Transactions on Computational Systems Biology X

1. Front Matter

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2. Biological and Biologically-Inspired Communication

   1. Towards a Self-structured Grid: An Ant-Inspired P2P Algorithm

      • Agostino Forestiero, Carlo Mastroianni, Giuseppe Papuzzo, Giandomenico Spezzano

      Pages 1-19

   2. Robustness to Code and Data Deletion in Autocatalytic Quines

      • Thomas Meyer, Daniel Schreckling, Christian Tschudin, Lidia Yamamoto

      Pages 20-40

   3. A Computational Scheme Based on Random Boolean Networks

      • Elena Dubrova, Maxim Teslenko, Hannu Tenhunen

      Pages 41-58

   4. On Channel Capacity and Error Compensation in Molecular Communication

      • Baris Atakan, Ozgur B. Akan

      Pages 59-80

   5. Molecular Communication through Gap Junction Channels

      • Tadashi Nakano, Tatsuya Suda, Takako Koujin, Tokuko Haraguchi, Yasushi Hiraoka

      Pages 81-99

   6. Clustering Time-Series Gene Expression Data with Unequal Time Intervals

      • Luis Rueda, Ataul Bari, Alioune Ngom

      Pages 100-123

   7. Integrating Thermodynamic and Observed-Frequency Data for Non-coding RNA Gene Search

      • Scott F. Smith, Kay C. Wiese

      Pages 124-142

   8. An Evolutionary Approach to the Non-unique Oligonucleotide Probe Selection Problem

      • Lili Wang, Alioune Ngom, Robin Gras, Luis Rueda

      Pages 143-162

   9. Stochastic π-Calculus Modelling of Multisite Phosphorylation Based Signaling: The PHO Pathway in Saccharomyces Cerevisiae

      • Nicola Segata, Enrico Blanzieri

      Pages 163-196

3. Back Matter

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Technology is taking us to a world where myriads of heavily networked devices interact with the physical world in multiple ways, and at many levels, from the globalInternetdowntomicroandnanodevices. Manyofthesedevicesarehighly mobile and autonomous and must adapt to the surrounding environment in a totally unsupervised way. A fundamental research challenge is the design of robust decentralized c- puting systemsthat arecapableofoperating in changing environmentsandwith noisy input, and yet exhibit the desired behavior and response time, under c- straints such as energy consumption, size, and processing power. These systems should be able to adapt and learn how to react to unforeseen scenarios as well as to display properties comparable to social entities. The observation of nature has brought us many great and unforeseen concepts. Biological systems are able to handle many of these challenges with an elegance and e?ciency far beyond currenthumanartifacts. Basedonthisobservation,bio-inspiredapproacheshave been proposed as a means of handling the complexity of such systems. The goal is to obtain methods to engineer technical systems, which are of a stability and e?ciency comparable to those found in biological entities. This Special Issue on Biological and Biologically-inspired Communication contains the best papers from the Second International Conference on Bio- Inspired Models of Network, Information, and Computing Systems (BIONET- ICS 2007). The BIONETICS conference aims to bring together researchers and scientistsfromseveraldisciplines incomputerscienceandengineeringwhereb- inspired methods are investigated, as well as from bioinformatics, to deepen the information exchange and collaboration among the di?erent communities.

• ant algorithms
• biology
• boolean function
• channel capacity
• complexity
• computational biology
• covariance models
• database search
• evolution
• fault-tolerance
• gene expression
• genetic algorithms
• genetic regulatory ne
• life sciences
• model
• algorithm analysis and problem complexity

• The Microsoft Research, University of Trento, Centre for Computational and Systems Biology, Povo (TN), Italy

  Corrado Priami

• Department of Computer Science, University of Erlangen, Erlangen, Germany

  Falko Dressler

• Department of Electrical and Electronics Engineering, Middle East Technical University, Ankara, Turkey

  Ozgur B. Akan

• School of Computer Science, University of Windsor, Windsor, Canada

  Alioune Ngom

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