Network motifs are small patterns of connections, found over‐represented in gene regulatory networks. An example is the negative feedback loop (e.g. factor A represses itself). This opposes its own state so that when ‘on’ it tends towards ‘off’ – and vice versa. Here, we argue that such self‐opposition, if considered dimensionlessly, is analogous to the liar paradox: ‘This statement is false’. When ‘true’ it implies ‘false’ – and vice versa. Such logical constructs have provided philosophical consternation for over (...) 2000 years. Extending the analogy, other network topologies give strikingly varying outputs over different dimensions. For example, the motif ‘A activates B and A. B inhibits A’ can give switches or oscillators with time only, or can lead to Turing‐type patterns with both space and time (spots, stripes or waves). It is argued here that the dimensionless form reduces to a variant of ‘The following statement is true. The preceding statement is false’. Thus, merely having a static topological description of a gene network can lead to a liar paradox. Network diagrams are only snapshots of dynamic biological processes and apparent paradoxes can reveal important biological mechanisms that are far from paradoxical when considered explicitly in time and space. (shrink)

Embryonic development combines paradoxical properties: it has great precision, it is usually conducted at breakneck speed and it is flexible on relatively short evolutionary time scales, particularly at early stages. While these features appear mutually exclusive, we consider how they may be reconciled by the properties of key early regulatory networks. We illustrate these ideas with the network that controls development of endoderm progenitors. We argue that this network enables precision because of its intrinsic stability, self propagation and (...) dependence on signalling. The network enables high developmental speed because it is rapidly established by maternal inputs at multiple points. In turn these properties confer flexibility on an evolutionary time scale because they can be initiated in many ways, while buffering essential progenitor cell populations against changes in their embryonic environment on both evolutionary and developmental time scales. Although stable, these networks must be capable of rapid dissolution as cell differentiation progresses. While we focus on the core early endodermal network of vertebrates, we argue that these properties are likely to be general in early embryonic stem cell populations, such as mammalian ES cells. BioEssays 30:757–765, 2008. © 2008 Wiley Periodicals, Inc. (shrink)

The potential of the vertebrate limb as a model system to study developmental mechanisms is particularly well illustrated by the analysis of the Hox gene network. These genes are probably involved in the establishment of patterns encoding positional information. Their functional organisation during both limb and trunk development are very similar and seem to involve the progressive activation in time, along the chromosome, of a battery of genes whose products could differentially instruct those cells where they are expressed. (...) This process may be common to all organisms that develop according to an anterior‐posterior morphogenetic progression. The possible linkage of this system to a particular mechanism of segmentation as well as its phylogenetic implications are discussed. (shrink)

The potential of the vertebrate limb as a model system to study developmental mechanisms is particularly well illustrated by the analysis of the Hox gene network. These genes are probably involved in the establishment of patterns encoding positional information. Their functional organisation during both limb and trunk development are very similar and seem to involve the progressive activation in time, along the chromosome, of a battery of genes whose products could differentially instruct those cells where they are expressed. (...) This process may be common to all organisms that develop according to an anterior‐posterior morphogenetic progression. The possible linkage of this system to a particular mechanism of segmentation as well as its phylogenetic implications are discussed. (shrink)

Cells can transit between a range of stable epithelial and mesenchymal states and this has allowed the evolution of complex body forms. Epithelial to mesenchymal transition (EMT) and its reverse, mesenchymal to epithelial transition (MET), occur sequentially in development and organogenesis. EMT often accompanies transitions between stem‐like cells and their more differentiated progeny, as occurs at gastrulation, although the relevance of this had not been clarified. New findings from the cancer and cell reprogramming fields suggest that EMT and MET can (...) act as essential portals to stem cell character. Here, we review these findings in the broader context of EMT and MET with emphasis on stem cell biology. Using the heart as an example, we also explore the potential role of EMT/MET in organ regeneration. Understanding EMT and MET at a network level will give us new tools to probe stem cell character and enhance tissue repair. (shrink)

