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PubMed1968

[The genetic code].

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Amino Acid Sequence↗
PubMed2001

Efforts toward creating unnatural base pairs for an expanded genetic code.

A series of unnatural base pairs was designed and examined for the expansion of the genetic alphabet and for a better understanding of the mechanism of nucleic acid biosyntheses. To improve the shape complementarity of the previously developed unnatural base pairs, 2-amino-6-(N,N-dimethylamino)purine (x)--pyridon-2-one (y) and 2-amino-6-(2-thienyl)purine (s)--y, the pyrimidine analogue, y, was replaced by a five-member ring, 4-imidazolin-2-one (z), and the s-z pairing in replication was examined. Unnatural bases based on the five-member ring were also applied to the development of non-hydrogen-bonded base pairs.

Base Pairing↗
PubMed1997

About a symmetry of the genetic code.

Considering the three codonic positions as independent, it is possible to explain the grouping of the 64 trinucleotides (without AAA, TTT, CCC and GGG) into three equal sets T0, T1 and T2 according to their preferable reading frame (0, 1 or 2) in coding sequences. Supposing that the two complementarity strands of DNA are coding, it is demonstrated that the complementary of a codon is classified in to the same set, which has been observed statistically (with a few exceptions) in the coding sequences by Arquès & Michel [(1996) J. theor. Biol. 182, 45-58] and Arquès et al. [(1997) J. theor. Biol. 185, 241-253]. Finally, the circular property of the code pointed out by these authors is demonstrated, and a direct consequence to biological considerations of these properties is discussed.

Animals↗
PubMedDate not supplied

Material representations: from the genetic code to the evolution of cellular automata.

We present a new definition of the concept of representation for cognitive science that is based on a study of the origin of structures that are used to store memory in evolving systems. This study consists of novel computer experiments in the evolution of cellular automata to perform nontrivial tasks as well as evidence from biology concerning genetic memory. Our key observation is that representations require inert structures to encode information used to construct appropriate dynamic configurations for the evolving system. We propose criteria to decide if a given structure is a representation by unpacking the idea of inert structures that can be used as memory for arbitrary dynamic configurations. Using a genetic algorithm, we evolved cellular automata rules that can perform nontrivial tasks related to the density task (or majority classification problem) commonly used in the literature. We present the particle catalogs of the new rules following the computational mechanics framework. We discuss if the evolved cellular automata particles may be seen as representations according to our criteria. We show that while they capture some of the essential characteristics of representations, they lack an essential one. Our goal is to show that artificial life can be used to shed new light on the computation-versus-dynamics debate in cognitive science, and indeed function as a constructive bridge between the two camps. Our definitions of representation and cellular automata experiments are proposed as a complementary approach, with both dynamics and informational modes of explanation.

Artificial Intelligence↗
PubMed2003

Scientists expand the genetic code.

A bacterium has been created that synthesizes an unnatural amino acid and incorporates it into proteins with a fidelity and efficiency that rivals that of the 20 natural amino acids.

Escherichia coli↗