Welcome to the Dal Co lab. We are part of the Department of Computational Biology, and of the Swiss National Centre of Competence in Research for Microbiomes. Read about how to Join us!
We study how functionality arises in biological systems. Our group is interested in a variety of systems, from microbial communities to organs. We investigate principles that drive multicellular organization and function. We do single cell experiments with microbial communities and we collaborate with groups working on other multicellular systems. We build computational models to uncover how interactions between single cells drive collective behavior and function.
Our group is interested in microbial ecology. A first central question in our research is: Can we predict the dynamics of microbial systems if we know how the individual cells interact? We address this question with single-cell experiments and modeling. We measure how single cells interact inside microbial communities, often using microscopy and microfluidics. We model these communities as systems composed of parts - the cells - that interact in space. With these models, we elucidate how properties of microbial communities (e.g. collective metabolism, response to environmental fluctuations and stresses) arise from the interactions that we observe between the single cells.
Our group is interested in collective behaviour. A second central question in our research is: How are cells programmed to produce specific multicellular behaviour? This question applies to both multicellular microbial systems and multicellular organisms. Multicellular microbial systems and multicellular organisms may share general organisational principles. We use modeling to infer which physical and biological interactions between cells are required to achieve target collective behaviours. Our group combines machine learning approaches with single-cell experimental data to understand and engineer collective behaviour. We are excited to collaborate with experimental groups working on different systems.
We are interdisciplinary. We believe that connecting disciplines is crucial for understanding any system of a certain complexity. For example, the properties of a society -studied by social scientists- arise from the properties of its components, the individuals -studied by psychologists; the properties of an atom -studied by chemists- arise from the properties of its elementary components -studied by particle physicists. Connecting fields generally unlocks tremendous scientific potential. We connect disciplines to elucidate how complex biological systems function.
Our group at the University of Lausanne, headed by Prof. Alma Dal Co, studies the dynamics and function of multicellular systems with modeling and experimental approaches. Candidates at all levels should have a good quantitative background. We greatly value curiosity, creativity, and drive to discover and learn new things.
Postdocs. We welcome fellowship-funded postdocs. Please contact us (email@example.com) in advance of the relevant fellowship submission deadline. We are happy to discuss suitable projects and support you in the writing. Here you find a list of relevant fellowships:
PhD students. We do not have positions now, but positions will open in the future. You can contact us in advance if you are interested in joining us for your PhD (firstname.lastname@example.org).
Master students. You can contact us directly via email (email@example.com). Please write a short description of why you are interested in doing your master thesis in our group.
Projects are available in two major research areas:
Interactions in microbial communities. Microbial communities perform fundamental processes on Earth. Microbial communities in the soil and the sea cycle the elements, and microbial communities in our gut shape our health. The processes that these microbial communities perform arise from interactions between different species. Our goal is to uncover the network of interaction in these systems and understand how collective processes arise. We measure interactions with single-cell experimental techniques, including microscopy and microfluidics. We build mathematical models to elucidate how the activities of the single cells and their interactions drive community properties such as growth, response to environmental fluctuations and stresses. We have projects with synthetic and natural communities.
Programming collective behavior of cells. Cells have the intrinsic ability to self-organize into functional assemblies. A central question is how cells are programmed to grow into these functional assemblies. We model physical and biological interactions occurring in multicellular systems and use machine learning methods to uncover which cell-to-cell interactions lead to specific collective behaviour. We build our models on single-cell data in collaborations with experimental labs working on organs and tissues.
We offer an inspiring working environment with very competitive salaries. Our group fosters collaborative and interdisciplinary work. We offer great creative freedom and we provide opportunities for career and personal development. Switzerland offers high life-style and fantastic nature. Our lab strives to having members with a diversity of backgrounds and identities. We believe this diversity fosters creativity.
J. van Gestel*1, T. Bareia*1, B. Tenennbaum, A. Dal Co, P Guler, N. Aframian, S. Puyesky, I. Grinberg, G. D’Souza, Z.Erez, M. Ackermann, A. Eldar*
Nature Communications (2021)
A. Dal Co*, S. van Vliet, D. Kiviet, S. Schlegel & M. Ackermann
Nature Ecology and Evolution (2020)
A. Dal Co*,1, S. van Vliet*,1 & M. Ackermann
Philos. Trans. of the Royal Society B (2019)
A. Dal Co*, M. Ackermann & S. van Vliet*
Journal of the Royal Society Interface (2019)
S. van Vliet*, A. Dal Co, A. R. Winkler, S. Spriewald, B. Stecher & M. Ackermann
Cell Systems (2018)
N. Nikolic*, F. Schreiber, A. Dal Co, D.J. Kiviet, T. Bergmiller, S. Littmann, M. Kuypers & M. Ackermann
PLOS Genetics (2017)
K. Moor, M. Diard, M.E. Sellin, B. Felmy, S.Y. Wotzka, A. Toska, E. Bakkeren, M. Arnoldini, F. Bansept, A. Dal Co, T.Völler, A. Minola, B. Fernandez-Rodriguez, G. Agatic, S. Barbieri, L. Piccoli, C. Casiraghi, D. Corti, A. Lanzavecchia, R.R. Regoes, C. Loverdo, R. Stocker, D.R. Brumley*, W.D. Hardt* & E. Slack*
University of Lausanne
Department of Computational Biology
|Since 09.2021||Assistant professor, University of Lausanne|
|2019-21||Postdoctoral Fellow, Harvard University, group of Michael Brenner|
|2014-19||PhD in Systems Biology, ETH Zurich, group of Martin Ackermann|
|2012-14||M.Sc. Physics of Complex Systems, University of Turin|
|2008-11||B.Sc. Physics, University of Padua|
|2002-12||Piano Master Degree, Conservatory of Venice|