It will be settled out for the open problem of designing an r-order finite-time state observer for reaction-diffusion genetic regulatory networks with time-varying delays. By assuming the Dirichlet boundary conditions, aiming to estimate the mRNA and protein concentrations via available network measurements. Firstly, sufficient F-T stability conditions for the filtering error system have been investigated via constructing an appropriate Lyapunov–Krasovskii functional and using several integral inequalities and convex technique simultaneously. These conditions are delay-dependent and reaction-diffusion-dependent and can (...) be checked by MATLAB toolbox. Furthermore, a method is proposed to design an r-order F-T state observer, and the explicit expressions of observer gains are given. Finally, a numerical example is presented to illustrate the effectiveness of the proposed method. (shrink)

The problem of finite-time stability of switched genetic regulatory networks with time-varying delays via Wirtinger’s integral inequality is addressed in this study. A novel Lyapunov–Krasovskii functional is proposed to capture the dynamical characteristic of GRNs. Using Wirtinger’s integral inequality, reciprocally convex combination technique and the average dwell time method conditions in the form of linear matrix inequalities are established for finite-time stability of switched GRNs. The applicability of the developed finite-time stability conditions is validated by numerical results.

We deal with the design problem of nonfragile state estimator for discrete-time genetic regulatory networks with time-varying delays and randomly occurring uncertainties. In particular, the norm-bounded uncertainties enter into the GRNs in random ways in order to reflect the characteristic of the modelling errors, and the so-called randomly occurring uncertainties are characterized by certain mutually independent random variables obeying the Bernoulli distribution. The focus of the paper is on developing a new nonfragile state estimation method to estimate (...) the concentrations of the mRNA and the protein for considered uncertain delayed GRNs, where the randomly occurring estimator gain perturbations are allowed. By constructing a Lyapunov-Krasovskii functional, a delay-dependent criterion is obtained in terms of linear matrix inequalities by properly using the discrete-time Wirtinger-based inequality and reciprocally convex combination approach as well as the free-weighting matrix method. It is shown that the proposed method ensures that the estimation error dynamics is globally asymptotically stable and the desired estimator parameter is designed via the solutions to certain LMIs. Finally, we provide two numerical examples to illustrate the feasibility and validity of the proposed estimation results. (shrink)

After reviewing theoretical reasons for doubting that machine learning methods can accurately infer gene regulatory networks from microarray data, we test 10 algorithms on simulated data from the sea urchin network, and on microarray data for yeast compared with recent experimental determinations of the regulatory network in the same yeast species. Our results agree with the theoretical arguments: most algorithms are at chance for determining the existence of a regulatory connection between gene pairs, and the algorithms (...) that perform better than chance are nonetheless so errorprone as to be of little practical use in these applications. (shrink)

This paper deals with the problem of reconstruction of the intergenic interaction graph from the raw data of genetic co-expression coming with new technologies of bio-arrays (DMA-arrays, protein-arrays, etc.). These new imaging devices in general only give information about the asymptotical part (fixed configurations of co-expression or limit cycles of such configurations) of the dynamical evolution of the regulatory networks (genetic and/or proteic) underlying the functioning of living systems. Extracting the casual structure and interaction coefficients of (...) a gene interaction network from the observed configurations is a complex problem. But if all the fixed configurations are supposedly observed and if they are factorizable into two or more subsets of values, then the interaction graph possesses as many connected components as the number of factors and the solution is obtained in polynomial time. This new result allows us for example to partly solve the topology of the genetic regulatory network ruling the flowering in Arabidopsis thaliana. (shrink)

Evolution has shaped all living organisms on Earth, although many details of this process are shrouded in time. However, it is possible to see, with one's own eyes, evolution as it happens by performing experiments in defined laboratory conditions with microbes that have suitably fast generations. The longest‐running microbial evolution experiment was started in 1988, at which time twelve populations were founded by the same strain ofEscherichia coli. Since then, the populations have been serially propagated and have evolved for tens (...) of thousands of generations in the same environment. The populations show numerous parallel phenotypic changes, and such parallelism is a hallmark of adaptive evolution. Many genetic targets of natural selection have been identified, revealing a high level of genetic parallelism as well. Beneficial mutations affect all levels of gene regulation in the cells including individual genes and operons all the way to global regulatory networks. Of particular interest, two highly interconnected networks—governing DNA superhelicity and the stringent response—have been demonstrated to be deeply involved in the phenotypic and genetic adaptation of these experimental populations. BioEssays 29:846–860, 2007. © 2007 Wiley Periodicals, Inc. (shrink)

Recent work on the evolution of signaling systems provides a novel way of thinking about genetic information, where information is passed between genes in a regulatory network. I use examples from evolutionary developmental biology to show how information can be created in these networks and how it can be reused to produce rapid phenotypic change.

