We present SASC, Self-Adaptive Semantic Crossover, a new class of crossover operators for genetic programming. SASC operators are designed to induce the emergence and then preserve good building-blocks, using metacontrol techniques based on semantic compatibility measures. SASC performance is tested in a case study concerning the replication of investment funds.

In many texts on evolution the reader will find a characteristic depiction of inheritance and evolution, one showing the generations of an evolving population linked only by a causal flow from genotype to genotype. On this view, the genotype of each organism in this population plays a dual role as both the motor of individual development and as the sole causal channel across the generations. This picture is known to be literally false. In many species, parents exert direct causal influence (...) on their offspring, and some of those influences cause the offspring to resemble the parent. For example, a butterfly that lays her eggs on the same plant host on which she hatched thereby exerts a causal influence on her offspring, and one apt to cause them to resemble her more than they would, had she chosen a plant of a different species. None of this is at all controversial, but it poses a puzzle. If the “Weissmanian” conception is literally false, why is it seen as a perspicacious representation of evolution? (shrink)

Talk of a “genetic program” has become almost as common in cell and evolutionary biology as talk of “genetic information”. But what is a genetic program? I understand the claim that an organism’s genome contains a program to mean that its genes not only carry information about which proteins to make, but also about the conditions in which to make them. I argue that the program description, while accurate in some respects, is ultimately misleading and should be (...) abandoned. After that, I sketch an alternative framework which is better suited to capturing the full informational nature of genes. This framework is centered on the notion of a signaling game, as originally developed by David Lewis, but expanded upon considerably by Brian Skyrms in more recent years. On the view I develop, genes turn out to be the producers and consumers of regulatory or developmental information, rather than entities encoding such information. This finding has consequences that link up with a broader debate in the philosophy of biology concerning inheritance systems. I take this to be one form of theoretical payoff that results from applying the signaling games framework to genes. (shrink)

The biomedical literature makes extensive use of the concept of a genetic program. So far, however, the nature of genetic programs has received no satisfactory elucidation from the standpoint of computer science. This unsettling omission has led to doubts about the very existence of genetic programs, on the grounds that gene regulatory networks lack a predetermined schedule of execution, which may seem to contradict the very idea of a program. I show, however, that we can make perfect (...) sense of genetic programs, if only we abandon the preconception that all computers have a von Neumann architecture. Instead, genetic programs instantiate the computational architecture of Post–Newell Production Systems. That is, genetic programs are unordered sets of conditional instructions, instructions that fire independently when their conditions are matched. For illustration I present a paradigm Production System that regulates the functioning of the well-known lac operon of E. coli. On close reflection it turns out that not only genes, but also proteins encode instructions. I propose, therefore, to rename genetic programs to biomolecular programs. Biomolecular and/or genetic programs, and the cellular computers than run them, are to be understood not as von Neumann computers, but as Post–Newell production systems. (shrink)

The notion of a genetic program has been widely criticized by both biologists and philosophers. But the debate has revolved around a narrow conception of what programs are and how they work, and many criticisms are linked to this same conception. To remedy this, I outline a modern and more apt idea of a program that possesses many of the features critics thought missing from programs. Moving away from over-simplistic conceptions of programs opens the way to a more fruitful (...) interplay of ideas between the complexity of biology and our most complex engineering discipline. (shrink)

Almost all existing genetic programming systems deal with fitness evaluation solely by testing. In this paper, by contrast, we present an original approach that combines genetic programming with Hoare logic with the aid of model checking and finite state automata, henceby proposing a brand new verification-focused formal genetic programming system that makes it possible to evolve reliable programs with mathematicallyverified properties.

