LNCS 2950 - Aspects of Molecular Computing (Frontmatter Pages)

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22 Artiom Alhazov, Carlos Martín-Vide, and Linqiang Pan Let us denote by AM the class of recognizing P systems with active membranes and with 2-division. Then from Theorem 1 and Theorem 2 we have VCP ∈ LMCAM ⊆ PMCAM and CP ∈ LMCAM ⊆ PMCAM. Because the class PMCAM is stable under polynomial time reduction, we have NP ⊆ PMCAM. Similarly, from Theorem 3 we have VCP ∈ PMC S AM and NP ⊆ PMC S AM , which can also be obtained from VCP ∈ PMCAM, NP ⊆ PMCAM and the fact PMCAM ⊆ PMC S AM . The following problems are open: (1) Does NP = PMCAM or NP = PMC S AM hold? (2) Find a class F of P systems such that NP = PMCF or NP = PMC S F . Acknowledgments. The work of the first author was supported by grant 2001CAJAL-BURV from Rovira i Virgili University; the work of the last author was supported by grant DGU-SB2001-0092 from Spanish Ministry for Education, Culture, and Sport, National Natural Science Foundation of China (Grant No. 60373089), and Huazhong University of Science and Technology Foundation. References 1. M.R. Garey, D.J. Johnson, Computers and Intractability. A Guide to the Theory of NP-Completeness. W.H. Freeman, San Francisco, 1979. 2. Gh. Păun, Computing with Membranes, Journal of Computer and System Sciences, 61, 1 (2000), 108–143, and TUCS Research Report 208, 1998 (http://www.tucs.fi). 3. Gh. Păun, P Systems with Active Membranes: Attacking NP-Complete Problems, Journal of Automata, Languages and Combinatorics, 6, 1 (2001), 75–90. 4. Gh. Păun, Membrane Computing: An Introduction, Springer, Berlin, Heidelberg, 2002. 5. M.J. Pérez-Jiménez, A. Romero-Jiménez, F. Sancho-Caparrini, Complexity Classes in Cellular Computing with Membranes, Proceedings of Brainstorming Week on Membrane Computing (M.Cavaliere,C.Martín-Vide and Gh. Păun eds.), Tarragona, Spain, February, (2003) 270–278. 6. M.J. Pérez-Jiménez, A. Romero-Jiménez, F. Sancho-Caparrini, A Polynomial Complexity Class in P Systems Using Membrane Division, Proceedings of the 5th Workshop on Descriptional Complexity of Formal Systems, Budapest, Hungary, July 12–14, 2003.
Writing Information into DNA Masanori Arita Department of Computational Biology Graduate School of Frontier Sciences University of Tokyo Kashiwanoha 5-1-5, 277-8561 Kashiwa, Japan arita@k.u-tokyo.ac.jp Abstract. The time is approaching when information can be written into DNA. This tutorial work surveys the methods for designing code words using DNA, and proposes a simple code that avoids unwanted hybridization in the presence of shift and concatenation of DNA words and their complements. 1 Introduction As bio- and nano-technology advances, the demand for writing information into DNA increases. Areas of immediate application are: – DNA computation which attempts to realize biological mathematics, i.e., solving mathematical problems by applying experimental methods in molecular biology [1]. Because a problem must be first encoded in DNA terms, the method of encoding is of crucial importance. Typically, a set of fixed-length oligonucleotides is used to denote logical variables or graph components. – DNA tag/antitag system which designs fixed-length short oligonucleotide tags for identifying biomolecules (e.g., cDNA), used primarily for monitoring gene expressions [2,3,4]. – DNA data storage which advocates the use of bacterial DNA as a long-lasting high-density data storage, which can also be resistant to radiation [5]. – DNA signature which is important for registering a copyright of engineered bacterial and viral genomes. Steganography (an invisible signature hidden in other information) is useful for the exchange of engineered genomes among developers. These fields are unlike conventional biotechnologies in that they attempt to encode artificial information into DNA. They can be referred to as ‘encoding models’. Although various design strategies for DNA sequences have been proposed and some have been demonstrated, no standard code like the ASCII code exists for these models, presumably because data transfer in the form of DNA has not been a topic of research. In addition, requirements for DNA sequences differ for each encoding model. In this tutorial work, the design of DNA words as information carriers is surveyed and a simple, general code for writing information into biopolymers is N. Jonoska et al. (Eds.): Molecular Computing (Head Festschrift), LNCS 2950, pp. 23–35, 2004. c○ Springer-Verlag Berlin Heidelberg 2004
Page 1 and 2: Lecture Notes in Computer Science 2
Page 3 and 4: Nata˘sa Jonoska Gheorghe Păun Grz
Page 5 and 6: Thomas J. Head
Page 7 and 8: VIII Preface portant to keep in min
Page 9 and 10: X Table of Contents Formal Properti
Page 11 and 12: Solving Graph Problems by P Systems
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Molecular Tiling and DNA Self-assem
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8 Hierarchical Tiling Molecular Til
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References Molecular Tiling and DNA
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On Some Classes of Splicing Languag
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ˆxa ˆby ✬ ✩✬ ✩ a b x y
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The Power of Networks of Watson-Cri
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Fixed Point Approach to Commutation
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Here the last one holds if and only
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� � � � � Fixed Point App
