Synthetic Modeling and the Functional Role of Noise

In synthetic biology the use of engineering metaphors to describe biological organisms and their behavior has become a common practice. The concept of noise provides one of the most compelling examples of such transfer. But this notion is also confusing: While in engineering noise is a destructive force perturbing artificial systems, in synthetic biology it has acquired an additional functional meaning. It has been found out that noise is an important factor in driving biological processes such as gene regulation, development, and evolution. How did noise acquire this dual meaning in the field of synthetic biology? In this paper we study the emergence of the functional meaning of noise in relation to synthetic modeling. We will pay particular attention to the interdisciplinary aspects of this process highlighting the way borrowed concepts, analogical reasoning and the use of cross-disciplinary computational templates were entwined in it

Attribute Exploration of Gene Regulatory Processes

This thesis aims at the logical analysis of discrete processes, in particular of such generated by gene regulatory networks. States, transitions and operators from temporal logics are expressed in the language of Formal Concept Analysis. By the attribute exploration algorithm, an expert or a computer program is enabled to validate a minimal and complete set of implications, e.g. by comparison of predictions derived from literature with observed data. Here, these rules represent temporal dependencies within gene regulatory networks including coexpression of genes, reachability of states, invariants or possible causal relationships. This new approach is embedded into the theory of universal coalgebras, particularly automata, Kripke structures and Labelled Transition Systems. A comparison with the temporal expressivity of Description Logics is made. The main theoretical results concern the integration of background knowledge into the successive exploration of the defined data structures (formal contexts). Applying the method a Boolean network from literature modelling sporulation of Bacillus subtilis is examined. Finally, we developed an asynchronous Boolean network for extracellular matrix formation and destruction in the context of rheumatoid arthritis.Comment: 111 pages, 9 figures, file size 2.1 MB, PhD thesis University of Jena, Germany, Faculty of Mathematics and Computer Science, 2011. Online available at http://www.db-thueringen.de/servlets/DocumentServlet?id=1960

Formal genetic maps

Formal genetic maps are databases, represented as text or graphic figures, that can be collected/organized/formulated and constructed for nearly any, and every, structural or functional region of the genetic material. Though these maps are basically descriptive, their analysis can provide relevant crucial data that can be applied for different purposes in many fields. The more comprehensive these maps are the more significant information that can be provided through their analysis. Formal genetic maps comprise four main categories: physical maps detailing the structural characteristics of different regions/sequences of both the nuclear and the mitochondrial genomes, functional maps describing the varied functional potentials of the different components of the genome/ transcriptome/proteome, experimental induced maps that are intentionally designed and constructed for specific purposes and constructed maps that are deduced and extracted from other formal maps to serve particular targets that cannot be achieved solely by the constituent maps. Formal genetic maps have a wide spectrum of applications in all fields of human genetics including basic genetics as well as medical genetics. The beneficial impact of the different types of formal genetic maps imposed their application in nearly all fields of medical genetics including basic/clinical/ diagnostic/therapeutic/prophylactic and applied genetics and made these maps indispensable tools in research studies relevant to these fields