Abstract

Long before the modern development of Computer Science, many biological processes naturally adopted fundamental concepts from this discipline. Throughout the past century of advancements in both areas, many similarities have been determined in their respective use of information, algorithms and data structures.

Consequently, modeling genetic processes through computation is proving to be very useful. Indeed, it is often possible to gain a greater biological understanding of each system itself. One can obtain relevant, quantitative results and also hard bounds on the processes. Additionally, one can use the methods and concepts already available to computer scientists in their study after similarities are established. Furthermore, by studying each system in this way, we can acquire theoretical evidence which can help to verify (or conversely, disqualify) biological hypotheses.

We will explore these relationships through the study of two specific genetic processes: the gene descrambling methods present in hypotrichous ciliates and the data compression used in some viral genomes. We will formalize each system and discuss the relevance of the obtained results to our biological comprehension and to our acceptance of various hypotheses.

Further work on different systems using this approach and establishing general connections between the two fields can lead towards a theory of biological processes in a more formal and quantitative fashion.

About the speaker

Ian McQuillan is a Ph.D. Candidate at the University of Western Ontario on bioinformatics and computational biology under the supervision of Dr. Helmut Jürgensen.

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