Biomedical subjects

Yaneer Bar-Yam

Publications and source records attributed to Yaneer Bar-Yam.

15 recordsLinked to original sources

PubMed2006

Long-range interactions and evolutionary stability in a predator-prey system.

Evolving ecosystems often are dominated by spatially local dynamics, but many also include long-range transport that mixes spatially separated groups. The existence of such mixing may be of critical importance since research shows spatial separation may be responsible for long-term stability of predator-prey systems. Complete mixing results in rapid global extinction, while spatial systems achive long term stability due to an inhomogeneous spatial pattern of local extinctions. We consider the robustness of a generic evolving predator-prey or host-pathogen model to long-range mixing and find a transition to global extinction at nontrivial values implying that even if significant mixing already exists, a small amount of additional mixing may cause extinction. Our results are relevant to the global mixing of species due to human intervention and to global transport of infectious disease.

Animals↗

PubMed2006

Improving the effectiveness of health care and public health: a multiscale complex systems analysis.

The US health care system is struggling with a mismatch between the large, simple (low-information) financial flow and the complex (high-information) treatment of individual patients. Efforts to implement cost controls and industrial efficiency that are appropriate for repetitive tasks but not high-complexity tasks lead to poor quality of care. Multiscale complex systems analysis suggests that an important step toward relieving this structural problem is a separation of responsibility for 2 distinct types of tasks: medical care of individual patients and prevention/population health. These distinct tasks require qualitatively different organizational structures. The current use of care providers and organizations for both purposes leads to compromises in organizational process that adversely affect the ability of health care organizations to provide either individual or prevention/population services. Thus, the overall system can be dramatically improved by establishing 2 separate but linked systems with distinct organizational forms: (a) a high-efficiency system performing large-scale repetitive tasks such as screening tests, inoculations, and generic health care, and (b) a high-complexity system treating complex medical problems of individual patients.

Efficiency, Organizational↗

PubMed2005

Analytically solvable model of probabilistic network dynamics.

We present a simple model of network dynamics that can be solved analytically for fully connected networks. We obtain the dynamics of response of the system to perturbations. The analytical solution is an excellent approximation for random networks. A comparison with the scale-free network, though qualitatively similar, shows the effect of distinct topology.

Journal Article↗

PubMed2005

Estimating the total genetic diversity of a spatial field population from a sample and implications of its dependence on habitat area.

The total genetic diversity of a species is a key factor in its persistence and conservation. Because realistic sample sizes are far smaller than the total population, it is impractical to exhaustively characterize diversity of most populations. Here, we demonstrate the possibility of calculating the genetic diversity of a spatial population from a sample using genealogical models. We trace the history of a population by simulating the locations of the ancestors of a particular sample of the population backwards in time. We use this method to estimate the genetic diversity of the global population of Pseudomonas bacteria. The same results are obtained whether using a global sample or a subsample restricted to a particular geographic region (California). The results are also validated by comparing additional predictions of the model to the data. Furthermore, we use these results to show that the level of genetic diversity in a population depends strongly on the size of its habitat, much more strongly than does biodiversity as measured by the number of species. The strong dependence of diversity on habitat area has significant implications for conservation strategies.

Conservation of Natural Resources↗

PubMed2005

Multiscale complexity of correlated Gaussians.

We apply a recently developed measure of multiscale complexity to the Gaussian model consisting of continuous spins with bilinear interactions for a variety of interaction matrix structures. We find two universal behaviors of the complexity profile. For systems with variables that are not frustrated, an exponential decay of multiscale complexity in the disordered regime shows the presence of small-scale fluctuations and a logarithmically diverging profile of fixed shape near the critical point describes the spectrum of collective modes. For frustrated variables, oscillations in complexity indicate the presence of global or local constraints. These observations show that the multiscale complexity may be a useful tool for interpreting the underlying structure of systems for which pair correlations can be measured.

Journal Article↗

PubMed2005

Cell fates as high-dimensional attractor states of a complex gene regulatory network.

Cells in multicellular organisms switch between distinct cell fates, such as proliferation or differentiation into specialized cell types. Genome-wide gene regulatory networks govern this behavior. Theoretical studies of complex networks suggest that they can exhibit ordered (stable) dynamics, raising the possibility that cell fates may represent high-dimensional attractor states. We used gene expression profiling to show that trajectories of neutrophil differentiation converge to a common state from different directions of a 2773-dimensional gene expression state space, providing the first experimental evidence for a high-dimensional stable attractor that represents a distinct cellular phenotype.