This paper presents methods to visualize the structure of trees that occur in genetic programming. These methods allow for the inspection of structure of entire trees even though several thousands of nodes may be involved. The methods also scale to allow for the inspection of structure for entire populations and for complete trials even though millions of nodes may be involved. Examples are given that demonstrate how this new way of “seeing” can afford a potentially rich way of (...) understanding dynamics that underpin genetic programming. The examples indicate further studies that might be enabled by visualizing structure at these scales. (shrink)

Cognitive neuroscience is the branch of neuroscience that studies the neural mechanisms underpinning cognition and develops theories explaining them. Within cognitive neuroscience, computational neuroscience focuses on modeling behavior, using theories expressed as computer programs. Up to now, computational theories have been formulated by neuroscientists. In this paper, we present a new approach to theory development in neuroscience: the automatic generation and testing of cognitive theories using genetic programming (GP). Our approach evolves from experimental data cognitive theories that explain (...) “the mental program” that subjects use to solve a specific task. As an example, we have focused on a typical neuroscience experiment, the delayed-match-to-sample (DMTS) task. The main goal of our approach is to develop a tool that neuroscientists can use to develop better cognitive theories. (shrink)

The existence claim of a "genetic program" encoded in the DNA molecule which controls biological processes such as development has been examined. Sources of belief in such an entity are found in the rhetoric of Mendelian genetics, in the informationist speculations of Schrodinger and Delbruck, and in the instrumental efficacy found in the use of certain viral, and molecular genetic techniques. In examining specific research models, it is found that attempts at tracking the source of biological control always (...) leads back to the complex state of a cell as a whole, the organizational structure of which is not itself encoded in the DNA. It is argued that the "genetic program" is not an existing biological entity and its philosophical and heuristic status is challenged. (shrink)

The existence of a genetic program of development was proposed by molecular biologists in the nineteen-sixties. Historians and philosophers of science have since thoroughly criticized this notion. To fully appreciate its significance, it is interesting to consider the research which was pursued during this period by molecular biologists who proposed this notion. This study focuses on François Jacob's work and on the model of development supported by his lab in the early seventies, the T-complex model. This episode of Jacob's (...) scientific activity has since been forgotten. Characterization of this model shows that the notion of program was used in a metaphoric way and that it did not put any constraint on the work pursued in the lab at that time. Some attention is devoted to the origin of this metaphor in the context of the nineteen-seventies. (shrink)

Genetic Programming (GP) is a technique which permits automatic search for complex solutions using a computer. It goes beyond previous techniques in that it discovers the structure of those solutions. Previously, if one were trying to find an equation to fit a set of data, one would have had to provide the form of the equation (for example a fourth degree polynomial) and the computer could then find the appropriate parameters. By contrast, GP can experiment with a whole (...) range of different functional forms , building equations from a menu of functions, symbols and arithmetic operations. Thus GP can be seen as an essentially creative technique. It is good at finding novel solutions where not much is known about the form of the solution.. (shrink)

The ontogeny of the vertebrate retina has been a topic of interest to developmental biologists and human geneticists for many decades. Understanding the unfolding of the genetic program that transforms a field of progenitors cells into a functionally complex and multi‐layered sensory organ is a formidable challenge. Although classical genetic studies succeeded in identifying the key regulators of retina specification, understanding the architecture of their gene network and predicting their behavior are still a distant hope. The emergence of (...) next‐generation sequencing platforms revolutionized the field unlocking the access to genome‐wide datasets. Emerging techniques such as RNA‐seq, ChIP‐seq, ATAC‐seq, or single cell RNA‐seq are used to characterize eye developmental programs. These studies provide valuable information on the transcriptional and cis‐regulatory profiles of precursors and differentiated cells, outlining the trajectories that connect each intermediate state. Here, recent systems biology efforts are reviewed to understand the genetic programs shaping the vertebrate retina. (shrink)

This paper outlines a critique of the use of the genetic variance–covariance matrix (G), one of the central concepts in the modern study of natural selection and evolution. Specifically, I argue that for both conceptual and empirical reasons, studies of G cannot be used to elucidate so-called constraints on natural selection, nor can they be employed to detect or to measure past selection in natural populations – contrary to what assumed by most practicing biologists. I suggest that the search (...) for a general solution to the difficult problem of identifying causal structures given observed correlation’s has led evolutionary quantitative geneticists to substitute statistical modeling for the more difficult, but much more valuable, job of teasing apart the many possible causes underlying the action of natural selection. Hence, the entire evolutionary quantitative genetics research program may be in need of a fundamental reconsideration of its goals and how they correspond to the array of mathematical and experimental techniques normally employed by its practitioners. (shrink)