Sex‐specific transcriptional and epigenomic profiles are detectable in the embryo very soon after fertilization. I propose that in male (XY) and female (XX) pre‐implantation embryos sex chromosomes establish sexually dimorphic interactions with the autosomes, before overt differences become apparent and long before gonadogenesis. Lineage determination restricts expression biases between the sexes, but the epigenetic differences are less constrained and can be perpetuated, accounting for dimorphisms that arise later in life. In this way, sexual identity is registered in the epigenome very (...) early in development. As development progresses, sex‐specific regulatory modules are harbored within shared transcriptional networks that delineate common traits. In reviewing this field, I propose that analyzing the mechanisms for sexual dimorphisms at the molecular and biochemical level and incorporating developmental and environmental factors will lead to a greater understanding of sex differences in health and disease. (shrink)

This paper concerns periodic solutions of a class of equations that model gene regulatory networks. Unlike the vast majority of previous studies, it is not assumed that all decay rates are identical. To handle this more general situation, we rely on monotonicity properties of these systems. Under an alternative assumption, it is shown that a classical fixed point theorem for monotone, concave operators can be applied to these systems. The required assumption is expressed in geometrical terms as an alignment (...) condition on so-called focal points . As an application, we show the existence and uniqueness of a stable periodic orbit for negative feedback loop systems in dimension 3 or more, and of a unique stable equilibrium point in dimension 2. This extends a theorem of Snoussi, which showed the existence of these orbits only. (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)

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)

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)

It is widely accepted that the way information transfers across networks depends importantly on the structure of the network. Here, we show that the mechanism of information transfer is crucial: in many respects the effect of the specific transfer mechanism swamps network effects. Results are demonstrated in terms of three different types of transfer mechanism: germs, genes, and memes. With an emphasis on the specific case of transfer between sub-networks, we explore both the dynamics of each of these (...) across networks and a measure of their comparative fitness. Germ and meme transfer exhibit very different dynamics across linked networks. For germs, measured in terms of time to total infection, network type rather than degree of linkage between sub-networks is the primary factor. For memes or belief transfer, measured in terms of time to consensus, it is the opposite: degree of linkage trumps network type in importance. The dynamics of genetic information transfer is unlike either germs or memes. Transfer of genetic information is robust across network differences to which both germs and memes prove sensitive. We also consider function: how well germ, gene, and meme transfer mechanisms can meet their respective objectives of infecting the population, mixing and transferring genetic information, and spreading a message. A shared formal measure of fitness is introduced for purposes of comparison, again with an emphasis on linked sub-networks. Meme transfer proves superior to transfer by genetic reproduction on that measure, with both memes and genes superior to infection dynamics across all networks types. What kinds of network structure optimize fitness also differ among the three. Both germs and genes show fairly stable fitness with added links between sub-networks, but genes show greater sensitivity to the structure of sub-networks at issue. Belief transfer, in contrast to the other two, shows a clear decline in fitness with increasingly connected networks. When it comes to understanding how information moves on networks, our results indicate that questions of information dynamics on networks cannot be answered in terms of networks alone. A primary role is played by the specific mechanism of information transfer at issue. We must first ask about how a particular type of information moves. (shrink)

Frequent lateral genetic transfer undermines the existence of a unique “tree of life” that relates all organisms. Vertical inheritance is nonetheless of vital interest in the study of microbial evolution, and knowing the “tree of cells” can yield insights into ecological continuity, the rates of change of different cellular characters, and the evolutionary plasticity of genomes. Notwithstanding within-species recombination, the relationships most frequently recovered from genomic data at shallow to moderate taxonomic depths are likely to reflect cellular inheritance. At the (...) same time, it is clear that several types of ‘average signals’ from whole genomes can be highly misleading, and the existence of a central tendency must not be taken as prima facie evidence of vertical descent. Phylogenetic networks offer an attractive solution, since they can be formulated in ways that mitigate the misleading aspects of hybrid evolutionary signals in genomes. But the connections in a network typically show genetic relatedness without distinguishing between vertical and lateral inheritance of genetic material. The solution may lie in a compromise between strict tree-thinking and network paradigms: build a phylogenetic network, but identify the set of connections in the network that are potentially due to vertical descent. Even if a single tree cannot be unambiguously identified, choosing a subnetwork of putative vertical connections can still lead to drastic reductions in the set of candidate vertical hypotheses. (shrink)

