遗传算法——进化论思想与遗传学原理在工程优化中的应用

优胜劣汰是自然界物种进化的法则,近年来,生物科学中的进化论思想与遗传学原理被成功地应用于工程中优化问题的计算,于是产生了一种不同于传统算法的优化算法———遗传算法（ＧＡ）。本文介绍遗传算法所采用的进化论思想和遗传学原理,遗传算法的基本操作、算法步骤、不同于传统算法的特点以及遗传算法的发展历史与应用情况等,并对遗传算法对生物科学的可能应用作了简单的展望。     

Negative density‐dependent dispersal in tsetse (Glossina spp): red flag or red herring?

A deterministic model of the distribution of tsetse flies (Glossina spp) was used to assess the extent to which the efficacy of control operations would be affected by three different modes of density dependence in per capita adult dispersal: (i) density‐independent dispersal which has been commonly adopted in previous models, (ii) positive density‐dependent dispersal which has occasionally been discussed in the tsetse literature, (iii) negative density‐dependent dispersal (NDDD). The last has recently been suggested, from genetic studies, to change the dispersal rate of tsetse by up to 200‐fold, thereby posing a severe risk for the success of tsetse control operations. Modelling outputs showed that NDDD poses no such risk, provided the mean daily dispersal of tsetse is below about 1 km, which is greater than any rate actually recorded in the field or indicated by the genetic studies. NDDD can be problematic only if tsetse disperse at rates that appear highly unlikely, or even impossible, on energetic grounds. Under some circumstances these high rates would help rather than hinder the control officer. NDDD is not necessary to explain the results of control operations, and not sufficient to explain the results of successful control programmes.     

A Genetic Algorithm Approach to the Scheduling of FMSs with Multiple Routes

Usually, most of the typical job shop scheduling approaches deal with the processing sequence of parts in a fixed routing condition. In this paper, we suggest a genetic algorithm (GA) to solve the job-sequencing problem for a production shop that is characterized by flexible routing and flexible machines. This means that all parts, of all part types, can be processed through alternative routings. Also, there can be several machines for each machine type. To solve these general scheduling problems, a genetic algorithm approach is proposed and the concepts of virtual and real operations are introduced. Chromosome coding and genetic operators of GAs are defined during the problem solving. A minimum weighted tardiness objective function is used to define code fitness, which is used for selecting species and producing a new generation of codes. Finally, several experimental results are given.     

An improved genetic algorithm based fuzzy-tuned neural network

This paper presents a fuzzy-tuned neural network, which is trained by an improved genetic algorithm (GA). The fuzzy-tuned neural network consists of a neural-fuzzy network and a modified neural network. In the modified neural network, a neuron model with two activation functions is used so that the degree of freedom of the network function can be increased. The neural-fuzzy network governs some of the parameters of the neuron model. It will be shown that the performance of the proposed fuzzy-tuned neural network is better than that of the traditional neural network with a similar number of parameters. An improved GA is proposed to train the parameters of the proposed network. Sets of improved genetic operations are presented. The performance of the improved GA will be shown to be better than that of the traditional GA. Some application examples are given to illustrate the merits of the proposed neural network and the improved GA.     

Development of Microsatellite Markers for Japanese Scallop (Mizuhopecten yessoensis) and Their Application to a Population Genetic Study

Abstract The Japanese scallop (Mizuhopecten yessoensis) is one of the main fishery products in Japan, but with the expansion of culture operations of the Japanese scallop, various problems have been encountered including high mortality, poor growth, poor seed production, and so on. Moreover, there is concern that many years of cultivation may have affected the genetic structure of the scallop population. To approach these problems and concerns, we developed microsatellite markers as a molecular tool for population genetic studies. By using 4 microsatellite markers as well as a mitochondrial marker, we investigated the genetic structure of samples from the islands of Hokkaido (14 populations) and Honshu (Tohoku, 3 populations) in Japan, and south Primorye (4 populations) in Russia. All the populations sampled had high genetic diversity (average expected heterozygosity, 0.7011 to 0.7622; haplotype diversity, 0.6090 to 0.8848), and almost all showed a tendency of homozygote excess, which was significant in 2 populations. Hierarchical analysis of molecular variance tests based on the microsatellite and mitochondrial markers indicated that the 3 geographic regions were genetically divergent from one another, with little evidence of divergence within regions. Homogeneity in allele frequency distributions between natural and cultured scallops and allele frequency stability over a period of 2 decades indicated that the culturing operations have probably not had a substantial effect on the genetic structure of the populations.     