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Remarks on Relativisations and DNA
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Splicing Test Tube Systems and Thei
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Splicing Test Tube Systems 141 the
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Splicing Test Tube Systems 143 to a
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Splicing Test Tube Systems 145 6. R
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Splicing Test Tube Systems 147 (c)
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I0 Ai i Splicing Test Tube Systems
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Splicing Test Tube Systems 151 4. J
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Digital Information Encoding on DNA
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DNA-based Cryptography Ashish Gehan
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DNA-based Cryptography 169 concern.
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DNA-based Cryptography 171 The one-
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DNA-based Cryptography 173 of DNA t
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DNA-based Cryptography 175 Fig. 3.
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DNA-based Cryptography 177 the comp
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DNA-based Cryptography 179 can be c
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DNA-based Cryptography 181 4.4 DNA-
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DNA-based Cryptography 183 Fig. 7.
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DNA-based Cryptography 185 offer li
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DNA-based Cryptography 187 30. C. M
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Splicing to the Limit Elizabeth Goo
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Splicing to the Limit 191 molecular
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Splicing to the Limit 193 Discussio
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Example 9. The splicing rules are S
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−2α � kNNk = −2αMN, k α
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Finally we define the limit languag
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6 Conclusion Splicing to the Limit
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Formal Properties of Gene Assembly
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(a) (b) Formal Properties of Gene A
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n-Insertion on Languages Masami Ito
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n-Insertion on Languages 215 3. ∀
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n-Insertion on Languages 217 Theore
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Transducers with Programmable Input
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1 01 s 0 Transducers with Programma
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order β l Transducers with Program
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start tile Transducers with Program
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Methods for Constructing Coded DNA
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u u Methods for Constructing Coded
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On the Universality of P Systems wi
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An Algorithm for Testing Structure
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Definition 1. Define the relation
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280 Manfred Kudlek Definition 5. Co
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On Languages of Cyclic Words 283 Th
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On Languages of Cyclic Words 285 No
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On Languages of Cyclic Words 287 Th
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A DNA Algorithm for the Hamiltonian
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Formal Languages Arising from Gene
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A Proof of Regularity for Finite Sp
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The Duality of Patterning in Molecu
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The Duality of Patterning in Molecu
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Membrane Computing: Some Non-standa
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The P Versus NP Problem Through Cel
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Realizing Switching Functions Using
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Realizing Switching Functions Using
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AND Gate Realizing Switching Functi
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NOR Gate Realizing Switching Functi
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Plasmids to Solve #3SAT Rani Siromo
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Plasmids to Solve #3SAT 363 A comme
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Plasmids to Solve #3SAT 365 from th
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Communicating Distributed H Systems
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Proof Communicating Distributed H S
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Books: Publications by Thomas J. He
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LNCS 2950 - Aspects of Molecular Computing (Frontmatter Pages)

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