Like biological species, languages change over time. As noted by Darwin, there are many parallels between language evolution and biological evolution. Insights into these parallels have also undergone change in the past 150 years. Just like genes, words change over time, and language evolution can be likened to genome evolution accordingly, but what kind of evolution? There are fundamental differences between eukaryotic and prokaryotic evolution. In the former, natural variation entails the gradual accumulation of minor mutations in alleles. In the (...) latter, lateral gene transfer is an integral mechanism of natural variation. The study of language evolution using biological methods has attracted much interest of late, most approaches focusing on language tree construction. These approaches may underestimate the important role that borrowing plays in language evolution. Network approaches that were originally designed to study lateral gene transfer may provide more realistic insights into the complexities of language evolution.Editor's suggested further reading in BioEssays Linguistic evidence supports date for Homeric epics Abstract. (shrink)

Understanding the dynamics of information is crucial to many areas of research, both inside and outside of philosophy. Using computer simulations of three kinds of information, germs, genes, and memes, we show that the mechanism of information transfer often swamps network structure in terms of its effects on both the dynamics and the fitness of the information. This insight has both obvious and subtle implications for a number of questions in philosophy, including questions about the nature of information, whether (...) there is genetic information, and how to arrange scientific communities. (shrink)

NCG 4.0 is the latest update of the Network of Cancer Genes, a web-based repository of systems-level properties of cancer genes. In its current version, the database collects information on 537 known (i.e. experimentally supported) and 1463 candidate (i.e. inferred using statistical methods) cancer genes. Candidate cancer genes derive from the manual revision of 67 original publications describing the mutational screening of 3460 human exomes and genomes in 23 different cancer types. For all 2000 cancer genes, duplicability, evolutionary origin, (...) expression, functional annotation, interaction network with other human proteins and with microRNAs are reported. In addition to providing a substantial update of cancer-related information, NCG 4.0 also introduces two new features. The first is the annotation of possible false-positive cancer drivers, defined as candidate cancer genes inferred from large-scale screenings whose association with cancer is likely to be spurious. The second is the description of the systems-level properties of 64 human microRNAs that are causally involved in cancer progression (oncomiRs). Owing to the manual revision of all information, NCG 4.0 constitutes a complete and reliable resource on human coding and non-coding genes whose deregulation drives cancer onset and/or progression. NCG 4.0 can also be downloaded as a free application for Android smart phones. (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)

The dissertation explores the way that large-scale research projects in human genetics influence and are influenced by various social and political issues in contemporary U.S. society. In short, the dissertation argues that the same cultural assumptions which make research projects like the Human Genome Project and human behavioral genetics research seem like promising and worthwhile endeavors simultaneously lead to the results of these projects getting used to define the terms that various social issues are discussed in. In cases where the (...) issues involve conflicting agendas, those cultural assumptions that drive the research projects often point towards a specific form of resolution, a form that is often implicitly or explicitly supported by the results of the research projects themselves. ;There is, in other words, a complex relationship of mutual support between certain kinds of research projects in human genetics, the legal and social decisions made in various areas in political life, and the kinds of discourse that can exist around those same areas. This relationship is pernicious insofar as those assumptions that encourage the research and influence the way the research is used are assumptions that many people would question the wisdom of uncritically accepting. And indeed, they are assumptions that, I argue, have strong racist and sexist overtones, assumptions born out of a radically anti-egalitarian framework. Political decisions and social discourse that might otherwise seem radically racist, sexist, or classist can, once they are being made in the shadow of research undertaken under these same kinds of assumptions, be made to seem somehow natural, inevitable, or at the very least, scientifically well-motivated. (shrink)

