Attribute Exploration of Gene Regulatory Processes

TL;DR

This thesis introduces a logical analysis framework for gene regulatory networks using Formal Concept Analysis and attribute exploration, enabling validation of temporal rules and integration of background knowledge.

Contribution

It presents a novel approach combining Formal Concept Analysis with attribute exploration for analyzing gene regulatory processes, including applications to biological networks.

Findings

Validated implications for gene coexpression and causal relationships

Applied method to Bacillus subtilis sporulation model

Developed Boolean network for rheumatoid arthritis

Abstract

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.