Various algorithms have been proposed for learning (partial) genetic regulatory networks through systematic measurements of differential expression in wild type versus strains in which expression of specific genes has been suppressed or enhanced, as well as for determining the most informative next experiment in a sequence. While the behavior of these algorithms has been investigated for toy examples, the full computational complexity of the problem has not received sufficient attention. We show that finding the true regulatory (...) network requires (in the worst-case) exponentially many experiments (in the number of genes). Perhaps more importantly, we provide an algorithm for determining the set of regulatory networks consistent with the observed data. We then show that this algorithm is infeasible for realistic data (specifically, nine genes and ten experiments). This infeasibility is not due to an algorithmic flaw, but rather to the fact that there are far too many networks consistent with the data (10 18 in the provided example). We conclude that gene perturbation experiments are useful in confirming regulatory network models discovered by other techniques, but not a feasible search strategy. (shrink)

The logic of genetic discovery has changed little over time, but the focus of biology is shifting from simple genotype–phenotype relationships to complex metabolic, physiological, developmental, and behavioral traits. In light of this, the traditional reductionist view of individual genes as privileged difference‐making causes of phenotypes is re‐examined. The scope and nature of genetic effects in complex regulatory systems, in which dynamics are driven by regulatory feedback and hierarchical interactions across levels of organization are considered. This (...) review argues that it is appropriate to treat genes as specific actual difference‐makers for the molecular regulation of gene expression. However, they are often neither stable, proportional, nor specific as causes of the overall dynamic behavior of regulatory networks. Dynamical models, properly formulated and validated, provide the tools to probe cause‐and‐effect relationships in complex biological systems, allowing to go beyond the limitations of genetic reductionism to gain an integrative understanding of the causal processes underlying complex phenotypes. (shrink)

In this post‐sequencing era, geneticists can focus on functional genomics on a much larger scale than ever before. One goal is the discovery and elucidation of the intricate genetic networks that co‐ordinate transcriptional activation in different regulatory circuitries. High‐throughput gene expression measurement using DNA arrays has thus become routine strategy. This approach, however, does not directly identify gene loci that belong to the same regulatory group; e.g., those that are bound by a common (set of) transcription (...) factor(s). Working in yeast, two groups have recently published an elegant method that could circumvent this problem, by combining chromatin immunoprecipitation and DNA microarrays.(1,2) The method is likely to provide a powerful tool for the dissection of global regulatory networks in eukaryotic cells. BioEssays 23:473–476, 2001. © 2001 John Wiley & Sons, Inc. (shrink)

Cover Photograph: Resolving developmental genetics in the fourth dimension: an illustration (by Kwang‐Hyun Cho himself) of the principle of dynamic network motifs in Drosophila development. Hitherto largely considered in terms of time‐invariant networks, drosophila development is viewed in the article by Man‐Sun Kim, Jeong‐Rae Kim, and Kwang‐Hyun Cho as the result of networks of gene interactions that change during the course of development. Using this paradigm, pivotal developmental events can be correlated with particular changes from one constellation of (...) gene interactions to a different one, and the method allows the identification of certain network motifs that are not identifiable using static approaches. Features article: “Dynamic network rewiring determines temporal regulatory functions in the Drosophila melanogaster development processes”, see pages 505 – 513. (shrink)

At the interface of developmental biology and evolutionary biology, the very criteria of scientific knowledge are up for grabs. A central issue is the status of evolutionary genetics models, which some argue cannot coherently be used with complex gene regulatory network (GRN) models to explain the same evolutionary phenomena. Despite those claims, many researchers use evolutionary genetics models jointly with GRN models to study evolutionary phenomena. This dissertation compares two recent research projects in which researchers jointly use the two (...) kinds of models. I use methods from the empirical social sciences, such as digital corpus analysis, content analysis, and structured case analysis. I infer three primary conclusions about projects of the kind studied. First, they employ an implicit concept of gene that enables the joint use of both kinds of models. Second, they pursue more epistemic aims besides mechanistic explanation of phenomena. Third, they don’t work to create and export broad synthesized theories. Rather, they focus on phenomena too complex to be understood by a common general theory, they distinguish parts of the phenomena, and they apply models from different theories to the different parts. For such projects, seemingly incompatible models are synthesized largely through mediated representations of complex phenomena. (shrink)

Biochemical networks are often called upon to illustrate emergent properties of living systems. In this contribution, I question such emergentist claims by means of theoretical work on genetic regulatory models and random Boolean networks. If the existence of a critical connectivity Kc of such networks has often been coined “emergent” or “irreducible”, I propose on the contrary that the existence of a critical connectivity Kc is indeed mathematically explainable in network theory. This conclusion also applies (...) to many other types of formal networks and weakens the emergentist claim attached to bio-molecular networks, and by extension to living systems. (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)

