In Conversation with - George Bassel

01 October 2018 - By: Angie Burnett

In Conversation with - George Bassel

George Bassel photo_opt

George Bassel, Professor of Plant Computational Biology at the University of Birmingham, talks to plant physiologist Angie Burnett

AB: How would you define computational biology?

GB: Computational biology makes use of computer-based tools to better understand complex phenomena in biology. This allows multiple aspects of a biological system to be integrated in order to better understand how they create complicated behaviours. This is distinct from the study of biological computation, which seeks to understand how organisms make calculations to control their development.

AB: How did you get into this field?

GB: By following my curiosity. My first scientific training was in plant physiology and molecular genetics. This taught me about fundamental aspects of plant growth and development. However, I found there to be limits as to the types of questions these approaches can answer. For example, a gene can be linked to a phenotype, such as the development of a flower organ. But everything between the molecule (or molecules) this gene produces and the creation of a new organ remained enigmatic. This detailed understanding of individual components did not explain how they would interact to create an integrated system leading to the emergence of complex phenomena, such as organs and behaviours. In an effort to understand the basis of this emergence, I began reading about complex systems and network science. It turns out this is a very young, rapidly developing and exciting field. A particularly interesting aspect is the identification of conserved organisational and control principles in complex systems that span across domains ranging from the social sciences and economics to physics, biology and many others. Learning about these principles has both expanded my view of biology and exposed me to a diversity of new quantitative tools and approaches that can be used to address fundamental questions about how plants work. A conservation of control principles in information processing across domains is also emerging. For example, we have found interesting parallels between how this occurs in plants and human engineered computational systems. This provides opportunities for the exchange of knowledge across domains, and the ability to better understand how plants respond to the environment.

AB: Can your research1 be extended to other organisms?

GB: Yes absolutely! And vice versa. An exciting aspect of information processing research is the presence of conserved control mechanisms across diverse domains. For example, we recently demonstrated that the rate at which cells communicate in a dormant Arabidopsis seed impacts when the decision to terminate dormancy is reached2. A similar control mechanism is present in Red Harvester ants where communication rates impact decision making about foraging behaviour and which task an individual performs3. Engineered high performance computer architectures also modulate the communication rates between their processors to control the outputs of their computations. Biological and technological systems appear to both be controlling how they process information using similar principles.

AB: So how do plants make decisions?

GB: I don’t think we know the answer to that! While models can be made which provide plausible answers to this question, how this actually happens remains fuzzy. On the one hand we know how molecular networks are organised, and how they can generate outputs. In the case of multicellular plants, these networks are embedded across a large number of interconnected and communicating cells. The rate at which these networks operate in individual cells is asynchronous, and the speed at which they communicate their results to one another is unclear. How the collective calculations of communities of cells reach unified decisions represents a computational challenge known as the “majority voting problem”. The algorithms plants are employing to solve this problem remain unknown, and this represents a major outstanding question in the field.

AB: What are the main tools you use in your work?

GB: We use a combination of molecular genetics, 3D imaging, image analysis and network science. Work in the lab relies heavily on confocal microscopy and 3D image analysis. We prepare tissue samples by staining the cell walls with fluorescent dyes, then clarify the sample to make it transparent for imaging. The confocal microscope is then used to take a 3D image. This “z-stack” image is then analysed in a computer to identify how the cells are connected to one another. The cells and their connections are then turned into networks, which can be analysed using network science to understand how cells are organised.

AB: Do you have a favourite technique?

GB: I really appreciate what network science offers as a clever way of making complicated things simple. It is also a very young field that continues to undergo rapid development. I am finding it very exciting to be a part of this and to apply these techniques to plant science.

AB: What excites you most about computational biology?

GB: Making use of computers to understand how plants respond to their environment, while also using principles of computer science to better understand how information is processed in biology. These represent exciting research frontiers that are able to address questions that have not yet been fully explored.

AB: Of which achievement in your career so far are you proudest?

GB: Our recent study on the control of seed dormancy in Arabidopsis seeds2. We identified a decision-making centre in the radicle of the dormant embryo, having specialised cells which each promoted and inhibited germination, respectively. We went on to show that this configuration enhanced the computational capacities of the seed so that they could process alternating high and low temperatures as a cue to break dormancy. This provides an exciting example of how plants can make use of their multicellular body plans to enhance their ability to compute information from their environment.

AB: You’re organising an exciting session, Computation in Biological Systems, at SEB Seville. What can we look forward to?

GB: The session brings together researchers examining information processing in diverse biological systems and across different scales. My hope is that we will explore this frontier area of research through presentations and stimulating discussions, and explore similarities and differences in how this is done in different contexts. We had a similar session last year in Florence on Multicellular Complexity, also bringing together researchers from diverse backgrounds, and this proved to be a great success. The SEB provides an excellent platform to hold meetings on frontier multidisciplinary research areas, including an open and free environment to have productive discussions.


1. The Bassel lab
2. Topham et al. 2017
3. Greene and Gordon 2003

Category: Plant Biology
Angie White- RS

Angie Burnett

Angie Burnett studied Natural Sciences at the University of Cambridge before taking up the inaugural SEB PhD studentship, studying source-sink limitations of growth in barley at the University of Sheffield and Brookhaven National Laboratory, with Colin Osborne, Mark Rees and Alistair Rogers.  She has a keen interest in science communication and policy, having worked for The Conversation and completed work experience in the Houses of Parliament during her PhD.

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