Book reviewed in this article: Coping with Genetic Disorders. By John C. Fletcher. Genetics, Ethics and Parenthood. Edited by Karen Lebacqz. Screening and Counseling for Genetic Conditions: The Ethical, Social, and Legal Implications of Genetic Screening, Counseling, and Education Programs. A report of the President's Commission for the Study of Ethical Problems in Medicine and Biomedical and Behavioral Research.

This paper is an attempt to reconstruct the history of genetic and evolutionary theories of same-sex sexual behavior using Imre Lakatos’ methodology of scientific research programs . Although distinct, those two programs are complementary. Whereas the genetic program maintains that homosexuality is genetically inherited, the evolutionary program attempts to explain how such a gene, which apparently reduces the reproductive fitness of its homozygous carrier, is maintained in the population. This appraisal reveals that the two research programs have not (...) been empirically progressive in the Lakatosian sense. I argue that this situation has arisen precisely because of inappropriate over-commitment to the respective hard cores of the two research programs. As adherence to such cores is essential for success in research programs, according to Lakatos, I argue that Lakatos’ account of science may be descriptively adequate but is normatively inadequate. I provide grounds for generalizing this case as follows: the MSRP may successfully capture the logic of axiomised sciences, such as physics, but applies poorly to most sciences, including biological and social sciences, which do not lend themselves to axiomatic organization. (shrink)

The Patient Protection and Affordable Care Act of 2010 (ACA) contains many provisions intended to increase access to and lower the cost of health care by adopting public health measures. One of these promotes the use of at-work wellness programs by both providing employers with grants to develop these programs and also increasing their ability to tie the price employees pay for health insurance for participating in these programs and meeting specific health goals. Yet despite ACA's specific alteration of three (...) different statues which had in the past shielded employees from having to contribute to the cost of their health insurance based on their achieving employer-designated health markers, it chose to leave alone recently enacted rules implementing the Genetic Non-Discrimination Act (GINA), which prohibits employers from asking employees about their family health history in any context, including assessing their risk for setting wellness targets. This article reviews how both the changes made by ACA and the restrictions recently put place by GINA will affect the way employers are likely to structure Wellness Programs. It also considers how these changes reflect the competing social goals of both ACA, which seeks to expand access to the population by lowering costs, and GINA, which seeks to protect individuals from discrimination. It does so by analyzing both positive theories about how these new laws will function and normative theories explaining the likelihood of future friction between the interests of the population of the United States as a whole who are in need of increased and affordable access to health care, and of the individuals living in this country who risk discrimination, as science and medicine continue to make advances in linking genetic make-up to risk of future illness. (shrink)

The passing of the Patient Protection and Affordable Care Act is a triumph for the field of public health. Its inclusion of many provisions intended to prevent illness and promote health endorses the core belief of public health as expressed by Dr. Georges Benjamin, the long-time executive director of the American Public Health Association, in a Washington Post opinion piece praising ACA for “provid[ing] care as far upstream as possible… [in order to] reduce costs by identifying problems early and then (...) managing them to reduce or eliminate the need for more costly care in the future.” In this article, I consider the conflict between ACA’s adoption of public health goals seeing population health and societal interests in protecting individuals from discrimination based on their health. The article focuses on one aspect of ACA which seeks to lower the costs to employers who provide health insurance for their employees by making it easier for them to offer their employees substantial incentives for participating in and meeting the goals of employer-sponsored Wellness Programs. (shrink)