Explanation in terms of gene regulatory networks has become standard practice in evolutionary developmental biology. In this paper, we argue that GRNs fail to provide a robust, mechanistic, and dynamic understanding of the developmental processes underlying the genotype–phenotype map. Explanations based on GRNs are limited by three main problems: the problem of genetic determinism, the problem of correspondence between network structure and function, and the problem of diachronicity, as in the unfolding of causal interactions over time. Overcoming (...) these problems requires dynamic mechanistic explanations, which rely not only on mechanistic decomposition, but also on dynamic modeling to reconstitute the causal chain of events underlying the process of development. We illustrate the power and potential of this type of explanation with a number of biological case studies that integrate empirical investigations with mathematical modeling and analysis. We conclude with general considerations on the relation between mechanism and process in evo-devo. (shrink)

A network of gene regulation organized in a hierarchical and combinatorial manner is crucially involved in the development of the neural network, and has to be considered one of the main substrates of genetic change in its evolution. Though qualitative features may emerge by way of the accumulation of rather unspecific quantitative changes, it is reasonable to assume that at least in some cases specific combinations of regulatory parts of the genome initiated new directions of evolution, leading to (...) novel capabilities of the brain. These notions are applied, in this paper, to the evolution of the capability of cognition-based human empa­thy. It is suggested that it has evolved as a secondary effect of the evolution of strategic thought. Development of strategies depends on abstract representations of one’s own pos­sible future states in one’s own brain to allow assessment of their emotional desirability, but also on the representation and emotional evaluation of possible states of others, allowing anticipation of their behaviour. This is best achieved if representations of others are con­nected to one’s own emotional centres in a manner similar to self-representations. For this reason, the evolution of the human brain is assumed to have established representations with such linkages. No group selection is involved, because the quality of strategic thought affects the fitness of the individual. A secondary effect of this linkage is that both the actual states and the future perspectives of others elicit vicarious emotions, which may contribute to the motivations of altruistic behaviour. (shrink)

Recent studies have revealed an astonishing diversity of sex chromosomes in many vertebrate lineages, prompting questions about the mechanisms of sex chromosome turnover. While there is considerable population genetic theory about the evolutionary forces promoting sex chromosome replacement, this theory has not yet been integrated with our understanding of the molecular and developmental genetics of sex determination. Here, we review recent data to examine four questions about how the structure of gene networks influences the evolution of sex determination. (...) We argue that patterns of epistasis, arising from the structure of genetic networks, may play an important role in regulating the rates and patterns of sex chromosome replacement. (shrink)

Classic genetics studies found that genomic imbalance caused by changing the dosage of part of the genome (aneuploidy) has more detrimental effects than altering the dosage of the whole genome (ploidy). Previous analysis revealed global modulation of gene expression triggered by aneuploidy across various species, including maize (Zea mays), Arabidopsis, yeast, mammals, etc. Plant microRNAs (miRNAs) are a class of 20‐ to 24‐nt endogenous small noncoding RNAs that carry out post‐transcriptional gene expression regulation. That miRNAs and their putative targets are (...) preferentially retained as duplicates after whole‐genome duplication, as are many transcription factors and signaling components, indicates miRNAs are likely to be dosage‐sensitive and potentially involved in genomic balance networks. This review addresses the following questions regarding the role of miRNAs in genomic imbalance. (1) How do aneuploidy and polyploidy impact the expression of miRNAs? (2) Do miRNAs play a regulatory role in modulating the expression of their targets under genomic imbalance? (shrink)

The regulatory structures underlying United States and European Union policies regarding genetically modified (GM) food and crops are fundamentally different. The US regulates GM foods and crops as end products, applying roughly the same regulatory framework that it does to non GM foods or crops. The EU, on the other hand, regulates products of agricultural biotechnology as the result of a specific production process. Accordingly, it has developed a network of rules that regulate GM foods and crops specifically. (...) As a result, US regulation of GM foods and crops is relatively permissive, whereas EU regulation is relatively restrictive. Why are genetically modified food policies in the United States and the European Union so strikingly different? In the light of the recent World Trade Organization dispute on agricultural biotechnology, it may seem that economic interests are the driving force behind policies. While they are certainly part of the picture, the issue is far more complex. This paper argues that three different elements help explain differences between US and EU GM food policies. First, an investigation of US and European policies of the 1970s and 1980s on recombinant DNA research and of events leading up to early GM food and crop regulation allows a deeper understanding of current policy. Second, scrutinizing underlying values and norms can uncover the beliefs that condition current GM food and crop policy. Third, an analysis of involved actors’ views and levels of success in influencing policy is essential to understanding US and EU policies. (shrink)

