[HTML][HTML] Perspective: Sloppiness and emergent theories in physics, biology, and beyond
Large scale models of physical phenomena demand the development of new statistical and
computational tools in order to be effective. Many such models are “sloppy,” ie, exhibit …
computational tools in order to be effective. Many such models are “sloppy,” ie, exhibit …
Exploring Emergent Properties in Enzymatic Reaction Networks: Design and Control of Dynamic Functional Systems
The intricate and complex features of enzymatic reaction networks (ERNs) play a key role in
the emergence and sustenance of life. Constructing such networks in vitro enables stepwise …
the emergence and sustenance of life. Constructing such networks in vitro enables stepwise …
Minimal frustration underlies the usefulness of incomplete regulatory network models in biology
Regulatory networks as large and complex as those implicated in cell-fate choice are
expected to exhibit intricate, very high-dimensional dynamics. Cell-fate choice, however, is a …
expected to exhibit intricate, very high-dimensional dynamics. Cell-fate choice, however, is a …
Microbial models for simulating soil carbon dynamics: A review
Soils store the largest amount of carbon (C) in the biosphere, and the C pool in soil is critical
to the global C balance. Numerous microbial models have been developed over the last few …
to the global C balance. Numerous microbial models have been developed over the last few …
Information geometry for multiparameter models: New perspectives on the origin of simplicity
Complex models in physics, biology, economics, and engineering are often ill-determined or
sloppy: their multiple parameters can vary over wide ranges without significant changes in …
sloppy: their multiple parameters can vary over wide ranges without significant changes in …
Driving the model to its limit: profile likelihood based model reduction
In systems biology, one of the major tasks is to tailor model complexity to information content
of the data. A useful model should describe the data and produce well-determined …
of the data. A useful model should describe the data and produce well-determined …
Human inference reflects a normative balance of complexity and accuracy
We must often infer latent properties of the world from noisy and changing observations.
Complex, probabilistic approaches to this challenge such as Bayesian inference are …
Complex, probabilistic approaches to this challenge such as Bayesian inference are …
Bridging mechanistic and phenomenological models of complex biological systems
MK Transtrum, P Qiu - PLoS computational biology, 2016 - journals.plos.org
The inherent complexity of biological systems gives rise to complicated mechanistic models
with a large number of parameters. On the other hand, the collective behavior of these …
with a large number of parameters. On the other hand, the collective behavior of these …
Equifinality, sloppiness, and emergent structures of mechanistic soil biogeochemical models
Biogeochemical models increasingly consider the microbial control of carbon cycling in soil.
The major current challenge is to validate mechanistic descriptions of microbial processes …
The major current challenge is to validate mechanistic descriptions of microbial processes …
The limitations of model-based experimental design and parameter estimation in sloppy systems
We explore the relationship among experimental design, parameter estimation, and
systematic error in sloppy models. We show that the approximate nature of mathematical …
systematic error in sloppy models. We show that the approximate nature of mathematical …