This paper presents the architecture and initial feasibility results of a proto-type communication network that utilizes genetic programming to evolve services and protocols as part of network operation. The network evolves responses to environmental conditions in a manner that could not be preprogrammed within legacy network nodes a priori. A priori in this case means before network operation has begun. Genetic material is exchanged, loaded, and run dynamically within an active network. The transfer and execution of code (...) in support of the evolution of network protocols and services would not be possible without the active network environment. Rapid generation of network service code occurs via a genetic programming paradigm. Complexity and Algorithmic Information Theory play a key role in understanding and guiding code evolution within the network. (shrink)

Synthetic biology research is often described in terms of programming cells through the introduction of synthetic genes. Genetic material is seemingly attributed with a high level of causal responsibility. We discuss genetic causation in synthetic biology and distinguish three gene concepts differing in their assumptions of genetic control. We argue that synthetic biology generally employs a difference-making approach to establishing genetic causes, and that this approach does not commit to a specific notion of genetic (...) program or genetic control. Still, we suggest that a strong program concept of genetic material can be used as a successful heuristic in certain areas of synthetic biology. Its application requires control of causal context, and may stand in need of a modular decomposition of the target system. We relate different modularity concepts to the discussion of genetic causation and point to possible advantages of and important limitations to seeking modularity in synthetic biology systems. (shrink)

In 1969, the field of human genetics was in its infancy. Amniocentesis was a new technique for prenatal diagnosis, and a newborn genetic screening program had been established in one state. There were also concerns about the potential hazards of genetic engineering. A research group at the Hastings Center and Paul Ramsey pioneered in the discussion of genetics and bioethics. Two principal techniques have emerged as being of enduring importance: human gene transfer research and genetic testing and (...) screening. This essay tracks the development and use of these techniques and considers the ethical issues that they raise. (shrink)

The aviation industry is one of the most widely used applications in transportation. Due to the limited capacity of aircraft, revenue management in this industry is of high significance. On the other hand, the hub location problem has been considered to facilitate the demands assignment to hubs. This paper presents an integrated p-hub location and revenue management problem under uncertain demand to maximize net revenue and minimize total cost, including hub establishment and transportation costs. A fuzzy programming model and (...) a genetic algorithm are developed to solve the proposed model with different sizes. The mining and petroleum industry is used for case studies. Results show that the proposed algorithm can obtain a suitable solution in a reasonable amount of time. (shrink)

Genetic engineering is a rapidly evolving field of research with potentially powerful therapeutic applications. The technology CRISPR-Cas9 not only has improved the accuracy and overall feasbility of genome editing but also has increased access to users by lowering cost and increasing usability and speed. The potential benefits of genetic engineering may come with an increased risk of off-target events or carcinogenic growth. Germ-line cell therapy may also pose risks to potential progeny and thus have an additional burden of (...) proof for safety. Persons responsible for evaluating the ethics of genetic-engineering research programs or clinical trials should do so in light of the nature, integrity, and totality of the human person. Recent news of the implantation and birth of genetically engineered human embryos is just one example of increased rogue science. Health care institutions should consider what steps can be taken to prevent or slow this trend. (shrink)

Understanding the mechanisms of early embryonic patterning and the timely allocation of specific cells to embryonic regions and fates as well as their development into tissues and organs, is a fundamental problem in Developmental Biology. The classical explanation for this process had been built around the notion of positional information. Accordingly the programmed appearance of sources of Morphogens at localized positions within a field of cells directs their differentiation. Recently, the development of organs and tissues from unpatterned and initially identical (...) stem cells (adult and embryonic) has challenged the need for positional information and even the integrity of the embryo, for pattern formation. Here we review the emerging area of organoid biology from the perspective of Developmental Biology. We argue that the events underlying the development of these systems are not purely linked to “self‐organization,” as often suggested, but rather to a process of genetically encoded self‐assembly where genetic programs encode and control the emergence of biological structures. (shrink)

According to evolutionary, genetic, and endocrinal perspectives, gender differences are modulated by the interaction between intra-uterine stress, genetic equipments, and the availability of the facilitating environment during the newborn period. The social message of fitness over obstacles during socialization and the discussion of secure/non-secure attachment styles should take into consideration the brain functions, which are altered differently in response to intra- and extra-uterine stress in each gender.