Through their transcript products genes regulate the rates at which an immense variety of transcripts and subsequent proteins occur. Understanding the mechanisms that determine which genes are expressed, and when they are expressed, is one of the keys to genetic manipulation for many purposes, including the development of new treatments for disease. Viewing each gene in a genome as a distinct variable that is either on or off, or more realistically as a continuous variable, the values of some of (...) these variables influence the values of others through the regulatory proteins they express, including, of course, the possibility that the rate of expression of a gene at one time may, in various circumstances, influence the rate of expression of that same gene at a later time. If we imagine an arrow drawn from each gene expression variable at a given time to a gene variable whose expression it influences a short while after, the result is a network, technically a directed acyclic graph. For example, the DAG in Figure 1 is a representation of a system in which the expression level of gene G1 at time 1 ) causes the expression level of G2, which in turn causes the expression level of G3. The arrows in Figure 1 which do not have a variable at their tails are “error terms” which represent all of the causes of a variable other than the ones explicitly represented in the DAG. The DAG describes more than associations—it describes causal connections among gene expression rates. A shock to a cell—by mutation, heating, chemical treatment, etc. may alter the DAG describing the relations among gene expressions, for example by activating a gene that was otherwise not expressed, producing a cascade of new expression effects. Although “knockout” experiments can reveal some of the underlying causal network of gene expression levels, unless guided by information from other sources, such experiments are limited in how much of the network structure they can reveal, due to the sheer number of possible combinations of experimental manipulations of genes necessary to reveal the complete causal network. Recent developments have made it possible to compare quantitatively the expression of tens of thousands of genes in cells from different sources in a single experiment, and to trace gene expression over time in thousands of genes simultaneously. cDNA microarrays are already producing extensive data, much of it available on the web. Thus there are calls for analytic software that can be applied to microarray and other data to help infer regulatory networks. In this paper we will review current techniques that are available for searching for the causal relations between variables, describe algorithmic and data gathering obstacles to applying these techniques to gene expression levels, and describe the prospects for overcoming these obstacles. (shrink)

Darwinian evolutionary theory has two key terms, variations and biological selection, which finally lead to survival of the fittest variant. With the rise of molecular genetics, variations were explained as results of error replications out of the genetic master templates. For more than half a century, it has been accepted that new genetic information is mostly derived from random error-based events. But the error replication narrative has problems explaining the sudden emergence of new species, new phenotypic traits, and (...) genome innovations as a sudden single event. Meanwhile, it is recognized that errors cannot explain the evolution of genetic information, genetic novelty, and complexity. Now, empirical evidence establishes the crucial role of non-random genetic content editors, such as viruses, diversity generating retroelements, and other RNA networks, to produce new genetic information, complex regulatory control, inheritance vectors, genetic identity, immunity, new sequence space, evolution of complex organisms, and evolutionary transitions. (shrink)

Graphical AbstractRecent waves of controversies surrounding genetic engineering have spilled into popular science in Twitter battles between reputable scientists and their followers. Here, a cautionary perspective on the possible blind spots and risks of CRISPR and related biotechnologies is presented, focusing in particular on the stochastic nature of cellular control processes.

Transposable elements are no longer considered to be “junk” DNA. Here, we review how TEs can impact gene regulation systematically. TEs encode various regulatory elements that enables them to regulate gene expression. RJ Britten and EH Davidson hypothesized that TEs can integrate the function of various transcriptional regulators into gene regulatory networks. Uniquely TEs can deposit regulatory sites across the genome when they transpose, and thereby bring multiple genes under control of the same regulatory logic. (...) Several studies together have robustly established that TEs participate in embryonic development and oncogenesis. We discuss the regulatory characteristics of TEs in context of evolution to understand the extent of their impact on gene networks. Understanding these features of TEs is central to future investigations of TEs in cellular processes and phenotypic presentations, which are applicable to development and disease studies. We re-visit the Britten–Davidson “gene-battery” model and understand the genetic and transcriptional impact of TEs in innovating gene regulatory networks. Transposable elements are exogenous sequences that have either been co-opted or repurposed for host functions. The vast amounts of TE sequence in the genome provides raw material for gene expression regulation, and still remains to be fully understood; the “gene-battery” model provides the basis for understanding this. (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 examines processes of translation through which molecular genetic technologies and practices are incorporated into environmental health research and regulation. Specifically, it considers how scientists, risk assessors, and regulators have used genetically modified mouse models to translate across scientific disciplines, articulate emergent molecular forms, standards, and practices with the extant? gold standard,? and establish roles for molecular knowledge in risk assessment and regulation. Noting variation both within and between regulatory agencies in responses to data from these models, (...) the article describes also the role of public-private networks and their effects on professional and institutional imperatives which shape regulators? responses to the potential applications of these models. The conclusions address the importance of translation for understanding the wider implications of the molecularization of environmental health science. (shrink)