In the multidisciplinary field of developmental cognitive neuroscience, statistical associations between levels of description play an increasingly important role. One example of such associations is the observation of correlations between relatively common gene variants and individual differences in behavior. It is perhaps surprising that such associations can be detected despite the remoteness of these levels of description, and the fact that behavior is the outcome of an extended developmental process involving interaction of the whole organism with a variable environment. (...) Given that they have been detected, how do such associations inform cognitive-level theories? To investigate this question, we employed a multiscale computational model of development, using a sample domain drawn from the field of language acquisition. The model comprised an artificial neural network model of past-tense acquisition trained using the backpropagation learning algorithm, extended to incorporate population modeling and genetic algorithms. It included five levels of description—four internal: genetic, network, neurocomputation, behavior; and one external: environment. Since the mechanistic assumptions of the model were known and its operation was relatively transparent, we could evaluate whether cross-level associations gave an accurate picture of causal processes. We established that associations could be detected between artificial genes and behavioral variation, even under polygenic assumptions of a many-to-one relationship between genes and neurocomputational parameters, and when an experience-dependent developmental process interceded between the action of genes and the emergence of behavior. We evaluated these associations with respect to their specificity, to their developmental stability, and to their replicability, as well as considering issues of missing heritability and gene–environment interactions. We argue that gene–behavior associations can inform cognitive theory with respect to effect size, specificity, and timing. The model demonstrates a means by which researchers can undertake multiscale modeling with respect to cognition and develop highly specific and complex hypotheses across multiple levels of description. (shrink)

Predicting the phenotype of an organism from its genotype is a central question in genetics. Most importantly, we would like to find out if the perturbation of a single gene may be the cause of a disease. However, our current ability to predict the phenotypic effects of perturbations of individual genes is limited. Network models of genes are one tool for tackling this problem. In a recent study, (Lee et al.) it has been shown that network models (...) covering the majority of genes of an organism can be used for accurately predicting phenotypic effects of gene perturbations in multicellular organisms. BioEssays 30:707–710, 2008. © 2008 Wiley Periodicals, Inc. (shrink)

Because a large number of molecular mechanisms involved in gene regulation have been described during the last decades, it is now becoming possible to address questions about the global structure of gene regulatory networks, at least in the case of some of the best-characterized organisms.This paper presents a global characterization of the transcriptional regulation in Escherichiacoli on the basis of the current data. The connectivity of the corresponding network was evaluated by analyzing the distribution of the number (...) of genes regulated by a given regulatory protein, and the distribution of the number of regulatory genes regulating a given regulated gene. The mean connectivity found (between 2 and 3) shows a rather loosely interconnected structure. Special emphasis is given to circular sequences of interactions (“circuits”) because of their critical dynamical properties. Only one-element circuits were found, in which negative autoregulation is the dominant architecture. These global properties are discussed in light of several pertinent theoretical approaches, as well as in terms of physiological and evolutionary considerations. BioEssays 20:433–440, 1998. © 1998 John Wiley & Sons Inc. (shrink)

Because a large number of molecular mechanisms involved in gene regulation have been described during the last decades, it is now becoming possible to address questions about the global structure of gene regulatory networks, at least in the case of some of the best-characterized organisms.This paper presents a global characterization of the transcriptional regulation in Escherichiacoli on the basis of the current data. The connectivity of the corresponding network was evaluated by analyzing the distribution of the number (...) of genes regulated by a given regulatory protein, and the distribution of the number of regulatory genes regulating a given regulated gene. The mean connectivity found (between 2 and 3) shows a rather loosely interconnected structure. Special emphasis is given to circular sequences of interactions (“circuits”) because of their critical dynamical properties. Only one-element circuits were found, in which negative autoregulation is the dominant architecture. These global properties are discussed in light of several pertinent theoretical approaches, as well as in terms of physiological and evolutionary considerations. BioEssays 20:433–440, 1998. © 1998 John Wiley & Sons Inc. (shrink)