A specification language for planning and fault recovery in manufacturing systems

This paper presents the syntax and semantics of a component-oriented rule-based language for specifying the formal models of manufacturing systems. A model captures the state of a component of the system in a set of first-order logic predicates, and it captures the semantics of the operations performed by this component in a set of rules that determine the preconditions and postconditions of an operation. The models are then used to plan the sequence of operations of each class of jobs to be manufactured by these systems. A plan-oriented fault detection and correction strategy is proposed. This strategy can automatically handle any combination of faults that may occur when monitoring the operations of manufacturing systems. A fault-tree is consulted prior to executing the scheduled operations of a plan, and the faults that affect the execution of these operations are handled subsequently. Resuming the original cyclic schedule is attempted, whenever feasible. As a proof of concept, a prototype implementation of both the main constructs of the component-oriented rule-based language and the planning and fault-recovery algorithms presented in this paper have been completed. This prototype is implemented on a Unix-based system in the Ada programming language. The specification of a manufacturing system is first expressed in the proposed language. These statements are then translated into Ada code. This code is next compiled by a Verdix Ada compiler and is executed in order to create and populate the model data structure of the system. A detailed plan of execution and a set of fault-recovery plans may then be derived for a job to be manufactured on this system.     

Improving the efficiency of evolutionary de novo peptide design: strategies for probing configuration and parameter settings

Evolutionary molecular design based on genetic algorithms (GAs) has been demonstrated to be a flexible and efficient optimization approach with potential for locating global optima. Its efficacy and efficiency are largely dependent on the operations and control parameters of the GAs. Accordingly, we have explored new operations and probed good parameter setting through simulations. The findings have been evaluated in a helical peptide design according to "Parameter setting by analogy" strategy; highly helical peptides have been successfully obtained with a population of only 16 peptides and 5 iterative cycles. The results indicate that new operations such as multi-step crossover-mutation are able to improve the explorative efficiency and to reduce the sensitivity to crossover and mutation rates (CR-MR). The efficiency of the peptide design has been furthermore improved by setting the GAs at the good CR-MR setting determined through simulation. These results suggest that probing the operations and parameter settings through simulation in combination with "Parameter setting by analogy" strategy provides an effective framework for improving the efficiency of the approach. Consequently, we conclude that this framework will be useful for contributing to practical peptide design, and gaining a better understanding of evolutionary molecular design.     

Theory of epigenetic coding

The logic of genetic control of development may be based on a binary epigenetic code. This paper revises the author's previous scheme dealing with the numerology of annelid metamerism in these terms. Certain features of the code had been deduced to be combinatorial, others not. This paradoxical contrast is resolved here by the interpretation that these features relate to different operations of the code; the combinatiorial to coding identity of units, the non-combinatorial to coding production of units. Consideration of a second paradox in the theory of epigenetic coding leads to a new solution which further provides a basis for epimorphic regeneration, and may in particular throw light on the "regeneration-duplication" phenomenon. A possible test of the model is also put forward.     

Critical limitations in biological production of chemicals: process or genetic solutions?

Abstract: Production of bulk chemicals by biological processes is presently limited by failure of contemporary biological and bioreactor technology to deliver high product concentrations in high space-time yields in fluids of sufficiently low water content for subsequent down-stream processing operations. Limitations in the bioreactor portion of the process can arise due to failure to process sufficient substrate, substrate inhibition, inadequate rates or yields, and product inhibition. Various process approaches for addressing many of these limitations have been demonstrated or conceptualized. Less developed but potentially effective are genetic strategies addressing these process limitations. Ideally, the most effective combination of genetic and process approaches should be integrated in a synergistic fashion to maximize the economic potential of biological production of chemicals.     

