2 research outputs found
Biomolecular System Design: Architecture, Synthesis, and Simulation
The advancements in systems and synthetic biology have been broadening the range of realizable systems with increasing complexity both in vitro and in vivo. Systems for digital logic operations, signal processing, analog computation, program flow control, as well as those composed of different functions â for example an on-site diagnostic system based on multiple biomarker measurements and signal processing â have been realized successfully. However, the efforts to date tend to tackle each design problem separately, relying on ad hoc strategies rather than providing more general solutions based on a unified and extensible architecture, resulting in long development cycle and rigid systems that require redesign even for small specification changes.Inspired by well-tested techniques adopted in electronics design automation (EDA), this work aims to remedy current design methodology by establishing a standardized, complete flow for realizing biomolecular systems. Given a behavior specification, the flow streamlines all the steps from modeling, synthesis, simulation, to final technology mapping onto implementing chassis. The resulted biomolecular systems of our design flow are all built on top of an FPGA-like reconfigurable architecture with recurring modules. Each module is designed the function of eachmodule depends on the concentrations of assigned auxiliary species acting as the âtuning knobs.â Reconfigurability not only simplifies redesign for altered specification or post-simulation correction, but also makes post-manufacture fine-tuning â even after system deployment â possible. This flexibility is especially important in synthetic biology due to the unavoidable variations in both the deployed biological environment and the biomolecular reactions forming the designed system.In fact, by combining the systemâs reconfigurability and neural networkâs self-adaptiveness through learning, we further demonstrate the high compatibility of neuromorphic computation to our proposed architecture. Simulation results verified that with each module implementing a neuron of selected model (ex. spike-based, threshold-gate-like, etc.), accompanied by an appropriate choice of reconfigurable properties (ex. threshold value, synaptic weight, etc.), the system built from our proposed flow can indeed perform desired neuromorphic functions
Continuous-time temporal logic specification and verification for nonlinear biological systems in uncertain contexts
In this thesis we introduce a complete framework for modelling and verification of biological systems in uncertain contexts based on the bond-calculus process algebra and
the LBUC spatio-temporal logic. The bond-calculus is a biological process algebra which
captures complex patterns of interaction based on affinity patterns, a novel communication
mechanism using pattern matching to express multiway interaction affinities and general
kinetic laws, whilst retaining an agent-centric modelling style for biomolecular species.
The bond-calculus is equipped with a novel continuous semantics which maps models to
systems of Ordinary Differential Equations (ODEs) in a compositional way.
We then extend the bond-calculus to handle uncertain models, featuring interval uncertainties in their species concentrations and reaction rate parameters. Our semantics is also
extended to handle uncertainty in every aspect of a model, producing non-deterministic
continuous systems whose behaviour depends either on time-independent uncertain parameters and initial conditions, corresponding to our partial knowledge of the system at
hand, or time-varying uncertain inputs, corresponding to genuine variability in a systemâs
behaviour based on environmental factors.
This language is then coupled with the LBUC spatio-temporal logic which combines
Signal Temporal Logic (STL) temporal operators with an uncertain context operator
which quantifies over an uncertain context model describing the range of environments
over which a property must hold. We develop model-checking procedures for STL and
LBUC properties based on verified signal monitoring over flowpipes produced by the
Flow* verified integrator, including the technique of masking which directs monitoring for
atomic propositions to time regions relevant to the overall verification problem at hand.
This allows us to monitor many interesting nested contextual properties and frequently
reduces monitoring costs by an order of magnitude. Finally, we explore the technique
of contextual signal monitoring which can use a single Flow* flowpipe representing a
functional dependency to complete a whole tree of signals corresponding to different
uncertain contexts. This allows us to produce refined monitoring results over the whole
space and to explore the variation in system behaviour in different contexts