Because a large number of molecular mechanisms involved in gene regulation have been described during the last decades, it is now becoming possible to address questions about the global structure of gene regulatory networks, at least in the case of some of the best-characterized organisms.This paper presents a global characterization of the transcriptional regulation in Escherichiacoli on the basis of the current data. The connectivity of the corresponding network was evaluated by analyzing the distribution of the number (...) of genes regulated by a given regulatory protein, and the distribution of the number of regulatory genes regulating a given regulated gene. The mean connectivity found (between 2 and 3) shows a rather loosely interconnected structure. Special emphasis is given to circular sequences of interactions (“circuits”) because of their critical dynamical properties. Only one-element circuits were found, in which negative autoregulation is the dominant architecture. These global properties are discussed in light of several pertinent theoretical approaches, as well as in terms of physiological and evolutionary considerations. BioEssays 20:433–440, 1998. © 1998 John Wiley & Sons Inc. (shrink)

The combination of decreased genotyping costs and prolific social media use is fueling a personal genetic testing industry in which consumers purchase and interact with genetic risk information online. Consumers and their genetic risk profiles are protected in some respects by the 2008 federal Genetic Information Nondiscrimination Act (GINA), which forbids the discriminatory use of genetic information by employers and health insurers; however, practical and technical limitations undermine its enforceability, given the everyday practices of online social networking and its impact (...) on the workplace. In the Web 2.0 era, employers in most states can legally search about job candidates and employees online, probing social networking sites for personal information that might bear on hiring and employment decisions. We examine GINA's protections for online sharing of genetic information as well as its limitations, and propose policy recommendations to address current gaps that leave employees? genetic information vulnerable in a Web-based world. (shrink)

The aberrations of a gene can influence it and the functions of its neighbour genes in gene interaction network, leading to the development of carcinogenesis of normal cells. In consideration of gene interaction network as a complex network, previous studies have made efforts on the driver attribute filling of genes via network properties of nodes and network propagation of mutations. However, there are still obstacles from problems of small size of cancer samples (...) and the existence of drivers without property of network neighbours, limiting the discovery of cancer driver genes. To address these obstacles, we propose an efficient modularity subspace based concept learning model. Our model can overcome the curse of dimensionality due to small samples via dimension reduction in the task of attribute concept learning and explore the features of genes through modularity subspace beyond the network neighbours. The evaluation analysis also demonstrates the superiority of our model in the task of driver attribute filling on two gene interaction networks. Generally, our model shows a promising prospect in the application of interaction network analysis of tumorigenesis. (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)

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.

Different sources of data on the evolution of segmentation lead to very different conclusions. Molecular similarities in the developmental pathways generating a segmented body plan tend to suggest a segmented common ancestor for all bilaterally symmetrical animals. Data from paleontology and comparative morphology suggest that this is unlikely. A possible solution to this conundrum is that throughout evolution there was a parallel co‐option of gene regulatory networks that had conserved ancestral roles in determining body axes and in elongating the (...) anterior‐posterior axis. Inherent properties in some of these networks made them easily recruitable for generating repeated patterns and for determining segmental boundaries. Phyla where this process happened are among the most successful in the animal kingdom, as the modular nature of the segmental body organization allowed them to diverge and radiate into a bewildering array of variations on a common theme. (shrink)

Gene expression network is also a type of complex network. It is challenging to analyze the gene expression network through relevant knowledge and algorithms of a complex network. In this paper, the existing characteristics of genes are analyzed from various indexes of the gene expression network to analyze key genes and TOP genes. Firstly, gene chip data are screened, gene data with obvious characteristics are selected, and relevant clustering characteristics are (...) analyzed. Then, the complex gene network structure is established, and gene networks with different threshold shapes and different sizes are selected. Finally, the relevant indexes and PR values after the PageRank algorithm are analyzed for complex networks under different thresholds, thus establishing the TOP gene and PR sequence. (shrink)

