41,562 research outputs found
Evolution of a Modular Software Network
"Evolution behaves like a tinkerer" (Francois Jacob, Science, 1977). Software
systems provide a unique opportunity to understand biological processes using
concepts from network theory. The Debian GNU/Linux operating system allows us
to explore the evolution of a complex network in a novel way. The modular
design detected during its growth is based on the reuse of existing code in
order to minimize costs during programming. The increase of modularity
experienced by the system over time has not counterbalanced the increase in
incompatibilities between software packages within modules. This negative
effect is far from being a failure of design. A random process of package
installation shows that the higher the modularity the larger the fraction of
packages working properly in a local computer. The decrease in the relative
number of conflicts between packages from different modules avoids a failure in
the functionality of one package spreading throughout the entire system. Some
potential analogies with the evolutionary and ecological processes determining
the structure of ecological networks of interacting species are discussed.Comment: To appear in PNA
The Emergence of Canalization and Evolvability in an Open-Ended, Interactive Evolutionary System
Natural evolution has produced a tremendous diversity of functional
organisms. Many believe an essential component of this process was the
evolution of evolvability, whereby evolution speeds up its ability to innovate
by generating a more adaptive pool of offspring. One hypothesized mechanism for
evolvability is developmental canalization, wherein certain dimensions of
variation become more likely to be traversed and others are prevented from
being explored (e.g. offspring tend to have similarly sized legs, and mutations
affect the length of both legs, not each leg individually). While ubiquitous in
nature, canalization almost never evolves in computational simulations of
evolution. Not only does that deprive us of in silico models in which to study
the evolution of evolvability, but it also raises the question of which
conditions give rise to this form of evolvability. Answering this question
would shed light on why such evolvability emerged naturally and could
accelerate engineering efforts to harness evolution to solve important
engineering challenges. In this paper we reveal a unique system in which
canalization did emerge in computational evolution. We document that genomes
entrench certain dimensions of variation that were frequently explored during
their evolutionary history. The genetic representation of these organisms also
evolved to be highly modular and hierarchical, and we show that these
organizational properties correlate with increased fitness. Interestingly, the
type of computational evolutionary experiment that produced this evolvability
was very different from traditional digital evolution in that there was no
objective, suggesting that open-ended, divergent evolutionary processes may be
necessary for the evolution of evolvability.Comment: SI can be found at: http://www.evolvingai.org/files/SI_0.zi
Quasispecies Theory for Evolution of Modularity
Biological systems are modular, and this modularity evolves over time and in
different environments. A number of observations have been made of increased
modularity in biological systems under increased environmental pressure. We
here develop a quasispecies theory for the dynamics of modularity in
populations of these systems. We show how the steady-state fitness in a
randomly changing environment can be computed. We derive a fluctuation
dissipation relation for the rate of change of modularity and use it to derive
a relationship between rate of environmental changes and rate of growth of
modularity. We also find a principle of least action for the evolved modularity
at steady state. Finally, we compare our predictions to simulations of protein
evolution and find them to be consistent.Comment: 21 pages, 4 figures; presentation reordered; to appear in Phys. Rev.