The idea that innateness can be understood in terms of genetic coding or genetic programming is discussed. I argue that biology does not provide any support for the view that the whole-organism features of interest to nativists in psychology and linguistics are genetically coded for. This provides some support for recent critical and deflationary treatments of the concept of innateness.

The transhumanist project of reshaping human beings by promoting their improvement through technological innovations has a broad agenda. This study focuses on the enhancement of the human organism through genetic modification techniques. Transhumanism values and a discussion of their philosophical background provide a framework to understand its ideals. Genetics and ethics are employed to assess the claims of the transhumanist program of human enhancement. A succinct description of central concepts in genetics and an explanation of current techniques to edit (...) the human genome serve to assess the capabilities and limitations of editing techniques. Potential benefits and liabilities of human enhancement through genome editing are discussed to appraise its feasibility. Ethical considerations of genome editing inform a reflection on the implications of introducing heritable changes in the genome of individuals. It is concluded that the transhumanist program is underpinned by a large number of hypotheses rather than by sufficient evidence. (shrink)

This essay analyzes one of Germany's former premier research institutions for biomedical research, the Kaiser Wilhelm Institute for Anthropology, Human Heredity and Eugenics (KWIA) as a test case for the way in which politics and human heredity served as resources for each other during the Third Reich. Examining the KWIA from this perspective brings us a step closer to answering the questions at the heart of most recent scholarship concerning the biomedical community under the swastika: (1) How do we explain (...) why the vast majority of German human geneticists and eugenicists were willing to work for the National Socialist state and, at the very least, legitimized its exterminationist racial policy; and (2) what accounts for at least some of Germany's most renowned medically trained professionals' involvement in forms of morally compromised science that wholly transcend the bounds of normal scientific practice? Although a complete answer to this question must await an examination of other German biological research centers, the present study suggests that during the Nazi period the symbiotic relationship between human genetics and politics served to radicalize both. The dynamic between the science of human heredity and Nazi politics changed the research practice of some of the biomedical sciences housed at the KWIA. It also simultaneously made it easier for the Nazi state to carry out its barbaric racial program leading, finally, to the extermination of millions of so-called racial undesirables. (shrink)

Genetic Programming is a powerful optimization algorithm, which employs the crossover for genetic operation. Because the crossover operator in GP randomly selects sub-trees, the building blocks may be destroyed by the crossover. Recently, algorithms called PMBGPs based on probabilistic techniques have been proposed in order to improve the problem mentioned above. We propose a new PMBGP employing Bayesian network for generating new individuals with a special chromosome called expanded parse tree, which much reduces a number of possible (...) symbols at each node. Although the large number of symbols gives rise to the large conditional probability table and requires a lot of samples to estimate the interactions among nodes, a use of the expanded parse tree overcomes these problems. Computational experiments on two subjects demonstrate that our new PMBGP is much superior to prior probabilistic models. (shrink)

Our program is ambitious, as is any attempt to match life (in our case real science) with virtue (e.g., exactness). We want our semantics to be not only simia mathematicae but also ancilla scientiae: built more geometrico and at the same time relevant, nay useful, to live science. The goal of exactness may sound arrogant but is actually modest, for the more we rigorize the more we are forced to leave out of consideration, at least for the time being. As (...) to the service intention: we should try to be of some help to science because the latter faces semantic problems but has no tools of its own for solving them. If it had such tools scientists would not engage in spirited polemics over matters of sense and reference, as they often do. Witness the debates on whether the relativistic and quantum theories are concerned with sentient observers, whether population genetics refers to populations taken as wholes, whether psychology is actually concerned with the brain, and whether the sense of a theory is excreted by its mathematical formalism or is determined by the way the theory is tested.A semantics of science should help settle these and similar issues. Moreover it should give sound advice as to how to formulate scientific theories so as to avoid such imprecisions and ambiguities as may give rise to debates of the kind. Constructing such a semantics, both exact and relevant to science, should be more rewarding than either manufacturing neat but irrelevant theories or pursuing erratic polemics on meaning and meaning changes. Research supported by a Killam grant awarded by the Canada Council. (shrink)