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)

Models of gene regulatory networks have proven useful for understanding many aspects of the highly complex behavior of biological control networks. Randomly generated non-Boolean networks were used in experimental simulations to generate data on dynamic phenotypes as a function of several genotypic parameters. We found that predictive relationships between some phenotypes and quantitative genotypic parameters such as number of network genes, interaction density, and initial condition could be derived depending on the strength of the topological genotype on specific (...) phenotypes. We quantitated the strength of the topological genotype effect on a number of phenotypes in multi-gene networks. For phenotypes with a low influence of topological genotype, derived and empirical relationships using quantitative genotype parameters were accurate in phenotypic outcomes. We found a number of dynamic network properties, including oscillation behaviors, that were largely dependent on genotype topology, and for which no such general quantitative relationships were determinable. It remains to be determined if these results are applicable to biological gene regulatory networks. (shrink)

Beyond belief change and meme adoption, both genetics and infection have been spoken of in terms of information transfer. What we examine here, concentrating on the specific case of transfer between sub-networks, are the differences in network dynamics in these cases: the different network dynamics of germs, genes, and memes. Germs and memes, it turns out, exhibit a very different dynamics across networks. For infection, measured in terms of time to total infection, it is network type rather (...) than degree of linkage between sub-networks that is of primary importance. For belief transfer, measured in terms of time to consensus, it is degree of linkage rather than network type that is crucial. Genes model each of these other dynamics in part, but match neither in full. For genetics, like belief transfer and unlike infection, network type makes little difference. Like infection and unlike belief, on the other hand, the dynamics of genetic information transfer within single and between linked networks are much the same. In ways both surprising and intriguing, transfer of genetic information seems to be robust across network differences crucial for the other two. (shrink)

Neuronal signalling involves multiple neuropeptides that are diverse in structure and function. Complex patterns of tissue‐specific expression arise from alternate RNA splicing of neuropeptide‐encoding gene transcripts. The pattern of expression and its role in cell signalling is diffecult to study at the level of single neurons in the complex vertebrate brain. However, in the model molluscan system, Lymnaea, it is possible to show that alternate mRNA expression of the FMRFamide gene is specific to single identified neurons. Two different (...) transcripts are expressed in a mutually exclusive manner in different neurons. Post‐translational processing of the two precursor proteins leads to completely distinct sets of neuropeptide transmitters. The function of these transmitter cocktails, resulting from alternate mRNA splicing, was studied physiologically in identified neurons forming part of a behaviourally important network regulating heartbeat. (shrink)

What is a gene? Does it represent a natural kind, or is it just a tool for genomics? A clear answer to these questions has been challenged by postgenomic discoveries. In response, I will argue that the gene can be deemed a natural kind as it satisfies some requirements for genuine kindhood. Specifically, natural kinds are projectible categories in our best scientific theories, and they represent nodes in the causal network of the world (as in Khalidi. Natural (...) Categories and Human Kinds: Classification in the Natural and Social Sciences. Cambridge University Press, Cambridge, 2013; Khalidi. Synthese 195: 1379–1396, 2018; Khalidi. Are Sexes Natural Kinds, In: Dasgupta S, Weslake B (eds) Current Controversies in Philoso-phy of Science. Routledge, New York, 2020; Khalidi. Philos Sci 88:1–21, 2021). In Sect. 2, I will present a brief history of the gene and the controversy over its status. In Sect. 3, I will introduce the account of natural kinds considered in this paper. In Sect. 4, I will first present the relevant definition of genes and how they can be classified. Then, I will argue that the gene can be considered a natural kind as it satisfies the criteria for natural kindhood. Section 5 concludes. (shrink)