Many natural and biological phenomena can be depicted as networks. Theoretical and empirical analyses of networks have become prevalent. I discuss theoretical biases involved in the delineation of biological networks. The network perspective is shown to dissolve the distinction between regulatory architecture and regulatory state, consistent with the theoretical impossibility of distinguishing a priori between “program” and “data”. The evolutionary significance of the dynamics of trans-generational and inter-organism regulatory networks is explored and implications (...) are presented for understanding the evolution of the biological categories development-heredity; plasticity-evolvability; and epigenetic-genetic. (shrink)

Viruses and related infectious genetic parasites are the most abundant biological agents on this planet. They invade all cellular organisms, are key agents in the generation of adaptive and innate immune systems, and drive nearly all regulatory processes within living cells.

Co‐option of the eye developmental gene regulatory network may have led to the appearance of novel functional traits on the wings of flies and butterflies. The first trait is a recently described wing organ in a species of extinct midge resembling the outer layers of the midge's own compound eye. The second trait is red pigment patches on Heliconius butterfly wings connected to the expression of an eye selector gene, optix. These examples, as well as others, are discussed regarding (...) the type of empirical evidence and burden of proof that have been used to infer gene network co‐option underlying the origin of novel traits. A conceptual framework describing increasing confidence in inference of network co‐option is proposed. Novel research directions to facilitate inference of network co‐option are also highlighted, especially in cases where the pre‐existent and novel traits do not resemble each other. (shrink)

Genetic regulatory networks are complex, involving tens or hundreds of genes and scores of proteins with varying dependencies and organizations. This invites the application of artificial techniques in coming to understand natural complexity. I describe two attempts to deploy artificial models in understanding natural complexity. The first abstracts from empirically established patterns, favoring random architectures and very general constraints, in an attempt to model developmental phenomena. The second incorporates detailed information concerning the genetic structure, organization, and (...) dependencies in actual systems in an attempt to explain developmental differences. The results offered by these models, pitched at these different levels of abstraction, are different. The more detailed models are more continuous with classical developmental approaches. (shrink)

Co‐option of the eye developmental gene regulatory network may have led to the appearance of novel functional traits on the wings of flies and butterflies. The first trait is a recently described wing organ in a species of extinct midge resembling the outer layers of the midge's own compound eye. The second trait is red pigment patches on Heliconius butterfly wings connected to the expression of an eye selector gene, optix. These examples, as well as others, are discussed regarding (...) the type of empirical evidence and burden of proof that have been used to infer gene network co‐option underlying the origin of novel traits. A conceptual framework describing increasing confidence in inference of network co‐option is proposed. Novel research directions to facilitate inference of network co‐option are also highlighted, especially in cases where the pre‐existent and novel traits do not resemble each other. (shrink)

Collaborative forms of work such as extended networks, expert groups, and consortia increasingly structure biomedical activities. They are particularly prominent in the cancer field, where procedures such as multicenter clinical trials have been instrumental in establishing the specialty of oncology, and subfields such as cancer genetics, where bioclinical activities—for example, testing for breast and ovarian cancer genes and follow-up interventions—are predicated on the articulation of a number of tasks performed by new clinical collectives. In this article, we examine the (...) founding and development of a French bioclinical collective—the Groupe Génétique et Cancer —that coordinates and structures the activities of most French actors in cancer genetics and operates simultaneously in the clinical, research, and regulatory domains. To examine the group’s structure and dynamics, the article combines information gathered through traditional fieldwork methods with information elicited from a coauthorship and semantic-network analysis of the publications of GGC members from 1969 to 2001. (shrink)

The “Lošinj Declaration on Biotic Sovereignty” is a novelty in the consideration of the environment and life in general and a unique document on a global scale. Until the advent of the Declaration, the environment was usually considered in an instrumentalist way, following the prevailing techno-scientific paradigm. The Declaration introduces biotic sovereignty as the starting point for the debate on GMOs, from which the harmfulness or potential benefits of genetic engineering can be assessed. The protection of biotic sovereignty should (...) be one of the crucial values that European and Croatian citizens should defend in the upcoming struggle to change and probably drastically reduce the regulatory regime for genetically modified crops in the European Union and thus also in Croatia. In this paper, we highlight the importance of the “Lošinj Declaration on Biotic Sovereignty” in the context of the emergence of new gene regulation techniques that are becoming a threat to biotic sovereignty. We analyse the lobbying process against the ruling C-528/16 using the example of the scientists united in the network EU-SAGE. The central part of the paper analyses the controversy over a new European Commission study on new genetic techniques and the political context of the conflict between the European Commission and the European Parliament over the authorisation of new seed varieties of genetically modified crops. (shrink)

Functional neuroimaging studies allow examination of the cerebral networks involved in human behavior. For pathological aggression, several studies have reported a involvement of frontal and temporal areas, reflecting disruption of emotional regulatory systems. Recent genetic studies that bring together reward system dysfunction and violent behavior.

