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1 Towards Automated Explanation of Gene-Gene Relationships

During the recent decades research in molecular biology experienced several paradigm shifts that changed the researchers’ approach to solving particular problems in the field. The invention of microarray technology in the last decade of the previous millennium can certainly be seen as one of those paradigm shifts [3]. However, although there appear first reports showing efforts to combine various resources of genomic data instead of investigating just one source (e.g., [2, 4]), the understanding and interpretation of the results—the key issue in any attempt to a discovery—is still entirely left to the human. Microarray data represent a reasonable source of new hypotheses on gene function and between-gene relationships. In order to fully understand and explain these hypotheses, biological background information from many resources has to be explored and combined. We propose a novel method intended to aid a researcher in understanding hypothetical relationships between genes, e.g., genes not previously known to be related. In order to justify a tentative link between genes, the sequences, promoter regions, protein structure, function and other properties may have to be investigated for these and possibly other related genes. Although a manual search for information that would link two genes is theoretically possible, in practice it may be a very tedious task. Our approach is an attempt to design and implement a high-level wrapper for existing databases and tools, providing an automated process of forming relevant human-readable explanations. The proposed solution draws from the achievements of research in artificial intelligence—knowledge representation and knowledgeintensive reasoning, non-deductive inference mechanisms, and machine-learning [1].