Artificial intelligence approach in analysis of DNA sequences.

We present an approach for designing a knowledge-based system, called Sequence Acquisition In Context (SAIC), that will be able to cooperate with a biologist in the analysis of DNA sequences. The main task of the system is the acquisition of the expert knowledge that the biologist uses for solving ambiguities from gel autoradiograms, with the aim of re-using it later for solving similar ambiguities. The various types of expert knowledge constitute what we call the contextual knowledge of the sequence analysis. Contextual knowledge deals with the unavoidable problems that are common in the study of the living material (eg noise on data, difficulties of observations). Indeed, the analysis of DNA sequences from autoradiograms belongs to an emerging and promising area of investigation, namely reasoning with images. The SAIC project is developed in a theoretical framework that is shared with other applications. Not all tasks have the same importance in each application. We use this observation for designing an intelligent assistant system with three applications. In the SAIC project, we focus on knowledge acquisition, human-computer interaction and explanation. The project will benefit research in the two other applications. We also discuss our SAIC project in the context of large international projects that aim to re-use and share knowledge in a repository.