosted at the Center for Regenerative Therapies (CRTD), TU Dresden

Since 2019
Assistant Professor, Department of Mechanical Engineering, University of California Santa Barbara

Assistant Researcher (PI), Neuroscience Research Institute, and Lecturer, Center for Bioengineering, University of California Santa Barbara

Postdoctoral Fellow, Harvard University, Center for Systems Biology

Ph.D. Biomedical Engineering, Georgia Institute of Technology & Emory University (United States)

Selected Publications

Walker JL, Patterson LHC, Rodriguez-Mesa E, Shields K, Foster JS, Valentine MT, Doyle AM, Foster KL
Controlled Single Cell Compression with a High-Throughput MEMS Actuator.
Journal of Microelectromechanical Systems 29(5), 790–796 (2020)

Patterson LHC, Walker JL, Rodriguez-Mesa E, Shields K, Foster JS, Valentine MT, Doyle AM, Foster KL
Investigating Cellular Response to Impact With a Microfluidic MEMS Device.
IEEE Journal of Microelectromechanical Systems 29(1):14–24 (2020)

Beach S*, Grundeen S*, Doyle A, Theogarajan L
Fabrication and Validation of Flexible Pillar Electrodes for Neural Electrophysiological Recording.
Engineering Research Express. 2(2): 025025 (2020)
* equal contributions

Jang S, Choubey S, Furchtgott L, Zou LN, Doyle AM, Menon V, Loew EB, Krostag A, Martinez RA, Madisen L, Levi BP, Ramanathan S
Dynamics of embryonic stem cell differentiation inferred from single-cell transcriptomics show a series of transitions through discrete cell states.
eLIFE 15:e20487 (2017)

Thomsen ER, Mich JK, Yao Z, Hodge RD, Doyle AM, Jang S, Shehata SI, Nelson AM, Shapovalova NV, Levi BP, Ramanathan S
Fixed single-cell transcriptomic characterization of human radial glial diversity.
Nature Methods 13: 87–93 (2016)