Modularity Enhances the Rate of Evolution in a Rugged Fitness Landscape
Biological systems are modular, and this modularity affects the evolution of
biological systems over time and in different environments. We here develop a
theory for the dynamics of evolution in a rugged, modular fitness landscape. We
show analytically how horizontal gene transfer couples to the modularity in the
system and leads to more rapid rates of evolution at short times. The model, in
general, analytically demonstrates a selective pressure for the prevalence of
modularity in biology. We use this model to show how the evolution of the
influenza virus is affected by the modularity of the proteins that are
recognized by the human immune system. Approximately 25\% of the observed rate
of fitness increase of the virus could be ascribed to a modular viral
landscape.Comment: 45 pages; 7 figure
Development of modularity in the neural activity of children's brains
We study how modularity of the human brain changes as children develop into
adults. Theory suggests that modularity can enhance the response function of a
networked system subject to changing external stimuli. Thus, greater cognitive
performance might be achieved for more modular neural activity, and modularity
might likely increase as children develop. The value of modularity calculated
from fMRI data is observed to increase during childhood development and peak in
young adulthood. Head motion is deconvolved from the fMRI data, and it is shown
that the dependence of modularity on age is independent of the magnitude of
head motion. A model is presented to illustrate how modularity can provide
greater cognitive performance at short times, i.e.\ task switching. A fitness
function is extracted from the model. Quasispecies theory is used to predict
how the average modularity evolves with age, illustrating the increase of
modularity during development from children to adults that arises from
selection for rapid cognitive function in young adults. Experiments exploring
the effect of modularity on cognitive performance are suggested. Modularity may
be a potential biomarker for injury, rehabilitation, or disease.Comment: 29 pages, 11 figure
Crosstalk and the Dynamical Modularity of Feed-Forward Loops in Transcriptional Regulatory Networks
Network motifs, such as the feed-forward loop (FFL), introduce a range of complex behaviors to transcriptional regulatory networks, yet such properties are typically determined from their isolated study. We characterize the effects of crosstalk on FFL dynamics by modeling the cross regulation between two different FFLs and evaluate the extent to which these patterns occur in vivo. Analytical modeling suggests that crosstalk should overwhelmingly affect individual protein-expression dynamics. Counter to this expectation we find that entire FFLs are more likely than expected to resist the effects of crosstalk (approximate to 20% for one crosstalk interaction) and remain dynamically modular. The likelihood that cross-linked FFLs are dynamically correlated increases monotonically with additional crosstalk, but is independent of the specific regulation type or connectivity of the interactions. Just one additional regulatory interaction is sufficient to drive the FFL dynamics to a statistically different state. Despite the potential for modularity between sparsely connected network motifs, Escherichia coli (E. coli) appears to favor crosstalk wherein at least one of the cross-linked FFLs remains modular. A gene ontology analysis reveals that stress response processes are significantly overrepresented in the cross-linked motifs found within E. coli. Although the daunting complexity of biological networks affects the dynamical properties of individual network motifs, some resist and remain modular, seemingly insulated from extrinsic perturbations-an intriguing possibility for nature to consistently and reliably provide certain network functionalities wherever the need arise
Dynamic reconfiguration of human brain networks during learning
Human learning is a complex phenomenon requiring flexibility to adapt
existing brain function and precision in selecting new neurophysiological
activities to drive desired behavior. These two attributes -- flexibility and
selection -- must operate over multiple temporal scales as performance of a
skill changes from being slow and challenging to being fast and automatic. Such
selective adaptability is naturally provided by modular structure, which plays
a critical role in evolution, development, and optimal network function. Using
functional connectivity measurements of brain activity acquired from initial
training through mastery of a simple motor skill, we explore the role of
modularity in human learning by identifying dynamic changes of modular
organization spanning multiple temporal scales. Our results indicate that
flexibility, which we measure by the allegiance of nodes to modules, in one
experimental session predicts the relative amount of learning in a future
session. We also develop a general statistical framework for the identification
of modular architectures in evolving systems, which is broadly applicable to
disciplines where network adaptability is crucial to the understanding of
system performance.Comment: Main Text: 19 pages, 4 figures Supplementary Materials: 34 pages, 4
figures, 3 table
Modular knowledge systems accelerate human migration in asymmetric random environments
Migration is a key mechanism for expansion of communities. In spatially
heterogeneous environments, rapidly gaining knowledge about the local
environment is key to the evolutionary success of a migrating population. For
historical human migration, environmental heterogeneity was naturally
asymmetric in the north-south (NS) and east-west (EW) directions. We here
consider the human migration process in the Americas, modeled as random,
asymmetric, modularly correlated environments. Knowledge about the environments
determines the fitness of each individual. We present a phase diagram for
asymmetry of migration as a function of carrying capacity and fitness
threshold. We find that the speed of migration is proportional to the inverse
complement of the spatial environmental gradient, and in particular we find
that north-south migration rates are lower than east-west migration rates when
the environmental gradient is higher in the north-south direction.
Communication of knowledge between individuals can help to spread beneficial
knowledge within the population. The speed of migration increases when
communication transmits pieces of knowledge that contribute in a modular way to
the fitness of individuals. The results for the dependence of migration rate on
asymmetry and modularity are consistent with existing archaeological
observations. The results for asymmetry of genetic divergence are consistent
with patterns of human gene flow.Comment: 13 pages, 6 figures, 1 table in Proc. Roy. Soc. Interface 201
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