Thisisthe?rstissueofanewjournaloftheLNCSjournalsubline.Theaimofthe journal is to encourage inter- and multidisciplinary research in the ?elds of c- puter science and life sciences. The recent paradigmatic shift in biology towards a system view of biological phenomena requires a corresponding paradigmatic shift in the techniques from computer science that can face the new challenges. Classical tools usually used in bioinformatics are no longer up to date and new ideas are needed. The convergence of sciences and technologies we are experiencing these days is changing the classical terms of reference for research activities. In fact clear distinctions between disciplines no longer exist because advances in one ?eld permit advances in others and vice versa, thus establishing a positive feedback loop between sciences. The potential impact of the convergence of sciences and technologies is so huge that we must consider how to control and correctly drive our future activities. International and national funding agencies are looking at interdisciplinary research as a key issue for the coming years, especially in the intersection of life sciences and information technology. To speed up this process, we surely need to establish relationships between researchers of di?erent communities and to de?ne a common language that will allow them to exchange ideas and - sults. Furthermore, expectations of di?erent communities can be merged only by running activities like common projects and experiences. TheTransactionsonComputationalSystemsBiologycouldbeagoodforumto helplifescientistsandcomputerscientiststodiscusstogethertheircommongoals.

Inhalt

Accessible Protein Interaction Data for Network Modeling. Structure of the Information and Available Repositories.- Early Systems Biology and Prebiotic Networks.- Virtualization in Systems Biology: Metamodels and Modeling Languages for Semantic Data Integration.- Genome Size and Numbers of Biological Functions.- Operational Patterns in Beta-Binders.- Discrete Event Multi-level Models for Systems Biology.- A New Time-Dependent Complexity Reduction Method for Biochemical Systems.