TaBooN -- Boolean Network Synthesis Based on Tabu Search

Recent developments in Omics-technologies revolutionized the investigation of biology by producing molecular data in multiple dimensions and scale. This breakthrough in biology raises the crucial issue of their interpretation based on modelling. In this undertaking, network provides a suitable framework for modelling the interactions between molecules. Basically a Biological network is composed of nodes referring to the components such as genes or proteins, and the edges/arcs formalizing interactions between them. The evolution of the interactions is then modelled by the definition of a dynamical system. Among the different categories of network, the Boolean network offers a reliable qualitative framework for the modelling. Automatically synthesizing a Boolean network from experimental data therefore remains a necessary but challenging issue. In this study, we present taboon, an original work-flow for synthesizing Boolean Networks from biological data. The methodology uses the data in the form of Boolean profiles for inferring all the potential local formula inference. They combine to form the model space from which the most truthful model with regards to biological knowledge and experiments must be found. In the taboon work-flow the selection of the fittest model is achieved by a Tabu-search algorithm. taboon is an automated method for Boolean Network inference from experimental data that can also assist to evaluate and optimize the dynamic behaviour of the biological networks providing a reliable platform for further modelling and predictions

Automated requirements analysis for a molecular watchdog timer

Dynamic systems in DNA nanotechnology are often programmed using a chemical reaction network (CRN) model as an intermediate level of abstraction. In this paper, we design and analyze a CRN model of a watchdog timer, a device commonly used to monitor the health of a safety critical system. Our process uses incremental design practices with goal-oriented requirements engineering, software verification tools, and custom software to help automate the software engineering process. The watchdog timer is comprised of three components: an absence detector, a threshold filter, and a signal amplifier. These components are separately designed and verified, and only then composed to create the molecular watchdog timer. During the requirements-design iterations, simulation, model checking, and analysis are used to verify the system. Using this methodology several incomplete requirements and design flaws were found, and the final verified model helped determine specific parameters for biological experiments

A Constraint Logic Programming Approach to Predicting the Three-Dimensional Yeast Genome

In order for all of a cell's genetic information to fit inside its nucleus, the chromosomes must undergo extensive folding and organization. Just like in origami where the same piece of paper folded in different ways allows the paper to take on different forms and potential functions, it is possible that different genomic organizations (or architectures) are related to various nuclear functions. Until recently, it has been impossible to comprehensively investigate this relationship due to the lack of high-resolution and high-throughput techniques for identifying genomic architectures. The recent development of a technique called Hi-C, which is a derivation of chromosome conformation capture, has made it possible to detect the complete set of interactions occurring within (intra-interactions) and between (inter-interactions) chromosomes in the nucleus. Many computational methods have been proposed that use these analytical results to infer the rough three-dimensional (3D) architecture of the genome. However, the genomic architecture also impacts additional types of nuclear interactions and techniques exist that are able to capture and measure these interactions. Unfortunately, it is difficult to incorporate these additional datasets into the existing tools. To overcome this, a novel application of constraint logic programming (CLP) was used to develop a new program for the prediction of the 3D genomic architecture. The unique representation used in this program lends itself well to the future incorporation of additional genomic datasets. This thesis investigates the most efficient way to date to represent and optimally solve the constraint satisfaction problem of the 3D genome. The developed program was used to predict a 3D logical model of the fission yeast genome and the results were visualized using Cytoscape. This model was then biologically validated through literature search which verified that the prediction was able to recapitulate key documented features of the yeast genome. Future work will utilize this tool as a computational framework and extend it to incorporate additional genomic datasets and information into the prediction and visualization of the 3D genomic architecture. The development of the CLP program described here is a step towards a better understanding of the elusive relationship between the 3D structure of the genome and various nuclear functions