Cell Differentiation↗

PubMed2004

Dynamics of cellular level function and regulation derived from murine expression array data.

A major open question of systems biology is how genetic and molecular components interact to create phenotypes at the cellular level. Although much recent effort has been dedicated to inferring effective regulatory influences within small networks of genes, the power of microarray bioinformatics has yet to be used to determine functional influences at the cellular level. In all cases of data-driven parameter estimation, the number of model parameters estimable from a set of data is strictly limited by the size of that set. Rather than infer parameters describing the detailed interactions of just a few genes, we chose a larger-scale investigation so that the cumulative effects of all gene interactions could be analyzed to identify the dynamics of cellular-level function. By aggregating genes into large groups with related behaviors (megamodules), we were able to determine the effective aggregate regulatory influences among 12 major gene groups in murine B lymphocytes over a variety of time steps. Intriguing observations about the behavior of cells at this high level of abstraction include: (i) a medium-term critical global transcriptional dependence on ATP-generating genes in the mitochondria, (ii) a longer-term dependence on glycolytic genes, (iii) the dual role of chromatin-reorganizing genes in transcriptional activation and repression, (iv) homeostasis-favoring influences, (v) the indication that, as a group, G protein-mediated signals are not concentration-dependent in their influence on target gene expression, and (vi) short-term-activating/long-term-repressing behavior of the cell-cycle system that reflects its oscillatory behavior.

Animals↗

PubMed2004

Theory predicts the uneven distribution of genetic diversity within species.

Global efforts to conserve species have been strongly influenced by the heterogeneous distribution of species diversity across the Earth. This is manifest in conservation efforts focused on diversity hotspots. The conservation of genetic diversity within an individual species is an important factor in its survival in the face of environmental changes and disease. Here we show that diversity within species is also distributed unevenly. Using simple genealogical models, we show that genetic distinctiveness has a scale-free power law distribution. This property implies that a disproportionate fraction of the diversity is concentrated in small sub-populations, even when the population is well-mixed. Small groups are of such importance to overall population diversity that even without extrinsic perturbations, there are large fluctuations in diversity owing to extinctions of these small groups. We also show that diversity can be geographically non-uniform--potentially including sharp boundaries between distantly related organisms--without extrinsic causes such as barriers to gene flow or past migration events. We obtained these results by studying the fundamental scaling properties of genealogical trees. Our theoretical results agree with field data from global samples of Pseudomonas bacteria. Contrary to previous studies, our results imply that diversity loss owing to severe extinction events is high, and focusing conservation efforts on highly distinctive groups can save much of the diversity.

Animal Migration↗

PubMed2004

Information flow through a chaotic channel: prediction and postdiction at finite resolution.

We reconsider the persistence of information under the dynamics of the logistic map in order to discuss communication through a nonlinear channel where the sender can set the initial state of the system with finite resolution, and the recipient measures it with the same accuracy. We separate out the contributions of global phase-space shrinkage and local-phase space contraction and expansion to the uncertainty in predicting and postdicting the state of the system. We determine how the amplification parameter, the time lag, and the resolution influence the possibility for communication. A novel "clockwork" representation for real numbers is introduced that allows for a visualization of the flow of information between scales.

Journal Article↗

PubMed2004

The evolution of reproductive restraint through social communication.

The evolution of altruistic behavior through group selection is generally viewed as possible in theory but unlikely in reality, because individual selection favoring selfish strategies should act more rapidly than group selection favoring cooperation. Here we demonstrate the evolution of altruism, in the form of conditional reproductive restraint based on an explicitly social mechanism, modulated by intrapopulation communication comprising signal and evolved response, in a spatially distributed predatory/parasitic/pathogenic model system. The predatory species consistently comes to exploit a signal implying overcrowding, individuals constraining their reproduction in response, with a corresponding increase in equilibrium reproduction rate in the absence of signal. This signaled restraint arises in a robust way for a range of model spatial systems; it outcompetes non-signal-based restraint and is not vulnerable to subversion by noncooperating variants. In these systems, communication is used to evaluate population density and regulate reproduction accordingly, consistent with central ideas of Wynne-Edwards [Wynne-Edwards, V. C. (1962) Animal Dispersion in Relation to Social Behavior (Hafner, New York)], whose claims about the evolutionary importance of group selection helped ignite decades of controversy. This quantitative simulation model shows how the key evolutionary transition from solitary living to sociality can occur. The process described here of cooperation evolving through communication may also help to explain other major evolutionary transitions such as intercellular communication leading to multicellular organisms.