Somatic complementation by fusion of two mutant cells and mixing of their cytoplasms occurs when the genetic defect of one fusion partner is cured by the functional gene product provided by the other. We have found that complementation of mutational defects in the network mediating stimulus‐induced commitment and sporulation of Physarum polycephalum may reflect time‐dependent changes in the signaling state of its molecular building blocks. Network perturbation by fusion of mutant plasmodial cells in different states of activation, and the (...) time‐resolved analysis of somatic complementation effects can be used to systematically probe network structure and dynamics. Time‐resolved somatic complementation quantitatively detects regulatory interactions between the functional modules of a network, independent of their biochemical composition or subcellular localization, and without being limited to direct physical interactions. BioEssays 25:950–960, 2003. © 2003 Wiley Periodicals, Inc. (shrink)

This paper investigated the part played by collaborative practices in chaneling the work of prominent biochemists into the development of molecular biology. The RNA collaborative network that emerged in the 1960s in France encompassed a continuum of activities that linked laboratories to policy-making centers. New institutional frameworks such as the DGRST committees were instrumental in establishing new patterns of funding, and in offering arenas for multidisciplinary debates and boundary assessment. It should be stressed however, that although this collaborative network was (...) based on centralized initiatives aimed at developing molecular biology as a new biological specialty, it operated above all as a nexus of practices. The main argument of this paper is that the central allocation of funds and resources, exemplified by the DGRST operation, actually enhanced the creation of a self-conscious community of biochemists turned molecular biologists by virtue of an increased circulation of tools, skills, and results that took place within the RNA network and a few analogous systems of exchange.Having hands on “things” viewed as identical for all practical purposes was a potent factor in changing the experimental systems and their meanings. Limited but shared means of doing helped to reduce uncertainties, change representations, and turn contingent decisions into meaningful choices. The collaborative enterprises then resulted in personal contacts and the transfer of skills and materials, which gradually incorporated the biochemical tools into systems producing facts relevant to molecular biology as defined by its early practitioners. In that sense, networking was a regulatory process that stabilized new research objects and acculturated French biochemists.The mere existence of such a collaborative network also changed the scale of the disciplining process. Collaborations may have been started for contingent motives, but multiple exchanges resulted in the emergence of a new collective, and amplified small displacements. Collaborations, however, worked both ways, and the RNA network may be viewed as an efficient “trading-post.” An unexpected outcome of the development of a conversion zone is the fact that, by the late 1960s, the former biochemists dominated the “new” world of molecular biology — both in terms of research habits, since interests in structural studies dominated the field, and in terms of institutional initiatives such as the creation of laboratories and institutes for molecular biology.As an example of the cognitive displacements achieved by the network, I have focused here on the stabilization of “messenger RNA” as a new biological entity. This process illustrates the role of “boundary objects” and other mediating innovations in the development of disciplinary structures. Students of science trained in the symbolic interactionism tradition have proposed that “boundary objects” enhance the multiple interactions between heterogeneous social worlds: they are robust enough to enhance unity, but plastic enough to be manipulated in different social and cultural contexts.81 Within the emerging network, messenger RNA was a weakly structured “genetic information carrier” in common use, but it could, at the same time, be a strongly structured “macromolecular structure” adapted to practical and local uses. Consequently, messenger RNA favored the association of groups of heterogeneous scientists with backgrounds and interests in medical biochemistry, genetics, physical chemistry, organic chemistry, and so forth. This contrast between general and local uses was also instrumental in integrating the manipulation of things and the negotiation of aims. In contrast to transfer RNAs, which in the French context remained objects for chemical (and mainly structural) studies, messenger RNA became a key component of the new culture of “genetic information”. Messenger RNA was a loose theoretical entity described as a “genetic information carrier” in the policy-making documents, while operational but tacit and more conflicting definitions prevailed at the bench. In other words, messenger RNA was not only a classical “boundary object” but also a “flag object,” which tightened the collaborative network by mediating between the DGRST offices and the laboratories. (shrink)

