An Investigation and Application of Biology and Bioinformatics for Activity Recognition

Activity recognition in a smart home context is inherently difficult due to the variable nature of human activities and tracking artifacts introduced by video-based tracking systems. This thesis addresses the activity recognition problem via introducing a biologically-inspired chemotactic approach and bioinformatics-inspired sequence alignment techniques to recognise spatial activities. The approaches are demonstrated in real world conditions to improve robustness and recognise activities in the presence of innate activity variability and tracking noise

Methodology for identifying alternative solutions in a population based data generation approach applied to synthetic biology

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonDesign is an essential component of sustainable development. Computational modelling has become a useful technique that facilitates the design of complex systems. Variables that characterises a complex system are encoded into a computational model using mathematical concepts and through simulation each of these variables alone or in combination are modified to observe the changes in the outcome. This allows the researchers to make predictions on the behaviour of the real system that is being studied in response to the changes. The ultimate goal of any design process is to come up with the best design; as resources are limited, to minimize the cost and resource consumption, and to maximize the performance, profits and efficiency. To optimize means to find the best solution, the best compromise among several conflicting demands subject to predefined requirements. Therefore, computational optimization, modelling and simulation forms an integrated part of the modern design practice. This thesis defines a data analytics driven methodology which enables the identification of alternative solutions of computational design by analysing the generational history of the population based heuristic search used to generate the templates. While optimisation is focused on obtaining the optimal solution this methodology focuses on alternative solutions which are sub optimal by fitness or solutions with similar fitness but different structures. When the optimal design solution is less robust, alternative solutions can offer a sufficiently good accuracy and an achievable resource requirement. The main advantage of the methodology is that it exploits the exploration process of the solution space during a single run, by focusing also on suboptimal solutions, which usually get neglected in the search for an optimal one. The history of the heuristic search is analysed for the emergence of alternative solutions and evolving of a solution. By examining how an initial solution converts to an optimal solution core design patterns are identified, and these were used to improve the design process. Further, this method limits the number of runs of the heuristic search as more solution space is covered. The methodology is generic because it can be used to any instance where a population based heuristic search is applied to generate optimal designs. The applicability of the methodology is demonstrated using three case studies from mathematics (building of a mathematical function for a set target) and biology (obtaining alternative designs for genomic metabolic models [GEM] and DNA walker circuits). In each case a different heuristic search method was used: Gene expression programming (mathematical expressions), genetic algorithms (GEM models) and simulated annealing (DNA walker circuits). Descriptive analytics, visual analytics and clustering was mainly used to build the data analytics driven approach in identifying alternative solutions. This data analytics driven methodology is useful in optimising the computational design of complex systems

From Epidemic to Pandemic Modelling

We present a methodology for systematically extending epidemic models to multilevel and multiscale spatio-temporal pandemic ones. Our approach builds on the use of coloured stochastic and continuous Petri nets facilitating the sound component-based extension of basic SIR models to include population stratification and also spatio-geographic information and travel connections, represented as graphs, resulting in robust stratified pandemic metapopulation models. This method is inherently easy to use, producing scalable and reusable models with a high degree of clarity and accessibility which can be read either in a deterministic or stochastic paradigm. Our method is supported by a publicly available platform PetriNuts; it enables the visual construction and editing of models; deterministic, stochastic and hybrid simulation as well as structural and behavioural analysis. All the models are available as supplementary material, ensuring reproducibility.Comment: 79 pages (with Appendix), 23 figures, 7 table

