Neil Dalchau

Neil Dalchau

I am a Scientist in the Biological Computation research group (part of Computational Science Laboratory) at Microsoft Research, Cambridge. I also hold an Honorary Senior Research Associate position at the Department of Chemistry, UCL.

My overall research interests are in how biological systems process information, perform computations, and make life-preserving decisions. The immune system is a great example of biological information processing, that operates at multiple temporal and spatial scales; without it, we'd struggle to survive again the many opportunistic pathogens that we encounter on a daily basis.

In addition to taking inspiration from understanding complex natural systems, I'm interested in engineering complex systems, using the building blocks of nature. Our project on Synthetic Biology seeks to understand how we can utilise the machinery of cells to perform new functions. Endowing cells with additional functions and refining their mechanisms enables us to enhance production of biofuels and medicine.

In all of our research areas, we are developing software tools to enable other researchers to understand or create biological function.


I started life as a mathematician, studying Mathematics at the University of Oxford, UK (2001-2005). I then went to the University of Cambridge to do a Ph.D, the project being a collaboration between Alex Webb's group at the Department of Plant Sciences and Jorge Goncalves in the Control Group at the Department of Engineering. You can download my thesis here.

Following my PhD, I briefly held a research associate position in the Control Group, working with Glenn Vinnicombe on applications of stochastic control theory to gene networks.

I came to Microsoft Research as a postdoc in 2009, during which I worked with Andrew Phillips on modelling immune systems and synthetic gene networks. I became a permanent member of the Biological Computation group in 2012.



  • Computational Modelling of Immune System Processes
    Immunodominance lies at the heart of the immune system's ability to distinguish self from non-self. Understanding and possibly controlling the mechanisms that govern immunodominance will have profound consequences for the fight against several classes of diseases, including viral infections and cancer. In the first phase of this project, we focus on computational modelling of MHC class I peptide editing.
  • A programming language for composable DNA circuits
    Recently, a range of information-processing circuits have been implemented in DNA by using strand displacement as their main computational mechanism. Examples include digital logic circuits and catalytic signal amplification circuits that function as efficient molecular detectors. As new paradigms for DNA computation emerge, the development of corresponding languages and tools for these paradigms will help to facilitate the design of DNA circuits and their compilation to nucleotide sequences.
  • A Programming Language for Genetic Engineering of Living Cells
    Synthetic biology aims at producing novel biological systems to carry out some desired and well-defined functions. An ultimate dream is to design these systems at a high level of abstraction using engineering-based tools and programming languages, press a button, and have the design translated to DNA sequences that can be synthesised and put to work in living cells.
  • Modelling of Circadian Oscillator Networks
    Circadian oscillators provide rhythmic temporal cues for a range of biological processes in animals and plants, enabling anticipation of the day/night cycle and enhancing fitness. Near 24 h oscillations are maintained at the gene transcription level, which integrate environmental cues such as light and temperature and internal cues such as metabolism and signalling. Characterising these interactions is vital for understanding how physiology is optimised with respect to the time of day.
  • 2020 Science
    The University College London and University of Oxford have recently received funding from the EPSRC Cross-Disciplinary Interfaces Programme (2020 Science: Mathematical and Computational Modelling of Complex Natural Systems) to collaborate with Microsoft Research Cambridge on a programme of research that will involve up to 17 post-doctoral Research Associates over a five year period.


    • Boyan Yordanov, Neil Dalchau, Paul Grant, Michael Pedersen, Stephen Emmott, Jim Haseloff, and Andrew Phillips, A Computational Method for Automated Characterization of Genetic Components, in ACS Synthetic Biology, American Chemical Society, 14 March 2014
    • James Osborne, Miguel Bernabeu, Maria Bruna, Ben Calderhead, Jonathan Cooper, Neil Dalchau, Sara-Jane Dunn, Alexander Fletcher, Robin Freeman, Derek Groen, Bernhard Knapp, Greg McInerny, Gary Mirams, Joe Pitt-Francis, Biswa Sengupta, David Wright, Christian Yates, David Gavaghan, Stephen Emmott, and Charlotte Deane, Ten simple rules for effective computational research, in PLoS Computational Biology, vol. 10, no. 3, pp. e1003506, PLoS Computational Biology (Public Library of Science Computational Biology), , March 2014