652 research outputs found
Diffusion, dimensionality and noise in transcriptional regulation
The precision of biochemical signaling is limited by randomness in the
diffusive arrival of molecules at their targets. For proteins binding to the
specific sites on the DNA and regulating transcription, the ability of the
proteins to diffuse in one dimension by sliding along the length of the DNA, in
addition to their diffusion in bulk solution, would seem to generate a larger
target for DNA binding, consequently reducing the noise in the occupancy of the
regulatory site. Here we show that this effect is largely cancelled by the
enhanced temporal correlations in one dimensional diffusion. With realistic
parameters, sliding along DNA has surprisingly little effect on the physical
limits to the precision of transcriptional regulation.Comment: 8 pages, 2 figure
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Dynamic Long-Term Modelling of Generation Capacity Investment and Capacity Margins: a GB Market Case Study
Many governments who preside over liberalised energy markets are developing policies aimed at promoting investment in renewable generation whilst maintaining the level of security of supply customers have come to expect. Of particular interest is the mix and amount of generation investment over time in response to policies promoting high penetrations of variable output renewable power such as wind. Modelling the dynamics of merchant generation investment in market environments can inform the debate. Such models need improved methods to calculate expected output, costs and revenue of thermal generation subject to varying load and random independent thermal outages in a power system with high penetrations of wind. This paper presents a dynamic simulation model of the aggregated Great Britain (GB) generation investment market. The short-term energy market is simulated using probabilistic production costing based on the Mix of Normals distribution technique with a residual load calculation (load net of wind output). Price mark-ups due to market power are accounted for. These models are embedded in a dynamic model in which generation companies use a Value at Risk (VaR) criterion for investment decisions. An `energy-only' market setting is used to estimate the economic profitability of investments and forecast the evolution of security of supply. Simulated results for the GB market case study show a pattern of increased relative security of supply risk during the 2020s. In addition, fixed cost recovery for many new investments can only occur during years in which more frequent supply shortages push energy prices higher. A sensitivity analyses on a number of key model assumptions provides insight into factors affecting the simulated timing and level of generation investment. This is achieved by considering the relative change in simulated levels of security of supply risk metric such as de-rated capacity margins and expected energy unserved. The model can be used as a decision support tool in policy design, in particular how to address the increased `energy-only market revenue risk facing thermal generation, particularly peaking units, that rely on a small number of high price periods to recover fixed costs and make adequate returns on investment
Enhancement of the stability of genetic switches by overlapping upstream regulatory domains
We study genetic switches formed from pairs of mutually repressing operons.
The switch stability is characterised by a well defined lifetime which grows
sub-exponentially with the number of copies of the most-expressed transcription
factor, in the regime accessible by our numerical simulations. The stability
can be markedly enhanced by a suitable choice of overlap between the upstream
regulatory domains. Our results suggest that robustness against biochemical
noise can provide a selection pressure that drives operons, that regulate each
other, together in the course of evolution.Comment: 4 pages, 5 figures, RevTeX
The moral foreign language effect is stable across presentation modalities
YesPeoples’ judgments and decisions often change when made in their foreign language. Existing
research testing this foreign language effect has predominantly used text-based stimuli with little
research focusing on the impact of listening to audio stimuli on the effect. The only existing study on
this topic found shifts in people’s moral decisions only in the audio modality. Firstly, by reanalyzing
the data from this previous study and by collecting data in an additional experiment, we found no
consistent effects of using foreign language on moral judgments. Secondly, in both datasets we
found no significant language by modality interaction. Overall, our results highlight the need for
more robust testing of the foreign language effect, and its boundary conditions. However, modality
of presentation does not appear to be a candidate for explaining its variability. Data and materials for
this experiment are available at https://osf.io/qbjxn/
Entropy and information in neural spike trains: Progress on the sampling problem
The major problem in information theoretic analysis of neural responses and
other biological data is the reliable estimation of entropy--like quantities
from small samples. We apply a recently introduced Bayesian entropy estimator
to synthetic data inspired by experiments, and to real experimental spike
trains. The estimator performs admirably even very deep in the undersampled
regime, where other techniques fail. This opens new possibilities for the
information theoretic analysis of experiments, and may be of general interest
as an example of learning from limited data.Comment: 7 pages, 4 figures; referee suggested changes, accepted versio
Thermodynamics of natural images
The scale invariance of natural images suggests an analogy to the statistical
mechanics of physical systems at a critical point. Here we examine the
distribution of pixels in small image patches and show how to construct the
corresponding thermodynamics. We find evidence for criticality in a diverging
specific heat, which corresponds to large fluctuations in how "surprising" we
find individual images, and in the quantitative form of the entropy vs. energy.
The energy landscape derived from our thermodynamic framework identifies
special image configurations that have intrinsic error correcting properties,
and neurons which could detect these features have a strong resemblance to the
cells found in primary visual cortex
Studying dark energy with galaxy cluster surveys
Galaxy cluster surveys provide a powerful means of studying the density and nature of the dark energy. The redshift distribution of detected clusters in a deep, large solid angle SZE or X-ray survey is highly sensitive to the dark energy equation of state. Accurate constraints at the 5% level on the dark energy equation of state require that systematic biases in the mass estimators must be controlled at better than the similar to10% level. Observed regularity in the cluster population and the availability of multiple, independent mass estimators suggests these precise measurements are possible. Using hydrodynamical simulations that include preheating, we show that the level of preheating required to explain local galaxy cluster structure has a dramatic effect on X-ray cluster surveys, but only a mild effect on SZE surveys. This suggests that SZE surveys may be optimal for cosmology while X-ray surveys are well suited for studies of the thermal history of the intracluster medium.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/60610/1/Mohr2002Studying.pd
Optimizing information flow in small genetic networks. I
In order to survive, reproduce and (in multicellular organisms)
differentiate, cells must control the concentrations of the myriad different
proteins that are encoded in the genome. The precision of this control is
limited by the inevitable randomness of individual molecular events. Here we
explore how cells can maximize their control power in the presence of these
physical limits; formally, we solve the theoretical problem of maximizing the
information transferred from inputs to outputs when the number of available
molecules is held fixed. We start with the simplest version of the problem, in
which a single transcription factor protein controls the readout of one or more
genes by binding to DNA. We further simplify by assuming that this regulatory
network operates in steady state, that the noise is small relative to the
available dynamic range, and that the target genes do not interact. Even in
this simple limit, we find a surprisingly rich set of optimal solutions.
Importantly, for each locally optimal regulatory network, all parameters are
determined once the physical constraints on the number of available molecules
are specified. Although we are solving an over--simplified version of the
problem facing real cells, we see parallels between the structure of these
optimal solutions and the behavior of actual genetic regulatory networks.
Subsequent papers will discuss more complete versions of the problem
Optimizing information flow in small genetic networks. II: Feed forward interactions
Central to the functioning of a living cell is its ability to control the
readout or expression of information encoded in the genome. In many cases, a
single transcription factor protein activates or represses the expression of
many genes. As the concentration of the transcription factor varies, the target
genes thus undergo correlated changes, and this redundancy limits the ability
of the cell to transmit information about input signals. We explore how
interactions among the target genes can reduce this redundancy and optimize
information transmission. Our discussion builds on recent work [Tkacik et al,
Phys Rev E 80, 031920 (2009)], and there are connections to much earlier work
on the role of lateral inhibition in enhancing the efficiency of information
transmission in neural circuits; for simplicity we consider here the case where
the interactions have a feed forward structure, with no loops. Even with this
limitation, the networks that optimize information transmission have a
structure reminiscent of the networks found in real biological systems
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