Altruism↗

PubMed2004

Response of complex networks to stimuli.

We consider the response of complex systems to stimuli and argue for the importance of both sensitivity, the possibility of large response to small stimuli, and robustness, the possibility of small response to large stimuli. Using a dynamic attractor network model for switching of patterns of behavior, we show that the scale-free topologies often found in nature enable more sensitive response to specific changes than do random networks. This property may be essential in networks where appropriate response to environmental change is critical and may, in such systems, be more important than features, such as connectivity, often used to characterize network topologies. Phenomenologically observed exponents for functional scale-free networks fall in a range corresponding to the onset of particularly high sensitivities, while still retaining robustness.

Biology↗

PubMed2004

Topology of large-scale engineering problem-solving networks.

The last few years have led to a series of discoveries that uncovered statistical properties that are common to a variety of diverse real-world social, information, biological, and technological networks. The goal of the present paper is to investigate the statistical properties of networks of people engaged in distributed problem solving and discuss their significance. We show that problem-solving networks have properties (sparseness, small world, scaling regimes) that are like those displayed by information, biological, and technological networks. More importantly, we demonstrate a previously unreported difference between the distribution of incoming and outgoing links of directed networks. Specifically, the incoming link distributions have sharp cutoffs that are substantially lower than those of the outgoing link distributions (sometimes the outgoing cutoffs are not even present). This asymmetry can be explained by considering the dynamical interactions that take place in distributed problem solving and may be related to differences between each actor's capacity to process information provided by others and the actor's capacity to transmit information over the network. We conjecture that the asymmetric link distribution is likely to hold for other human or nonhuman directed networks when nodes represent information processing and using elements.

Journal Article↗

PubMed2003

Dynamics and genealogy of strains in spatially extended host-pathogen models.

We examine the dynamics of evolution in a generic spatial model of a pathogen infecting a population of hosts, or an analogous predator-prey system. Previous studies of this model have found a range of interesting phenomena that differ from the well-mixed version. We extend these studies by examining the spatial and temporal dynamics of strains using genealogical tracing. When transmissibility can evolve by mutation, strains of intermediate transmissibility dominate even though high-transmissibility mutants have a short-term reproductive advantage. Mutant strains continually arise and grow rapidly for many generations but eventually go extinct before dominating the system. We find that, after a number of generations, the mutant pathogen characteristics strongly impact the spatial distribution of their local host environment, even when there are diverse types coexisting. Extinction is due to the depletion of susceptibles in the local environment of these mutant strains. Studies of spatial and genealogical relatedness reveal the self-organized spatial clustering of strains that enables their impact on the local environment. Thus, we find that selection acts against the high-transmissibility strains on long time-scales as a result of the feedback due to environmental change. Our study shows that averages over space or time should not be assumed to adequately describe the evolutionary dynamics of spatially distributed host-pathogen systems.

Animals↗

PubMed2003

Optimization of robustness and connectivity in complex networks.

Scale-free networks rely on a relatively small number of highly connected nodes to achieve a high degree of interconnectivity and robustness to random failure, but suffer from a high sensitivity to directed attack. In this paper we describe a parameterized family of networks and analyze their connectivity and sensitivity, identifying a network that has an interconnectedness closer to that of a scale-free network, a robustness to attack closer to that of an exponential network, and a resistance to failure better than that of either of those networks.

Models, Biological↗

PubMed2002

Spontaneous pattern formation and genetic invasion in locally mating and competing populations.

We present a theoretical model of evolution of spatially distributed populations in which organisms mate with and compete against each other only locally. We show using both analysis and numerical simulation that the typical dynamics of population density variation is a spontaneous formation of isolated groups due to competition for resources. The resulting spatial separation between groups strongly affects the process of genetic invasion by local reproductive mixing, and spatially inhomogeneous genetic distributions are possible in the final states. We then consider a specific version of this model in the presence of disruptive selection, favoring two fittest types against their genetic intermediates. This case can be simplified to a system that involves just two nonconserved order parameters: population density and type difference. Since the coexistence of two fittest types is unstable in this case, symmetry breaking and coarsening occur in type difference, implying eventual dominance by one type over another for finite populations. However, such coarsening patterns may be pinned by the spontaneously generated spatial separation between isolated groups. The long-term evolution of genetic composition is found to be sensitive to the ratio of the mating and competition ranges, and other parameters. Our model may provide a theoretical basis for consideration of various properties of spatially extended evolutionary processes, including spontaneous formation of subpopulations and lateral invasion of different types.

Journal Article↗