Research in SENSe
Algorithmic Biology
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The use of computational modelling and complexity theory to understand the underlying algorithmic principles of biological systems.
Example topics: the major transitions in evolution, the evolution of sex, symbiosis and symbiogenesis, ecosystem selection in biofilms, networks.
Bio-inspired Computing
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The development of algorithms and architectures inspired by natural selection and the decentralised organisation of swarms, brains, immune systems, etc.
Example topics: immune system behaviour, coevolutionary algorithms for multiplayer games of imperfect information, decentralised computing architectures, neuromodulation, robust analog circuits.
Biological Self-assembly
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The study and manipulation of self-assembling biological molecules and their designed synthetic analogues to enable bottom-up construction of nano/micro-scale devices such as biosensors.
Example topics: lipidic building blocks of cell membranes, lipid polymorphism, semiconductor-tethered liposomes, biotin-avidin interactions, supramolecular complexes, drug delivery.
Complex Networks
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Applying and extending network theory to deal with the large-scale and topologically complex networks found in domains such as biology, computing, geography and knowledge representation.
Example topics: constraints on networks due to spatial layout, integration of multiple interacting networks, network sampling, network structure in markets, ontology networks, social networks.
Ecological & Evolutionary Modelling
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The application of modelling techniques developed in artificial intelligence to problems in ecology and evolution.
Example topics: collective building behaviour in insects, the evolution of signalling and communication, social learning behaviour, mimicry, development of sophisticated wireless sensor nodes, the epistemological status of evolutionary simulation models.
Informed Matter
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Eliciting the principles of nature's molecular level information processing and applying them to the development of molecular devices and the directed complexification of matter.
Example topics: The use of biological cells in robot control, microfluidic systems for enzymatic computation, computational design of molecular components for information processors, theoretical models of noise-driven behaviour in stochastic genetic and signalling systems.
Some additional information on the research interests of individual group members is also available.
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