Modeling, inference and optimization of regulatory networks based on time series data

In this survey paper, we present advances achieved during the last years in the development and use of OR, in particular, optimization methods in the new gene-environment and eco-finance networks, based on usually finite data series, with an emphasis on uncertainty in them and in the interactions of...

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Bibliographic Details
Published in:European journal of operational research 2011-05, Vol.211 (1), p.1-14
Main Authors: Weber, Gerhard-Wilhelm, Defterli, Ozlem, Alparslan Gök, Sırma Zeynep, Kropat, Erik
Format: Article
Language:English
Subjects:
Applied sciences
Biological and medical sciences
Computational biology
Computer science
control theory
systems
Data mining
Data processing. List processing. Character string processing
Environment
Estimates
Exact sciences and technology
Fundamental and applied biological sciences. Psychology
Games
General aspects
Inference
Mathematical models
Mathematical programming
Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects)
Memory organisation. Data processing
Networks
Nonlinear programming
Nonlinear programming Uncertainty modeling Computational biology Environment Games Data mining
Operational research
Operations research
Optimization
Optimization techniques
Parameter estimation
Preprocessing
Software
Studies
Time series
Uncertainty
Uncertainty modeling
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Summary:In this survey paper, we present advances achieved during the last years in the development and use of OR, in particular, optimization methods in the new gene-environment and eco-finance networks, based on usually finite data series, with an emphasis on uncertainty in them and in the interactions of the model items. Indeed, our networks represent models in the form of time-continuous and time-discrete dynamics, whose unknown parameters we estimate under constraints on complexity and regularization by various kinds of optimization techniques, ranging from linear, mixed-integer, spline, semi-infinite and robust optimization to conic, e.g., semi-definite programming. We present different kinds of uncertainties and a new time-discretization technique, address aspects of data preprocessing and of stability, related aspects from game theory and financial mathematics, we work out structural frontiers and discuss chances for future research and OR application in our real world.
ISSN:0377-2217
1872-6860
DOI:10.1016/j.ejor.2010.06.038