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1. Computational expressiveness of Genetic Systems

Author

Zandron, C, Busi, N, ZANDRON, CLAUDIO, Busi, N., Zandron, C, Busi, N, ZANDRON, CLAUDIO, and Busi, N.

Abstract

We introduce Genetic Systems, a formalism inspired by genetic regulatory networks and suitable for modeling the interactions between the genes and the proteins, acting as regulatory products. The generation of new objects, representing proteins, is driven by genetic gates: a new object is produced when all the activator objects are available in the system, and no inhibitor object is available. Activators are not consumed by the application of such an evolution rule. Objects disappear because of degradation: each object is equipped with a lifetime, and the object decays when such a lifetime expires. We investigate the computational expressiveness of Genetic Systems: we show that they are Turing equivalent by providing encodings of Random Access Machines in Genetic Systems. © 2008 Elsevier B.V. All rights reserved.

Published
2009

3. Analysis of 80 Dual-Kidney Transplantations: A Multicenter Experience

Author

Nardo, B., primary, Bertelli, R., additional, Cavallari, G., additional, Capocasale, E., additional, Cappelli, G., additional, Mazzoni, M.P., additional, Benozzi, L., additional, Valle, R. Dalla, additional, Fuga, G., additional, Busi, N., additional, Gilioli, C., additional, Albertazzi, A., additional, Stefoni, S., additional, Pinna, A.D., additional, and Faenza, A., additional

Published
2011
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4. Multicenter Study on Double Kidney Transplantation

Author

Bertelli, R., primary, Nardo, B., additional, Capocasale, E., additional, Cappelli, G., additional, Cavallari, G., additional, Mazzoni, M.P., additional, Benozzi, L., additional, Dalla Valle, R., additional, Fuga, G., additional, Busi, N., additional, Gilioli, C., additional, Albertazzi, A., additional, Stefoni, S., additional, Pinna, A.D., additional, and Faenza, A., additional

Published
2008
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5. Laparoscopic Donor Nephrectomy: Short Learning Curve

Author

Dalla Valle, R., primary, Mazzoni, M.P., additional, Capocasale, E., additional, Busi, N., additional, Pietrabissa, A., additional, Moretto, C., additional, Gualtierotti, M., additional, Massa, M., additional, Mosca, F., additional, and Sianesi, M., additional

Published
2006
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13. Renal vein extension in right kidney transplantation

Author

Dalla Valle, R, primary, Mazzoni, M.P, additional, Bignardi, L, additional, Busi, N, additional, Benozzi, L, additional, Gualtierotti, M, additional, Alessandri, L, additional, Bezer, L, additional, Iapichino, G, additional, Capocasale, E, additional, and Sianesi, M, additional

Published
2004
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16. Computational expressiveness of Genetic Systems

Author

Claudio Zandron, Nadia Busi, Zandron, C, and Busi, N

Subjects
Molecular computation, Theoretical computer science, genetic structures, General Computer Science, Computer science, Concurrency, Concurrency and distributed computation, Genetic systems, Theoretical Computer Science, computational, expressiveness, genetic, systems, Formalism (philosophy of mathematics), ComputingMethodologies_GENERAL, Gene, Turing, computer, Genetic regulatory networks, Computer Science(all), computer.programming_language
Abstract

We introduce Genetic Systems, a formalism inspired by genetic regulatory networks and suitable for modeling the interactions between the genes and the proteins, acting as regulatory products. The generation of new objects, representing proteins, is driven by genetic gates: a new object is produced when all the activator objects are available in the system, and no inhibitor object is available. Activators are not consumed by the application of such an evolution rule. Objects disappear because of degradation: each object is equipped with a lifetime, and the object decays when such a lifetime expires. We investigate the computational expressiveness of Genetic Systems: we show that they are Turing equivalent by providing encodings of Random Access Machines in Genetic Systems. © 2008 Elsevier B.V. All rights reserved.

Published
2009
Full Text
View/download PDF

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