354 research outputs found
Some notes on the problem of uncertainty in biological measurements
Problems of measurement and instrumentation in biolog
A window in time for the first evolutionary radiation
The window in time between the last globally sterilizing event and the evidence for a complex procaryotic ecosystem is quite narrow, perhaps as small as 200 million years. We will present a heuristic model outlining the first evolutionary radiation that could have led from primordial vesicles to the universal ancestor. The concept of the universal ancestor will be developed in terms of contemporary molecular biology
The thermodynamic dual structure of linear-dissipative driven systems
The spontaneous emergence of dynamical order, such as persistent currents, is
sometimes argued to require principles beyond the entropy maximization of the
second law of thermodynamics. I show that, for linear dissipation in the
Onsager regime, current formation can be driven by exactly the Jaynesian
principle of entropy maximization, suitably formulated for extended systems and
nonequilibrium boundary conditions. The Legendre dual structure of equilibrium
thermodynamics is also preserved, though it requires the admission of
current-valued state variables, and their correct incorporation in the entropy
Proceedings of the 2014 A.S.P.E.N. Research Workshop
Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/141886/1/jpen0167.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/141886/2/jpen0167-sup-0001.pd
The compositional and evolutionary logic of metabolism
Metabolism displays striking and robust regularities in the forms of
modularity and hierarchy, whose composition may be compactly described. This
renders metabolic architecture comprehensible as a system, and suggests the
order in which layers of that system emerged. Metabolism also serves as the
foundation in other hierarchies, at least up to cellular integration including
bioenergetics and molecular replication, and trophic ecology. The
recapitulation of patterns first seen in metabolism, in these higher levels,
suggests metabolism as a source of causation or constraint on many forms of
organization in the biosphere.
We identify as modules widely reused subsets of chemicals, reactions, or
functions, each with a conserved internal structure. At the small molecule
substrate level, module boundaries are generally associated with the most
complex reaction mechanisms and the most conserved enzymes. Cofactors form a
structurally and functionally distinctive control layer over the small-molecule
substrate. Complex cofactors are often used at module boundaries of the
substrate level, while simpler ones participate in widely used reactions.
Cofactor functions thus act as "keys" that incorporate classes of organic
reactions within biochemistry.
The same modules that organize the compositional diversity of metabolism are
argued to have governed long-term evolution. Early evolution of core
metabolism, especially carbon-fixation, appears to have required few
innovations among a small number of conserved modules, to produce adaptations
to simple biogeochemical changes of environment. We demonstrate these features
of metabolism at several levels of hierarchy, beginning with the small-molecule
substrate and network architecture, continuing with cofactors and key conserved
reactions, and culminating in the aggregation of multiple diverse physical and
biochemical processes in cells.Comment: 56 pages, 28 figure
Unified analysis of terminal-time control in classical and quantum systems
Many phenomena in physics, chemistry, and biology involve seeking an optimal
control to maximize an objective for a classical or quantum system which is
open and interacting with its environment. The complexity of finding an optimal
control for maximizing an objective is strongly affected by the possible
existence of sub-optimal maxima. Within a unified framework under specified
conditions, control objectives for maximizing at a terminal time physical
observables of open classical and quantum systems are shown to be inherently
free of sub-optimal maxima. This attractive feature is of central importance
for enabling the discovery of controls in a seamless fashion in a wide range of
phenomena transcending the quantum and classical regimes.Comment: 10 page
Signatures of arithmetic simplicity in metabolic network architecture
Metabolic networks perform some of the most fundamental functions in living
cells, including energy transduction and building block biosynthesis. While
these are the best characterized networks in living systems, understanding
their evolutionary history and complex wiring constitutes one of the most
fascinating open questions in biology, intimately related to the enigma of
life's origin itself. Is the evolution of metabolism subject to general
principles, beyond the unpredictable accumulation of multiple historical
accidents? Here we search for such principles by applying to an artificial
chemical universe some of the methodologies developed for the study of genome
scale models of cellular metabolism. In particular, we use metabolic flux
constraint-based models to exhaustively search for artificial chemistry
pathways that can optimally perform an array of elementary metabolic functions.
Despite the simplicity of the model employed, we find that the ensuing pathways
display a surprisingly rich set of properties, including the existence of
autocatalytic cycles and hierarchical modules, the appearance of universally
preferable metabolites and reactions, and a logarithmic trend of pathway length
as a function of input/output molecule size. Some of these properties can be
derived analytically, borrowing methods previously used in cryptography. In
addition, by mapping biochemical networks onto a simplified carbon atom
reaction backbone, we find that several of the properties predicted by the
artificial chemistry model hold for real metabolic networks. These findings
suggest that optimality principles and arithmetic simplicity might lie beneath
some aspects of biochemical complexity
Ecosystem biogeochemistry considered as a distributed metabolic network ordered by maximum entropy production
Author Posting. © The Author(s), 2009. This is the author's version of the work. It is posted here by permission of The Royal Society for personal use, not for redistribution. The definitive version was published in Philosophical Transactions of the Royal Society B 365 (2010): 1417-1427, doi:10.1098/rstb.2009.0272.We examine the application of the maximum entropy production principle for describing ecosystem biogeochemistry. Since ecosystems can be functionally stable despite changes in species composition, we utilize a distributed metabolic network for describing biogeochemistry, which synthesizes generic biological structures that catalyze reaction pathways, but is otherwise organism independent. Allocation of biological structure and regulation of biogeochemical reactions is determined via solution of an optimal control problem in which entropy production is maximized. However, because synthesis of biological structures cannot occur if entropy production is maximized instantaneously, we propose that information stored within the metagenome allows biological systems to maximize entropy production when averaged over time. This differs from abiotic systems that maximize entropy production at a point in space-time, which we refer to as the steepest descent pathway. It is the spatiotemporal averaging that allows biological systems to outperform abiotic processes in entropy production, at least in many situations. A simulation of a methanotrophic system is used to demonstrate the approach. We conclude with a brief discussion on the implications of viewing ecosystems as self organizing molecular machines that function to maximize entropy production at the ecosystem level of organization.The work presented here was funded by the PIE-LTER program (NSF OCE-0423565), as well as from NSF CBET-0756562, NSF EF-0928742 and NASA Exobiology and Evolutionary Biology (NNG05GN61G)
Multistability and metastability: understanding dynamic coordination in the brain
Multistable coordination dynamics exists at many levels, from multifunctional neural circuits in vertebrates and invertebrates to large-scale neural circuitry in humans. Moreover, multistability spans (at least) the domains of action and perception, and has been found to place constraints upon, even dictating the nature of, intentional change and the skill-learning process. This paper reviews some of the key evidence for multistability in the aforementioned areas, and illustrates how it has been measured, modelled and theoretically understood. It then suggests how multistability—when combined with essential aspects of coordination dynamics such as instability, transitions and (especially) metastability—provides a platform for understanding coupling and the creative dynamics of complex goal-directed systems, including the brain and the brain–behaviour relation
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