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Optimal Experimental Design for Gene Regulatory Networks in the Presence of Uncertainty
2015
IEEE/ACM Transactions on Computational Biology & Bioinformatics
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Based on this prioritization, one can select an optimal experiment with the largest potential to reduce the pertinent uncertainty present in the current network model. ...
In this work, we utilize the concept of mean objective cost of uncertainty (MOCU) to propose a novel framework for optimal experimental design. ...
Later, experimental design is utilized in the inference of gene regulatory networks to reduce the entropy of the network model [19] - [22] . ...
doi:10.1109/tcbb.2014.2377733
pmid:26357334
fatcat:xxzdfqwz2rgubefpppdwddnbvi
Sequential Experimental Design for Optimal Structural Intervention in Gene Regulatory Networks Based on the Mean Objective Cost of Uncertainty
2018
Cancer Informatics
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A classical approach is to maximally reduce the overall uncertainty in the model, meaning maximal entropy reduction. ...
Complex models suffer from uncertainty and experiments are needed to reduce this uncertainty. ...
Since uncertainty can be quantified via entropy, a historical approach to experimental design has been to choose an experiment that maximally reduces entropy (Lindley 1956; Raiffa et al. 1961) . ...
doi:10.1177/1176935118790247
pmid:30093796
pmcid:PMC6080085
fatcat:ruefy7ezvfdk7ne3wjhhlsn5jy
Rites of passage: requirements and standards for building kinetic models of metabolic phenotypes
2015
Current Opinion in Biotechnology
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The overarching ambition of kinetic metabolic modeling is to capture the dynamic behavior of metabolism to such an extent that systems and synthetic biology strategies can reliably be tested in silico. ...
There is a need to introduce the community-level standards that will organize and accelerate the future developments in this area. ...
The principal challenges in developing large-scale to genome-scale kinetic models remain the uncertainty and the complexity that increase with the size of the networks. ...
doi:10.1016/j.copbio.2015.08.019
pmid:26342586
fatcat:6yifc3co2nburk3rdxyr2q347u
An experimental design framework for Markovian gene regulatory networks under stationary control policy
2018
BMC Systems Biology
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In the presence of uncertainty, it is of great practical interest to develop an experimental design strategy and thereby select experiments that optimally reduce a measure of uncertainty. ...
When the network is uncertain, a Bayesian framework can be applied, where policy optimality is with respect to both the dynamical objective and the uncertainty, as characterized by a prior distribution ...
Acknowledgments The authors would like to acknowledge Texas A&M High Performance Research Computing for providing computational resources to perform simulations in this paper. ...
doi:10.1186/s12918-018-0649-8
pmid:30577732
pmcid:PMC6302376
fatcat:xa5yi766ozc6nlldxtegiiycdy
Special Issue on "Biological Networks"
2018
Processes
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Networks of coordinated interactions among biological entities govern a myriad of biological functions that span a wide range of both length and time scales—from ecosystems to individual cells, and from ...
years (e.g., the life cycle of periodical cicadas) to milliseconds (e.g., allosteric enzymeregulation[...] ...
In silico implementations of the optimal input functions show great promise in significantly reducing parametric uncertainty. ...
doi:10.3390/pr6120242
fatcat:rs67eueipvbejoocx2lofk2uau
Computer-aided whole-cell design: taking a holistic approach by integrating synthetic with systems biology
[article]
2020
arXiv
pre-print
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We show how these models could significantly aid in the design and learn phases while reducing experimental testing by presenting case studies spanning from genome minimization to cell-free systems, and ...
The possibility to describe and build in silico whole-cells offers an opportunity to develop increasingly automatized, precise and accessible computer-aided design tools and strategies throughout novel ...
We sincerely thank Dr Kathleen Sedgley for her support with the workshop organization, and Dr Thomas Gorochowski for participating in discussions. ...
arXiv:2006.02720v1
fatcat:zyv26a5mhvfxnfm2wsmcyjn5km
Biophysically motivated regulatory network inference: progress and prospects
[article]
2016
bioRxiv
pre-print
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We conclude that methods combining advances in these four categories of required effort with new genomic technologies will result in biophysically motivated dynamic genome-wide regulatory network models ...
This perspective will focus on enumerating the elements of computational strategies that, when coupled to appropriate experimental designs, can lead to accurate large-scale models of chromatin-state and ...
Uncertainty about the critical timing and rate of events here motivates the need for time series and dynamical experimental designs as uncertainty about the interactions motivates genetics and perturbation ...
doi:10.1101/051847
fatcat:3ril4ploovfbrkg7bj4pixtyt4
Biophysically Motivated Regulatory Network Inference: Progress and Prospects
2016
Human Heredity
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Large-scale network inference approaches also have several advantages with regard to experimental design: that is, we can learn things from large-scale experimental designs that we cannot from single-gene ...
