Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
A New Mathematical Approach in Environmental and Life Sciences: Gene-Environment Networks and Their Dynamics
Date
2009-04-01
Author
Weber, Gerhard Wilhelm
Alparslan-Gok, S. Z.
Soyler, B.
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
230
views
0
downloads
Cite This
An important research area in life sciences is devoted to modeling, prediction, and dynamics of gene-expression patterns. As clearly understood in these days, this enterprise cannot become satisfactory without acknowledging the role of the environment. To a representation of past, present, and most likely future states, we also encounter measurement errors and uncertainties. This paper surveys and improves recent advances in understanding the foundations and interdisciplinary implications of the newly introduced gene-environment networks, and it integrates the important theme of carbon dioxide emission reduction into the networks and dynamics. We also introduce some operational and managerial issues of practical working and decision making, expressed in terms of sliding windows, quadrants (modules) of parametric effects, and navigating (controlling) between such effects and directing them. Given data from DNA microarray experiments and environmental records, we extract nonlinear ordinary differential equations that contain parameters that have to be determined. For this, we employ modern (Chebychevian) approximation and (generalized semi-infinite) optimization. After this is provided, time- discretized dynamical systems are studied. A combinatorial algorithm with polyhedra sequences allows to detect the region of parametric stability. Finally, we analyze the topological landscape of gene-environment networks with its structural (in)stability. By embedding as a module and investigating CO2 emission control and figuring out game theoretical aspects, we conclude. This pioneering work is theoretically elaborated, practically devoted to health care, medicine, education, living conditions, and environmental protection, and it invites the readers to future research.
Subject Keywords
General Environmental Science
URI
https://hdl.handle.net/11511/56743
Journal
ENVIRONMENTAL MODELING & ASSESSMENT
DOI
https://doi.org/10.1007/s10666-007-9137-z
Collections
Graduate School of Applied Mathematics, Article
Suggestions
OpenMETU
Core
Modeling building height errors in 3D urban environments
Özge, Ergin; Düzgün, H. Şebnem; Department of Geodetic and Geographical Information Technologies (2007)
A great interest in 3-D modeling in Geographic Information Technologies (GIS) has emerged in recent years, because many GIS related implementations, ranging from urban area design to environmental analysis require 3-D models. Especially the need for 3-D models is quite urgent in urban areas. However, numerous applications in GIS only represent two-dimensional information. The GIS community has been struggling with solving complex problems dealing with 3-D objects using a 2-D approach. This research focused ...
An algorithmic approach to analyse genetic networks and biological energy production: an introduction and contribution where OR meets biology
Uğur, Ömür; WEBER, G. -W.; WUENSCHIERS, R. (2009-01-01)
An emerging research area in computational biology and biotechnology is devoted to modelling and prediction of gene-expression patterns. In this article, after a short review of recent achievements we deepen and extend them, especially, by emphasizing and analysing the elegant means of matrix algebra. Based on experimental data, ordinary differential equations with nonlinearities on the right-hand side and a generalized treatment of the absolute shift term, representing the environmental effects, are invest...
A Review on Data Mining and Continuous Optimization Applications in Computational Biology and Medicine
Weber, Gerhard Wilhelm; Ozogur-Akyuz, Sureyya; Kropat, Erik (2009-06-01)
An emerging research area in computational biology and biotechnology is devoted to mathematical modeling and prediction of gene-expression patterns; it nowadays requests mathematics to deeply understand its foundations. This article surveys data mining and machine learning methods for an analysis of complex systems in computational biology, It mathematically deepens recent advances in modeling and prediction by rigorously introducing the environment and aspects of errors and uncertainty into the genetic con...
A review on modeling and simulation of quenching
Şimşir, Caner; Gür, Cemil Hakan (ASTM International, 2009-02-01)
Modeling and simulation of quenching are powerful tools in the design, optimization, and understanding of the quenching process since they provide quantitative results such as the evolution of microstructure and the internal stresses, which are practically impossible to acquire experimentally. The research on simulation of quenching and related phenomena originates from the early 70s and is still an active field owing to its industrial and scientific output. This paper aims to provide a comprehensive review...
On optimization, dynamics and uncertainty: A tutorial for gene-environment networks
WEBER, G. -W.; Uğur, Ömür; Taylan, P.; TEZEL, AYSUN (2009-05-28)
An emerging research area in computational biology and biotechnology is devoted to mathematical modeling and prediction of gene-expression patterns; to fully understand its foundations requires a mathematical study. This paper surveys and mathematically expands recent advances in modeling and prediction by rigorously introducing the environment and aspects of errors and uncertainty into the genetic context within the framework of matrix and interval arithmetic. Given the data from DNA microarray experiments...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
G. W. Weber, S. Z. Alparslan-Gok, and B. Soyler, “A New Mathematical Approach in Environmental and Life Sciences: Gene-Environment Networks and Their Dynamics,”
ENVIRONMENTAL MODELING & ASSESSMENT
, pp. 267–288, 2009, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/56743.