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Biomedical subjects

G L Hofacker

Publications and source records attributed to G L Hofacker.

8 recordsLinked to original sources
PubMed1996

Informational properties of neural nets performing algorithmic and logical tasks.

It is argued that the genetic information necessary to encode an algorithmic neural processor tutoring an otherwise randomly connected biological neural net is represented by the entropy of the analogous minimal Turing machine. Such a near-minimal machine is constructed performing the whole range of bivalent propositional logic in n variables. Neural nets computing the same task are presented; their informational entropy can be gauged with reference to the analogous Turing machine. It is also shown that nets with one hidden layer can be trained to perform algorithms solving propositional logic by error back-propagation.

Algorithms↗
PubMed1995

Complementary coding conforms to the primeval comma-less code.

The hypothesis that the universal genetic code is adapted to double-strand coding is supported by its remarkable compatibility with the RNY comma-less hypothesis. Coding by a triplet code on a polynucleotide double-strand allows for enciphering of five additional messages with reference to a chosen primary reading frame. Assuming the acceptance of coupled mutations on both strands, the best codon register for two overlapping messages can be inferred. The idea of evolutionarily compatible coding of two proteins by one nucleotide double-strand is extended to complementary coding for one protein in folded, single-stranded RNA.

Animals↗
PubMed1993

Neutral adaptation of the genetic code to double-strand coding.

We lay new foundations to the hypothesis that the genetic code is adapted to evolutionary retention of information in the antisense strands of natural DNA/RNA sequences. In particular, we show that the genetic code exhibits, beyond the neutral replacement patterns of amino acid substitutions, optimal properties by favoring simultaneous evolution of proteins encoded in DNA/RNA sense-antisense strands. This is borne out in the sense-antisense transformations of the codons of every amino acid which target amino acids physicochemically similar to each other. Moreover, silent mutations in the sense strand generate conservative ones in its antisense counterpart and vice versa. Coevolution of proteins coded by complementary strands is shown to be a definite possibility, a result which does not depend on any physical interaction between the coevolving proteins. Likewise, the degree to which the present genetic code is dedicated to evolutionary sense-antisense tolerance is demonstrated by comparison with many randomized codes. Double-strand coding is quantified from an information-theoretical point of view.

Adaptation, Biological↗
PubMed1990

Stochastic traits of molecular evolution--acceptance of point mutations in native actin genes.

A stochastic matrix of nucleotide mutation probabilities is derived by counting differences and identities in alignments of native actin genes, with the aim of obtaining a more reliable data base for regular modes of molecular evolution. The evolution of DNA sequences is thereby considered as a Markov process consisting of events (point mutations) characterized by a stochastic matrix for codon-codon interchanges. The genetic distance is set to 1 PAM (percentage of accepted point mutations). The results can be reproduced by Monte Carlo simulations which are subjected to selective constraints. The latter are observed as nonrandom codon usage and ratios of silent to recognizable point mutations. Specific patterns within the matrix of mutation probabilities attest to preferences of natural selection in the evolution of a specific protein.

Actins↗
PubMed1990

An ESS-analysis for ensembles of prisoner's dilemma strategies.

The ESS (Evolutionary Stable Strategy) concept of Maynard Smith can be applied in its weak form to ensembles of competing PD ("Prisoner's Dilemma") strategies memorizing two to three of one's own and one's opponent's moves. The format of our study is: (1) games have very long duration; (2) Taylor-Jonker dynamics applies; (3) Effects of finite population size can be ignored. It is shown that in the case R greater than (T + S)/2 a set of strategies can be singled out which do not lose against any other strategy while co-operating with themselves. Such a set is uninvadable by other PD strategies if it constitutes more than half of the total population.

Biological Evolution↗
PubMed1987

Point mutations as an optimal search process in biological evolution.

Point mutations are pictured as jumps in a phase space representing the sequences of amino acids or nucleotides as discrete points. It is shown that this space can be given a natural metric by quantifying common physical and chemical properties of amino acid constituents in terms of a natural measure. Evolution through point mutations is simulated by the search for points in the phase space representing amino acid sequences of high survival fitness. Due to the local compactness of the distribution of these functionally allowed points in phase space any successful search procedure has characteristics qualitatively different from those in the case of a random distribution. This is demonstrated by model calculations. A specified distribution of allowed points is generated with subsequent evaluation of the success of the retrieval process as a function of the jump probabilities between lattice sites. The results of such simulations are compared with data obtained from the analysis of the DNA or mRNA sequences coding related proteins. By counting silent and expressed nucleotide replacement frequencies one can draw conclusions as to the efficacy of the natural evolutionary search processes in the phase space of amino acid sequences. There are cases, where the highest possible information gain of one bit per accepted point mutation is achieved. In general the information gain is found to be somewhat sub-maximal due to functional requirements.

Amino Acid Sequence↗
PubMed1979

Evolutionary changes in protein composition -- evidence for an optimal strategy.

The information contained in the composition of different proteins of the same family is analyzed. It is found that within each family the gain in information per amino acid replacement is constant. This finding is interpreted to imply that evolutionary changes in proteins follow an "optimal" path in the sense that they maximize the number of potentially functional sequences that can be generated by T accepted point mutations from a given protein, subject to restrictions due to biological function.

Amino Acid Sequence↗