Although developmental biology is an institutionalized discipline, no unambiguous account of what development is and when it stops has so far been provided. In this article, I focus on two sets of developmental molecular mechanisms, namely those underlying the heterochronic pathway in C. elegans and those involving Hox genes in vertebrates, to suggest a conceptual account of animal development. I point out that, in these animals, the early stages of life exhibit salient mechanistic features, in particular in the way mechanisms (...) of genetic regulation occur in the organism. Indeed, these stages are characterized by sequential and irreversible changes in gene expression taking place throughout the organism. A general definition of animal development based on these distinctive features implies that, at least for some animal species, development does not go on throughout the life of the animal, contrary to what has recently been claimed by some biologists and philosophers. Instead, in such species, development encompasses various events occurring sequentially at the beginning of life. (shrink)

Hindbrain development is orchestrated by a vertebrate gene regulatory network that generates segmental patterning along the anterior–posterior axis via Hox genes. Here, we review analyses of vertebrate and invertebrate chordate models that inform upon the evolutionary origin and diversification of this network. Evidence from the sea lamprey reveals that the hindbrain regulatory network generates rhombomeric compartments with segmental Hox expression and an underlying Hox code. We infer that this basal feature was present in ancestral vertebrates and, as an (...) evolutionarily constrained developmental state, is fundamentally important for patterning of the vertebrate hindbrain across diverse lineages. Despite the common ground plan, vertebrates exhibit neuroanatomical diversity in lineage‐specific patterns, with different vertebrates revealing variations of Hox expression in the hindbrain that could underlie this diversification. Invertebrate chordates lack hindbrain segmentation but exhibit some conserved aspects of this network, with retinoic acid signaling playing a role in establishing nested domains of Hox expression. (shrink)

We give in this paper indications about the dynamical impact coming from the main sources of perturbation in biological regulatory networks. First, we define the boundary of the interaction graph expressing the regulations between the main elements of the network . Then, we search what changes in the state values on the boundary could cause some changes of states in the core of the system . After, we analyse the role of the mode of updating on the asymptotics (...) of the network, essentially on the occurrence of limit cycles . Finally, we show the influence of some topological changes on the dynamical behaviour of the system. (shrink)

The major challenge in complex disease genetics is to understand the fundamental features of this complexity and why functional alterations at multiple independent genes conspire to lead to an abnormal phenotype. We hypothesize that the various genes involved are all functionally united through gene regulatory networks (GRN), and that mutant phenotypes arise from the consequent perturbation of one or more rate‐limiting steps that affect the function of the entire GRN. Understanding a complex phenotype thus entails unraveling the details (...) of each GRN, namely, the transcription factors that bind to cis regulatory elements affected by sequence variants altering transcription of specific genes, and their mutual feedback relationships. These GRNs can be identified through their rate‐limiting steps and are best uncovered by genomic analyses of rare, extreme phenotype families, thus providing a coherent molecular basis to complex traits and disorders. (shrink)

Developmental processes in complex animals are directed by a hardwired genomic regulatory code, the ultimate function of which is to set up a progression of transcriptional regulatory states in space and time. The code specifies the gene regulatory networks (GRNs) that underlie all major developmental events. Models of GRNs are required for analysis, for experimental manipulation and, most fundamentally, for comprehension of how GRNs work. To model GRNs requires knowledge of both their overall structure, which depends (...) upon linkage amongst regulatory genes, and the modular building blocks of which GRNs are heirarchically constructed. The building blocks consist of basic transcriptional control processes executed by one or a few functionally linked genes. We show how the functions of several such building blocks can be considered in mathematical terms, and discuss resolution of GRNs by both “top down” and “bottom up” approaches. BioEssays 24:1118–1129, 2002. © 2002 Wiley‐Periodicals, Inc. (shrink)

I criticize Herbert Simon 's argument for the claim that complex natural systems must constitute decomposable, mereological or functional hierarchies. The argument depends on certain assumptions about the requirements for the successful evolution of complex systems, most importantly, the existence of stable, intermediate stages in evolution. Simon offers an abstract model of any process that succeeds in meeting these requirements. This model necessarily involves construction through a decomposable hierarchy, and thus suggests that any complex, natural, i.e., evolved, system is constituted (...) by a decomposable hierarchy. I argue that Stuart Kauffman's recent models of genetic regulatory networks succeed in specifying processes that could meet Simon 's requirements for evolvability without requiring construction through a decomposable hierarchy. Since Kauffman's models are at least as plausible as Simon 's model, Simon 's argument that complex natural systems must constitute decomposable, mereological or functional hierarchies does not succeed. (shrink)