Reproductive genetic carrier screening is increasingly being offered more widely, including to people with no family history or otherwise elevated chance of having a baby with a genetic condition. There are valid reasons to reject a prevention-focused public health ethics approach to such screening programs. Rejecting the prevention paradigm in this context has led to an emphasis on more individually-focused values of freedom of choice and fostering reproductive autonomy in RCS. We argue, however, that population-wide RCS has sufficient (...) features in common with other public health screening programs that it becomes important also to attend to its public health implications. Not doing so constitutes a failure to address the social conditions that significantly affect people’s capacity to exercise their reproductive autonomy. We discuss how a public health ethics approach to RCS is broader in focus than prevention. We also show that additional values inherent to ethical public health—such as equity and solidarity—are essential to underpin and inform the aims and implementation of reproductive carrier screening programs. (shrink)

There are many ways that biological theory can inform ethical discussions of genetic engineering and biomedical enhancement. In this essay, we highlight some of these potential contributions, and along the way provide a synthetic overview of the papers that comprise this special issue. We begin by comparing and contrasting genetic engineering with programs of selective breeding that led to the domestication of plants and animals, and we consider how genetic engineering differs from other contemporary biotechnologies such as (...) embryo selection. We go on to consider the implications of genetic engineering for human nature, human evolution, and persistence of the human species. Finally, we question whether genetic interventions warrant the extraordinary ethical scrutiny they are often given, and we show how the misleading “genetic blueprint” metaphor has imposed a faulty structure on the enhancement debate. We conclude by considering the nature of biological development and the sobering limits it places on what genetic engineering can reasonably hope to achieve. (shrink)

In this new post-genomic age of medicine and biomedical technology, there will be novel approaches to understanding disease, and to finding drugs and cures for diseases. Hundreds of new “disease genes” thought to be the causative agents of various genetic maladies will be identified and added to the list of hundreds of such genes already identified. Based on this knowledge, many new genetic tests will be developed and used in genetic screening programs. Genetic screening is the (...) foundation upon which reproductive technologies such as pre-natal diagnosis (PND) and preimplantation genetic diagnosis (PGD) are based. Genetic information arising from the human genome may also be used in attempts to redesign the human genetic inheritance by engineering the human germline (germline engineering). In each of these technologies—PND, PGD, and germline engineering—there are serious ethical and social concerns. Moreover, all three are eugenic in nature because they strive to control which genes are passed down to future generations. The goals of this article are threefold: 1) to introduce the science behind the three technologies; 2) to give a brief overview of eugenics in the past century and show how these genetic technologies are eugenic; and 3) to present a vision of social justice that rejects the genetic determinism upon which eugenics is based and embraces a holistic, ecological view of nature and humanity. (shrink)

There are many risks involved in genetic engineering. The release of genetically altered organisms in the environment can increase human suffering, decrease animal welfare, and lead to ecological disasters. The containment of biotechnological material in laboratories and industrial plants contributes to the risk of accidental release, especially if the handling and storage are inadequate. The purely political dangers include intensified economic inequality, the possibility of large-scale eugenic programs, and totalitarian control over human lives. How should the acceptability of these (...) risks be determined? We argue that the assessment should be left to those who can be harmed by the decisions in question. Economic risks are acceptable, if they are condoned by the corporations and governments who take them. The risks imposed on laboratory personnel by the containment of dangerous materials ought to be evaluated by the laboratory personnel themselves. All other risks are more or less universal, and should therefore be assessed as democratically as possible. If risk-taking is based on the choices of those who can be harmed by the consequences, then, even if the undesired outcome is realized, the risk is acceptable, because it is embedded in their own system of ethical and epistemic values. (shrink)