Abstract: Morphogenetic modelling and simulation help to understand the processes by which the form and shapes of organs (organogenesis) and organisms (embryogenesis) emerge. This requires two mutually coupled entities: the biomolecular signalling network and the tissue. Whereas the modelling of the signalling has been discussed and used in a multitude of works, the realistic modelling of the tissue has only started on a larger scale in the last decade. Here, common tissue modelling techniques are reviewed. Besides the continuum approach, the principles and main applications of the spheroid, vertex, Cellular Potts, Immersed Boundary and Subcellular Element models are discussed in detail. In recent years, many software frameworks, implementing the aforementioned methods, have been developed. The most widely used frameworks and modelling markup languages and standards are presented.
Abstract: There are numerous phylogenetic reconstruction methods and models available—but which should you use and why? Important considerations in phylogenetic analyses include data quality, structure, signal, alignment length and sampling. If poorly modelled, variation in rates of change across proteins and across lineages can lead to incorrect phylogeny reconstruction which can then lead to downstream misinterpretation of the underlying data. The risk of choosing and applying an inappropriate model can be reduced with some critical yet straightforward steps outlined in this paper. We use the question of the position of the root of placental mammals as our working example to illustrate the topological impact of model misspecification. Using this case study we focus on using models in a Bayesian framework and we outline the steps involved in identifying and assessing better fitting models for specific datasets.
Abstract: Computational and mathematical modeling is important in support of a better understanding of complex behavior in biology. For the investigation of biological systems, researchers have used computers to construct, verify, and validate models that describe the mechanisms behind biological processes in multi-scale representations. In this paper we combine Petri net models that represent the mycobacterial infection process and innate immune response at various levels of organization, from molecular interaction to granuloma dissemination. In addition to the conventional graphical representation of the Petri net, the outcome of the model is projected onto a 3D model representing the zebrafish embryo. In this manner we provide a visualization of the process in a simulation framework that portrays the infection in the living system.
Abstract: Mechanical Heating Ventilation and Air-Conditioning (HVAC) systems account for 60% of the total energy consumption of buildings. As a sector, buildings contributes about 40% of the total global energy demand. By using passive technology coupled with natural ventilation from wind towers, significant amounts of energy can be saved, reducing the emissions of greenhouse gases. In this study, the development of Computational Fluid Dynamics (CFD) analysis in aiding the development of wind towers was explored. Initial concepts of simple wind tower mechanics to detailed design of wind towers which integrate modifications specifically to improve the efficiency of wind towers were detailed. From this, using CFD analysis, heat transfer devices were integrated into a wind tower to provide cooling for incoming air, thus negating the reliance on mechanical HVAC systems. A commercial CFD code Fluent was used in this study to simulate the airflow inside the wind tower model with the heat transfer devices. Scaled wind tunnel testing was used to validate the computational model. The airflow supply velocity was measured and compared with the numerical results and good correlation was observed. Additionally, the spacing between the heat transfer devices was varied to optimise the performance. The technology presented here is subject to a patent application (PCT/GB2014/052263).
Abstract: Phylogenetic (tree-based) approaches to understanding evolutionary history are unable to incorporate convergent evolutionary events where two genes merge into one. In this study, as exemplars of what can be achieved when a tree is not assumed a priori, we have analysed the evolutionary histories of polyketide synthase genes and antibiotic resistance genes and have shown that their history is replete with convergent events as well as divergent events. We demonstrate that the overall histories of these genes more closely resembles the remodelling that might be seen with the children’s toy Lego, than the standard model of the phylogenetic tree. This work demonstrates further that genes can act as public goods, available for re-use and incorporation into other genetic goods.
Abstract: Dynamical interactions among sets of genes (and their products) regulate developmental processes and some dynamical diseases, like cancer. Gene regulatory networks (GRNs) are directed networks that define interactions (links) among different genes/proteins involved in such processes. Genetic regulation can be modified during the time course of the process, which may imply changes in the nodes activity that leads the system from a specific state to a different one at a later time (dynamics). How the GRN modifies its topology, to properly drive a developmental process, and how this regulation was acquired across evolution are questions that the evolutionary dynamics of gene networks tackles. In the present work we review important methodology in the field and highlight the combination of these methods with evolutionary algorithms. In recent years, this combination has become a powerful tool to fit models with the increasingly available experimental data.