Introduction to the Special Theme

by Gunnar W. Klau and Jacques Nicolas

In the life sciences, conventional wet lab experimentation is being increasingly accompanied by mathematical and computational techniques in order to deal with the overwhelming complexity of living systems. Computational biology is an interdisciplinary field that aims to further our understanding of living systems at all scales. New technologies lead to massive amounts of data as well as to novel and challenging research questions and more and more biological processes are analyzed and modelled with the help of mathematics and can be simulated in silico.

Computational biology is one side of a two-sided domain and generally refers to the fundamental research field. The term bioinformatics is frequently used for the more engineering-oriented side of the domain and deals with the production of practical software enabling original analysis of biological data. This ERCIM News special theme starts with two invited articles that reflect this complementarity. Harvey Greenberg presents his view on the positive contribution of Operations Research (OR) to biology. OR is in itself a powerful, interdisciplinary domain that led, among many other important contributions to computational biology, to the recent concept of pathway signatures. Knut Reinert describes the importance of good software design practices in bioinformatics by means of library design for sequence analysis. In fact, the next European infrastructure in bioinformatics, which is currently discussed in the project ELIXIR (European Life Sciences Infrastructure for Biological Information), has put emphasis on the necessity of shared efforts for setting common standards and tools for data management.

As already mentioned in the keynote by Dirk Evers we currently observe a neat evolution of the research field that results from the maturation and large diffusion of high-throughput technologies in biological laboratories. New types of data have to be taken into account: researchers are becoming increasingly aware of the importance of the RNA world and epigenomics in explaining cellular behaviour that can not be solely understood by purely genetic aspects. Metabolomics is the first method developed that is capable of obtaining high throughput data at the phenotypic level. Examples of joint European research efforts in this direction include the European Research Council Advanced Grants “RIBOGENES” (The role of noncoding RNA in sense and antisense or orientation in epigenetic control of rRNA genes) and the FP7 project “METAcancer (Identification and validation of new breast cancer biomarkers based on integrated metabolomics)”.

These recent developments make more systemic approaches possible, where several methods and sources of data have to be combined. This has an impact on the importance of developing data integration environments, adding semantics to observations (ontologies, text mining) and offering sophisticated navigation utilities through the web. It has also fostered a number of studies in high-performance computing such as distributed or grid computing or the use of graphical processing units. These techniques are no longer restricted to demanding applications in structural modelling but have become necessary in many other domains of computational biology.

Many innovative methods in the field come from health applications. A number of cohort studies are currently being carried out, for example within the 1000 genomes project or the Apo-sys (Apoptosis Systems Biology Applied to Cancer and AIDS ) project. For the first time, they will give access to an in depth study of the correlations between a variety of health-related factors like human individual genomic variations, nutrition, environment and diseases. Deciphering the relationships between genotype and phenotype is a major challenge for the coming years that researchers are just starting to explore. Advances will be obtained by more connections between distant research fields, and techniques from image analysis and data mining can be expected to play increasing roles in computational biology in the future.

In addition, such global studies will more generally be beneficial for the fields of population genetics and ecology. Sets of cells in a tissue and sets of bacteria in a selected habitat can now be studied at the finest level of molecular interaction, creating pressure to develop research on multi-scale modelling and model reduction techniques. Here, examples of European projects are MetaHIT and Metaexplore for the metagenomics of the human intestinal tract and the study of the enzymatic potential in cryptic biota, respectively.

This special theme features a selection of articles that covers a number of areas of Computational Biology and provides a nice snapshot of the research variety carried out in this area in Europe. In addition to the two invited contributions, it contains 23 short articles on new approaches, frameworks and applications in the domain of computational biology. From the perspective of mathematics and computer science, the articles cover topics such as "mathematical modelling and simulation", "statistics and optimization", "high-performance computing", "data and metadata integration", "sequence and graph algorithms" and "artificial intelligence". From the perspective of biology, the covered topics include: "high-throughput technologies", “systems biology, dynamical networks", "diseases", "drugs and gene mining", and "structural biology". The table gives an overview of this two-dimensional scheme.

Links:
1000 genomes: http://www.1000genomes.org
ELIXIR: http://www.elixir-europe.org
METAcancer: http://www.metacancer-fp7.eu/
Apo-sys: http://www.apo-sys.eu/
MetaHIT: http://www.metahit.eu/
MetaExplore: http://www.rug.nl/metaexplore/

Please contact:
Gunnar Klau
CWI, The Netherlands
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Jacques Nicolas
INRIA, France
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