This paper reports on the meeting of the Sounding Board of the EU Reprogenetics Project that was held in Budapest, Hungary, 6–9 November 2005. The Reprogenetics Project runs from 2004 until 2007 and has a brief to study the ethical aspects of human reproductive cloning and germline gene therapy. Discussions during The Budapest Meeting are reported in depth in this paper as well as the initiatives to involve the participating groups and others in ongoing collaborations with the goal of (...) forming an integrated network of European resources in the fields of ethics of science. (shrink)

The vast majority (> 95%) of single-gene mutations in yeast affect not only the expression of the mutant gene, but also the expression of many other genes. These data suggest the presence of a previously uncharacterized ‘gene expression network’—a set of interactions between genes which dictate gene expression in the native cell environment. Here, we quantitatively analyze the gene expression network revealed by microarray expression data from 273 different yeast gene deletion mutants.(1) (...) We find that gene expression interactions form a robust, error-tolerant ‘scale-free’ network, similar to metabolic pathways(2) and artificial networks such as power grids and the internet.(3-5) Because the connectivity between genes in the gene expression network is unevenly distributed, a scale-free organization helps make organisms resistant to the deleterious effects of mutation, and is thus highly adaptive. The existence of a gene expression network poses practical considerations for the study of gene function, since most mutant phenotypes are the result of changes in the expression of many genes. Using principles of scale-free network topology, we propose that fragmenting the gene expression network via ‘genome-engineering’ may be a viable and practical approach to isolating gene function. BioEssays 24:267–274, 2002. © 2002 Wiley Periodicals, Inc.; DOI 10.1002/bies.10054. (shrink)

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 reports on the meeting of the Sounding Board of the EU Reprogenetics Project that was held in Budapest, Hungary, 6–9 November 2005. The Reprogenetics Project runs from 2004 until 2007 and has a brief to study the ethical aspects of human reproductive cloning and germline gene therapy. Discussions during The Budapest Meeting are reported in depth in this paper as well as the initiatives to involve the participating groups and others in ongoing collaborations with the goal of (...) forming an integrated network of European resources in the fields of ethics of science. (shrink)

Cascades of transcriptional regulation are the common source of the forward drive in all developmental systems. Increases in complexity and specificity of gene expression at successive stages are based on the collaboration of varied combinations of transcription factors already expressed in the cells to turn on new genes, and the logical relationships between the transcription factors acting and becoming newly expressed from stage to stage are best visualized as gene regulatory networks. However, gene regulatory networks used in (...) different developmental contexts underlie processes that actually operate through different sets of rules, which affect the kinetics, synchronicity, and logical properties of individual network nodes. Contrasting early embryonic development in flies and sea urchins with adult mammalian hematopoietic development from stem cells, major differences are seen in transcription factor dosage dependence, the silencing or damping impacts of repression, and the impact of cellular regulatory history on the parts of the genome that are accessible to transcription factor action in a given cell type. These different features not only affect the kinds of models that can illuminate developmental mechanisms in the respective biological systems, but also reflect the evolutionary needs of these biological systems to optimize different aspects of development. (shrink)

In mice, dosage compensation of X‐linked gene expression is achieved through the inactivation of one of the two X‐chromosomes in XX female cells. The complex epigenetic process leading to X‐inactivation is largely controlled by Xist and Tsix, two non‐coding genes of opposing function. Xist RNA triggers X‐inactivation by coating the inactive X, while Tsix is critical for the designation of the active X‐chromosome through cis‐repression of Xist RNA accumulation. Recently, a plethora of trans‐acting factors and cis‐regulating elements have been (...) suggested to act as key regulators of either Xist, Tsix or both; these include ubiquitous factors such as Yy1 and Ctcf, developmental proteins such as Nanog, Oct4 and Sox2, and X‐linked regulators such as Rnf12. In this paper we summarise recent advances in our knowledge of the regulation of Xist and Tsix in embryonic stem (ES) and differentiating ES cells. (shrink)

Our primary interest is in determining how many gene perturbation experiments are required to determine the Various algorithms have been proposed for learning..