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

Weber G., DEFTERLİ Ö., ALPARSLAN GÖK S. Z., Kropat E.

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, vol.211, no.1, pp.1-14, 2011 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Review
  • Volume: 211 Issue: 1
  • Publication Date: 2011
  • Doi Number: 10.1016/j.ejor.2010.06.038
  • Journal Name: EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.1-14
  • Keywords: Nonlinear programming, Uncertainty modeling, Computational biology, Environment, Games, Data mining, GENE-ENVIRONMENT NETWORKS, EXPRESSION, DYNAMICS, UNCERTAINTY
  • Middle East Technical University Affiliated: Yes

Abstract

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. (C) 2010 Elsevier B.V. All rights reserved.