A system of simple theoretically possible modes of transmission of genetic information

A system of simple theoretically feasible methods of transfer of genetic information has been proposed. The system has been analyzed and the methods have been classified. The system allows to predict properties of organisms that use different ways of transfer of genetic information and estimate the pathways of evolution of these organisms. A scheme for verification of conclusions made on the basis of the system with viruses taken as an example.     

A simulation study of the genetic regulatory hierarchy for butterfly eyespot focus determination

The color patterns on the wings of butterflies have been an important model system in evolutionary developmental biology. Two types of models have been used to study these patterns. The first type of model employs computational techniques and generalized mechanisms of pattern formation to make predictions about how color patterns will vary as parameters of the model are changed. These generalized mechanisms include diffusion gradient, reaction-diffusion, lateral inhibition, and threshold responses. The second type of model uses known genetic interactions from Drosophila melanogaster and patterns of candidate gene expression in one of several butterfly species (most often Junonia (Precis) coenia or Bicyclus anynana) to propose specific genetic regulatory hierarchies that appear to be involved in color pattern formation. This study combines these two approaches using computational techniques to test proposed genetic regulatory hierarchies for the determination of butterfly eyespot foci (also known as border ocelli foci). Two computer programs, STELLA 8.1 and Delphi 2.0, were used to simulate the determination of eyespot foci. Both programs revealed weaknesses in a genetic model previously proposed for eyespot focus determination. On the basis of these simulations, we propose two revised models for eyespot focus determination and identify components of the genetic regulatory hierarchy that are particularly sensitive to changes in model parameter values. These components may play a key role in the evolution of butterfly eyespots. Simulations like these may be useful tools for the study of other evolutionary developmental model systems and reveal similar sensitive components of the relevant genetic regulatory hierarchies.     

A biomolecular implementation of logically reversible computation with minimal energy dissipation

Energy dissipation associated with logic operations imposes a fundamental physical limit on computation and is generated by the entropic cost of information erasure, which is a consequence of irreversible logic elements. We show how to encode information in DNA and use DNA amplification to implement a logically reversible gate that comprises a complete set of operators capable of universal computation. We also propose a method using this design to connect, or 'wire', these gates together in a biochemical fashion to create a logic network, allowing complex parallel computations to be executed. The architecture of the system permits highly parallel operations and has properties that resemble well known genetic regulatory systems.     

Implementation of a genetic logic circuit: bio-register

We introduce an idea of synthesizing a class of genetic registers based on the existing sequential biological circuits, which are composed of fundamental biological gates. In the renowned literature, biological gates and genetic oscillator have been unveiled and experimentally realized in recent years. These biological circuits have formed a basis for realizing a primitive biocomputer. In the traditional computer architecture, there is an intermediate load-store section, i.e. a register, which serves as a part of the digital processor. With which, the processor can load data from a larger memory into it and proceed to conduct necessary arithmetic or logic operations. Then, manipulated data are stored back to the memory by instruction via the register. We propose here a class of bio-registers for the biocomputer. Four types of register structures are presented. In silicon experiments illustrate results of the proposed design.     

Exact methods for the robotic cell problem

This paper investigates an exact method for the Robotic Cell Problem. We present a branch-and-bound algorithm which is the first exact procedure specifically designed with regard to this complex flow shop scheduling variant. Also, we propose a new mathematical programming model as well as new lower bounds. Furthermore, we describe an effective genetic algorithm that includes, as a mutation operator, a local search procedure. We report the results of a computational study that provides evidence that medium-sized instances, with up to 176 operations, can be optimally solved. Also, we found that the new proposed lower bounds outperform lower bounds from the literature. Finally, we show, that the genetic algorithm delivers good solutions while requiring short CPU times.     

