EDITORIAL On the border between biology, mathematics and computer science

Piotr Formanowicz
2011 BioTechnologia  
Computational biology, bioinformatics and systems biology are three closely related interdisciplinary areas of research rapidly evolving at the intersection of biology, mathematics and computer science. The general goal of all of these areas is to support the analysis of biological phenomena by mathematical and algorithmic methods. However, the ideas flow not only from mathematics and computer science to biology but also in the opposite direction when the biological objects and processes become
more » ... nd processes become a motivation for developing new mathematical theories or algorithms. It may be said that, at least in some sense, bioinformatics and systems biology are parts of computational biology. While computational biology as a whole, concerns the development of mathematical models of biological phenomena and algorithmic methods and tools for the analysis of biological processes and structures, bioinformatics is focused mainly on using these tools for biological discoveries. On the other hand, systems biology is related to the systems analysis of biological complex objects which, in turn, includes the development of mathematical and algorithmic methods for such an analysis and using them for biological investigations. For a long time, biology, on one hand, and mathematics and computer science, on the other, have been seen as almost distinct areas of research. It was mostly due to the fact that in biological sciences, as opposed to, for example, physics, qualitative (but not quantitative) descriptions and analyses were the basis for scientific investigations. This situation started to change when it became possible to read and analyze the most important building blocks of living organisms, i.e. nucleic acids and proteins. The impressive discoveries in molecular biology during the second half of the 20th century and especially the development of new very effective DNA sequencing techniques and methods at the beginning of the new millennium have resulted in an enormous amount of new biological data available in publicly accessible databases. Not only it has accelerated research in almost every branch of biology but has also demonstrated that the analysis of these data is very difficult or even impossible without mathematical and algorithmic methods. The reason for this is twofold. Firstly, the analysis of large sets of data, in general, requires formal methods. Secondly, it seems that the structure and functionality of living organisms is based on some strict rules which, at least in principle, can be described using a language of an appropriate mathematical theory. Previously, this was not so obvious but now there are strong evidences that this is the case. First of all, the entire organization of genetic information in genomes is very complex; however, at the very basic level, it is also very regular. The genetic code is a simple but rigorous and effective method which the nature applies to store and process the genetic information. Although it is simple, its discovery was not a trivial task. Genetic information is written in DNA and RNA molecules as sequences of nucleotides and therefore it can be represented in a natural way as sequences of letters corresponding to these nucleotides. Objects of this type (i.e. sequences of letters) are well known in computer science which has made it a subject of an intensive research from its very beginning. This makes many molecular biology issues well suited for the analysis using computer science--based methods. But more important and fundamental is the fact that living organisms are based on information processing. Indeed, the genetic information must be stored, copied and corrected, and
doi:10.5114/bta.2011.46536 fatcat:aw3y2iduxzhlheds5jhocn3nju