Genome Editing for Low-Acrylamide Wheat

Acrylamide (C3H5NO) is a food processing contaminant that has been classed as a probable (Group 2a) human carcinogen. Acrylamide forms from the reaction of free (non-protein) asparagine with reducing sugars during food processing. All major cereal products are affected and wheat products represent one of the main sources of dietary acrylamide intake in Europe. Asparagine concentration is the determining factor for acrylamide formation in cereal products. Asparagine biosynthesis is catalysed by a family of enzymes called asparagine synthetases (ASNs). The ASN genes were investigated and five ASN genes (TaASN1-4, with a double copy of TaASN3) identified in wheat (Triticum aestivum), with TaASN2 showing grain-specific expression. CRISPR/Cas9 was used to knock out the TaASN2 gene of wheat cv. Cadenza. A polycistronic gene containing four gRNAs, interspaced with tRNAs, was designed and introduced into wheat embryos by particle bombardment. The subsequent edits were characterised in the T1 and T2 generations using Next Generation Sequencing nucleotide sequence analysis. Triple (A, B, and D genome) nulls were identified, alongside an AD and an A genome null. Amino acid concentrations were measured in the T2 and T3 seed, with one triple null line showing a substantial reduction in the free asparagine concentration in the grain (90 % in the T2 seed and 50 % in the T3 seed compared with wildtype). The free asparagine also reduced as a proportion of the total free amino acid pool. Significant effects were also seen in glutamate and aspartate concentrations. Free asparagine and total free amino acid concentrations were higher in the T3 than T2 seeds, probably due to heat stress, but the concentrations in the edited plants remained substantially lower than in wildtype. Some of the edited lines showed poor germination, but this could be overcome by application of exogenous asparagine and no other phenotype was noted

Genome editing for low acrylamide wheat

Acrylamide (C3H5NO) is a food processing contaminant that has been classed as a probable (Group 2a) human carcinogen. Acrylamide forms from the reaction of free (non-protein) asparagine with reducing sugars during food processing. All major cereal products are affected and wheat products represent one of the main sources of dietary acrylamide intake in Europe. Asparagine concentration is the determining factor for acrylamide formation in cereal products. Asparagine biosynthesis is catalysed by a family of enzymes called asparagine synthetases (ASNs). The ASN genes were investigated and five ASN genes (TaASN1-4, with a double copy of TaASN3) identified in wheat (Triticum aestivum), with TaASN2 showing grain-specific expression. CRISPR/Cas9 was used to knock out the TaASN2 gene of wheat cv. Cadenza. A polycistronic gene containing four gRNAs, interspaced with tRNAs, was designed and introduced into wheat embryos by particle bombardment. The subsequent edits were characterised in the T1 and T2 generations using Next Generation Sequencing nucleotide sequence analysis. Triple (A, B, and D genome) nulls were identified, alongside an AD and an A genome null. Amino acid concentrations were measured in the T2 and T3 seed, with one triple null line showing a substantial reduction in the free asparagine concentration in the grain (90 % in the T2 seed and 50 % in the T3 seed compared with wildtype). The free asparagine also reduced as a proportion of the total free amino acid pool. Significant effects were also seen in glutamate and aspartate concentrations. Free asparagine and total free amino acid concentrations were higher in the T3 than T2 seeds, probably due to heat stress, but the concentrations in the edited plants remained substantially lower than in wildtype. Some of the edited lines showed poor germination, but this could be overcome by application of exogenous asparagine and no other phenotype was noted

Development of methods for combinational approaches to cis-regulatory module interactions

The complexity and size of the higher animal genome and relative scarcity of DNA-binding factors with which to regulate it imply a complex and pleiotropic regulatory system. Cisregulatory modules (CRMs) are vitally important regulators of gene expression in higher animal cells, integrating external and internal information to determine an appropriate response in terms of gene expression by means of direct and indirect interactions with the transcriptional machinery. The interaction space available within systems of multiple CRMs, each containing several sites where one or more factors could be bound is huge. Current methods of investigation involve the removal of individual sites or factors and measuring the resulting effect on gene expression. The effects of investigations of this type may be masked by the functional redundancy present in some of these regulatory systems as a result of their evolutionary development. The investigation of CRM function is limited by a lack of technology to generate and analyse combinatorial mutation libraries of CRMs, where putative transcription factor binding sites are mutated in various combinations to achieve a holistic view of how the factors binding to those sites cooperate to bring about CRM function. The principle work of this thesis is the generation of such a library. This thesis presents the development of microstereolithography as a method for making microfluidic devices, both directly and indirectly. A microfluidic device was fabricated that was used to generate oligonucleotide mixtures necessary to synthesise combinatorial mutants of a CRM sequence from the muscle regulatory factor MyoD. In addition, this thesis presents the development of the optimisation algorithms and assembly processes necessary for successful sequence assembly. Furthermore, it was found that the CRM, in combination with other CRMs, is able to synergistically regulate gene expression in a position and orientation independent manner in three separate contexts. Finally, by testing a small portion of the available combinatorial mutant library it was shown that mutation of individual binding sites within of the CRM is not sufficient to show a significant change in the level of reporter gene expression