Establishment of “The Gene Mine”: a resource for rapid identification of complex trait genes

Identification of genes underlying complex traits presents a challenge to which geneticists have responded with many diverse approaches. A common feature of these approaches is that different research groups must, on a case-by-case basis, replicate similar efforts in recruitment, genetic characterization, and analyses. To avoid this expensive “churning,” an alternative approach has been proposed: production of an experimental genetic reference population, the Collaborative Cross, in which both genetic diversity and mapping power are maximized. Since this population consists of inbred mouse strains, further advantages are that it is essentially infinitely reproducible; genetic characterization needs to be performed only once; and the founder strains’ genomes have been or will be sequenced, allowing imputation of allele sequences of all members of the reference population. Here we describe the establishment of such a genetic reference population, which we dub “The Gene Mine.” Over 1000 genetically distinct lines have been established, descended from eight diverse founder strains. Preliminary phenotypic ascertainment of these strains indicates unexpected variability arising from independent assortment of genetic variants. The Gene Mine will be a powerful resource for characterization of essentially any mouse phenotype that has a genetic basis.     

Design and analysis of a robust genetic Muller C-element

This paper presents results on the design and analysis of a robust genetic Muller C-element. The Muller C-element is a standard logic gate commonly used to synchronize independent processes in most asynchronous electronic circuits. Synthetic biological logic gates have been previously demonstrated, but there remain many open issues in the design of sequential (state-holding) logic operations. Three designs are considered for the genetic Muller C-element: a majority gate, a toggle switch, and a speed-independent implementation. While the three designs are logically equivalent, each design requires different assumptions to operate correctly. The majority gate design requires the most timing assumptions, the speed-independent design requires the least, and the toggle switch design is a compromise between the two. This paper examines the robustness of these designs as well as the effects of parameter variation using stochastic simulation. The results show that robustness to timing assumptions does not necessarily increase reliability, suggesting that modifications to existing logic design tools are going to be necessary for synthetic biology. Parameter variation simulations yield further insights into the design principles necessary for building robust genetic gates. The results suggest that high gene count, cooperativity of at least two, tight repression, and balanced decay rates are necessary for robust gates. Finally, this paper presents a potential application of the genetic Muller C-element as a quorum-mediated trigger.     

Allozyme evidence for extensive and ancient radiations in Australian Onychophora

Allozyme electrophoresis has been employed to examine genetic differentiation among eight described species, and representatives of an additional 15 taxa, of Australian peripatopsid Onychophora. The data reveal extremely high genetic differentiation among the described species and among the other taxa, each of which warrants specific recognition. Rapid protein evolution cannot account for the large genetic distances and it is proposed that these are a consequence of ancient divergence times. A method is presented for extracting phylogenetic information from allozyme data sets which are not amenable to conventional analysis.     

Codon Usage Decreases the Error Minimization Within the Genetic Code

The genetic code is not random but instead is organized in such a way that single nucleotide substitutions are more likely to result in changes between similar amino acids. This fidelity, or error minimization, has been proposed to be an adaptation within the genetic code. Many models have been proposed to measure this adaptation within the genetic code. However, we find that none of these consider codon usage differences between species. Furthermore, use of different indices of amino acid physicochemical characteristics leads to different estimations of this adaptation within the code. In this study, we try to establish a more accurate model to address this problem. In our model, a weighting scheme is established for mistranslation biases of the three different codon positions, transition/transversion biases, and codon usage. Different indices of amino acids physicochemical characteristics are also considered. In contrast to pervious work, our results show that the natural genetic code is not fully optimized for error minimization. The genetic code, therefore, is not the most optimized one for error minimization, but one that balances between flexibility and fidelity for different species.     

Non-B DNA structure-induced genetic instability

Repetitive DNA sequences are abundant in eukaryotic genomes, and many of these sequences have the potential to adopt non-B DNA conformations. Genes harboring non-B DNA structure-forming sequences increase the risk of genetic instability and thus are associated with human diseases. In this review, we discuss putative mechanisms responsible for genetic instability events occurring at these non-B DNA structures, with a focus on hairpins, left-handed Z-DNA, and intramolecular triplexes or H-DNA. Slippage and misalignment are the most common events leading to DNA structure-induced mutagenesis. However, a number of other mechanisms of genetic instability have been proposed based on the finding that these structures not only induce expansions and deletions, but can also induce DNA strand breaks and rearrangements. The available data implicate a variety of proteins, such as mismatch repair proteins, nucleotide excision repair proteins, topoisomerases, and structure specific-nucleases in the processing of these mutagenic DNA structures. The potential mechanisms of genetic instability induced by these structures and their contribution to human diseases are discussed.