The Neo‐Darwinian concept of natural selection is plausible when one assumes a straightforward causation of phenotype by genotype. However, such simple 1:1 mapping must now give place to the modern concepts of gene regulatory networks and gene expression noise. Both can, in the absence of genetic mutations, jointly generate a diversity of inheritable randomly occupied phenotypic states that could also serve as a substrate for natural selection. This form of epigenetic dynamics challenges Neo‐Darwinism. It needs to incorporate (...) the non‐linear, stochastic dynamics of gene networks. A first step is to consider the mathematical correspondence between gene regulatory networks and Waddington's metaphoric ‘epigenetic landscape’, which actually represents the quasi‐potential function of global network dynamics. It explains the coexistence of multiple stable phenotypes within one genotype. The landscape's topography with its attractors is shaped by evolution through mutational re‐wiring of regulatory interactions – offering a link between genetic mutation and sudden, broad evolutionary changes. (shrink)

Langerhans cells (LCs), residing in the epidermis, are able to induce potent immunogenic responses and also to mediate immune tolerance. We propose that tolerogenic and immunogenic responses of LCs are directed by signaling from the epidermis and involve counter‐acting gene circuits that are coupled to a core maturation gene module. We base our analysis on recent genetic and genomic findings facilitating the understanding of the molecular mechanisms controlling these divergent immune functions. Comparing gene regulatory network (GRN) analyses of (...) various types of dendritic cells (DCs) including LCs we integrate signaling‐dependent (TGFβ, EpCAM, β‐Catenin) and transcription factor (IRF4, IRF1, NFκB) regulated gene circuits that appear to orchestrate the distinctive LC functional states. Our model proposes, that while epidermal signaling in the steady‐state promotes LC tolerogenic function, the disruption of cell‐cell contacts coupled with inflammatory signaling induces LC immunogenic programing. The conceptual framework emphasizes the sensing of discrete epidermal and inflammatory cues by resident LCs in dictating their genomic programing and cell state dynamics. (shrink)

Computational approaches in systems biology have become a powerful tool for understanding the fundamental mechanisms of cellular metabolism and regulation. However, the interplay between the regulatory and the metabolic system is still poorly understood. In particular, there is a need for formal mathematical frameworks that allow analyzing metabolism together with dynamic enzyme resources and regulatory events. Here, we introduce a metabolic-regulatory network model that allows integrating metabolism with transcriptional regulation, macromolecule production and enzyme resources. Using this model, (...) we show that the dynamic interplay between these different cellular processes can be formalized by a hybrid automaton, combining continuous dynamics and discrete control. (shrink)

Current research on the origin of DNA and RNA, viruses, and mobile genetic elements prompts a re-evaluation of the origin and nature of genetic material as the driving force behind evolutionary novelty. While scholars used to think that novel features resulted from random genetic mutations of an individual’s specific genome, today we recognize the important role that acquired viruses and mobile genetic elements have played in introducing evolutionary novelty within the genomes of species. Viral infections and (...) subviral RNAs can enter the host genome and persist as genetic regulatory networks. Persistent viral infections are also important to understand the split between great apes and humans. Nearly all mammals and nonhuman primates rely on olfaction, i.e., chemoreception as the basis of the sense of smell for social recognition, group membership, and the coordination of organized social life. Humans, however, evolved other means to establish social bonding, because several infection waves by endogenous retroviruses caused a loss of odor receptors in human ancestors. The human independence from olfaction for social recognition was in turn one driver of the rather abrupt human transition to dependence on visual information, gesture production, and facial recognition that are at the roots of language-based communication. (shrink)

The international context of the last fifty years of modern bioethics have been significant in establishing health-care ethics or bioethics as a common parlance - an ideology of our times, achieving near universal acceptance, with little dissent. Most international health organizations have developed important declarations that have become the credo of their daily practice and long-term commitments. However, in the last decade in particular, bioethicists and other health-care practitioners and scholars have worried about the persistence of health-care inequities and the (...) inadequate realization of bioethics, particularly in low-to-middle income countries. Global bioethics, now well into the new millennium, has entered a regulatory crisis: it needs to confront not just global bioethical commitments around major scientific revolutions such as genomics, but further, a regulatory crisis about the persisting national public law silences and health inequities, especially in low-to-middle income countries. (shrink)

The international context of the last fifty years of modern bioethics have been significant in establishing health-care ethics or bioethics as a common parlance - an ideology of our times, achieving near universal acceptance, with little dissent. Most international health organizations have developed important declarations that have become the credo of their daily practice and long-term commitments. However, in the last decade in particular, bioethicists and other health-care practitioners and scholars have worried about the persistence of health-care inequities and the (...) inadequate realization of bioethics, particularly in low-to-middle income countries. Global bioethics, now well into the new millennium, has entered a regulatory crisis: it needs to confront not just global bioethical commitments around major scientific revolutions such as genomics, but further, a regulatory crisis about the persisting national public law silences and health inequities, especially in low-to-middle income countries. (shrink)