We conclude that methods combining advances in these four categories of required effort with new genomic technologies will result in biophysically motivated dynamic genome-wide regulatory network models ...
Uncertainty about the critical timing and rate of events here motivates the need for time series and dynamical experimental designs as uncertainty about the interactions motivates genetics and perturbation ...
doi:10.1159/000446614
pmid:28076866
fatcat:fytq7wm6dnbwjohtlg3bs5dbr4
Systems analysis of cellular networks under uncertainty
2009
FEBS Letters
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This uncertainty impedes the development of mechanistic mathematical models to achieve a true systems-level understanding. ...
Besides the often-quoted complexity of cellular networks, the prevalence of uncertainties about components, interactions, and their quantitative features provides a largely underestimated hallmark of current ...
Thereby, they extend the analysis to dynamic features of a network, despite uncertainties in the kinetic parameters. ...
doi:10.1016/j.febslet.2009.10.074
pmid:19879267
fatcat:w74siyswzjgxjicmc5sy7sacpu
Mathematical Modeling of Plant Metabolism―From Reconstruction to Prediction
2012
Metabolites
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Here, we provide an overview of mathematical approaches to analyze plant metabolism, with experimental procedures being used to validate their output, and we discuss them in the context of establishing ...
In combination with experimental high-throughput technologies this provides a promising platform to develop in silico models which are not only able to reproduce but also to predict metabolic phenotypes ...
We would also like to thank the reviewers of this article for their constructive advice to improve its quality and coverage. ...
doi:10.3390/metabo2030553
pmid:24957647
pmcid:PMC3901217
fatcat:cbb723m4g5b3vkpf5m44lccqoe
Reverse engineering biomolecular systems using -omic data: challenges, progress and opportunities
2012
Briefings in Bioinformatics
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In addition to reviewing progress made by the community and opportunities encountered in addressing these challenges, we explore the emerging field of synthetic biology, which is an exciting approach to ...
Consequently, both data-and design-driven approaches applied to^omic data may lead to novel insights in reverse engineering biological systems that could Chang F. ...
; Georgia Cancer Coalition Distinguished Cancer Scholar Award to MD Wang, and grants 5R21DA025168-02, 1R01HG004836-01 and 4R00LM009826-03 to G. ...
doi:10.1093/bib/bbs026
pmid:22833495
pmcid:PMC3404400
fatcat:rctmpuedxbcbxh6ipuloiy4kji
Applying evolutionary computation to mitigate uncertainty in dynamically-adaptive, high-assurance middleware
2011
Journal of Internet Services and Applications
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In this paper, we explore the integration of evolutionary computation into the development and run-time support of dynamically-adaptable, high-assurance middleware. ...
In the case of high-assurance adaptive software, however, this search capability must be coupled with rigorous development tools and run-time support to ensure that the resulting systems behave in accordance ...
The authors gratefully acknowledge the other members of the Software Engineering and Network Systems Laboratory for their contributions to this work. ...
doi:10.1007/s13174-011-0049-4
fatcat:whe7s2djazdapplpm2feouqhuy
The Expanding Computational Toolbox for Engineering Microbial Phenotypes at the Genome Scale
2020
Microorganisms
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Experimental and machine learning drivers have enabled these methods to improve by leaps and bounds in both scope and accuracy. ...
However, due to many recent advances, the gap between design in biology and other engineering fields is closing. ...
Acknowledgments: We would like to thank Patrick Phaneuf and Tobias Alter for helpful comments on the manuscript.
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/microorganisms8122050
pmid:33371386
pmcid:PMC7767376
fatcat:wpqrmia4wnagjjgirkj4ceb2cy
Experimental Design via Generalized Mean Objective Cost of Uncertainty
[article]
2018
arXiv
pre-print
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MOCU-based experimental design selects an experiment to maximally reduce MOCU, thereby gaining the greatest reduction of uncertainty impacting the operational objective. ...
We then demonstrate how this new formulation includes as special cases MOCU-based experimental design methods developed for materials science and genomic networks when there is experimental error. ...
DYNAMICAL GENETIC NETWORKS In [9] , optimal objective-based experimental design is derived for networks with multiple dynamic trajectories, modeling in [9] is based on [20] . ...
arXiv:1805.01143v1
fatcat:w5j2wd7t6zestgel2yviyw7ovu
On the Limitations of Biological Knowledge
2012
Current Genomics
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Scientific knowledge is grounded in a particular epistemology and, owing to the requirements of that epistemology, possesses limitations. ...
, experimental constraints, validation, knowledge discovery, and human intellectual capacity. ...
to reflect upon the issues discussed in this paper. ...
doi:10.2174/138920212803251445
pmid:23633917
pmcid:PMC3468890
fatcat:vzhcd57lv5bu7jxvscuwoiwym4
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