{"title":"Editorial: Structure, Dynamics and Function - Dynamical Properties of Large Bio-Molecular Networks","authors":"A. Fuente","doi":"10.2174/1875036201104010001","DOIUrl":null,"url":null,"abstract":"Bio-molecular systems consist of tens of thousands of molecular species of different chemical nature. These systems have been described as networks, such as metabolic networks [1, 2], protein-interaction networks [3], and transcriptional regulatory networks [4]. The nodes in these networks represent bio-molecular species (e.g. metabolites, proteins, RNAs) and the edges represent functional, causal or physical interactions between the nodes. The abstract representation of bio-molecular regulatory systems as networks is fruitful because it provides the ability to study the systems as a whole while ignoring many irrelevant details [5, 6]. All chemistry and physics is removed (or considered only implicitly) in order to concentrate on the essence of the system: the 'wiring scheme'. As for all abstractions of natural systems, we are doomed to lose some information when we represent bio-molecular regulatory systems as networks [6-8]. Large bio-molecular network have been subjected extensively to topological analysis for over a decade now. Many interesting topological features have been identified and their potential functions have been proposed [5, 6]. However, relating the structure of large bio-molecular network to dynamics and function is still a largely unexplored subject. Studies on dynamical properties have mostly been restricted to very small bio-molecular networks, due to the limited amount of quantitative data. Fortunately, several studies have shown that even without detailed quantitative knowledge, much can still be learned about the dynamical properties of large bio-molecular networks [9-13]. This special issue provides a recent update of the current state of art in relating structure to dynamics applied to large bio-molecular networks. The goal of the studies reviewed in this special issue is not to study the dynamics of any specific bio-molecular network, but rather to identify topological patterns which imply the possibility of certain dynamical/functional behaviors. By no means can we definitely state that 'structure determines function' as networks with the same structure could display distinct dynamics depending on their parameter values (for instance the strength or signs of interactions). Networks could for instance display oscillations or reach a stable steady state depending on the specific model parameters. To be able to characterize the true behavior of bio-molecular networks we need the quantitative information of all the parameters. Experimental identification of the large numbers of parameters is currently infeasible, even with modern high throughput techniques. Nevertheless, we can still learn much about dynamics from topology alone. Inspection of the network topology can immediately exclude certain dynamical behaviors completely …","PeriodicalId":38956,"journal":{"name":"Open Bioinformatics Journal","volume":"5 1","pages":"1-3"},"PeriodicalIF":0.0000,"publicationDate":"2011-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Open Bioinformatics Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2174/1875036201104010001","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Computer Science","Score":null,"Total":0}
引用次数: 0
Abstract
Bio-molecular systems consist of tens of thousands of molecular species of different chemical nature. These systems have been described as networks, such as metabolic networks [1, 2], protein-interaction networks [3], and transcriptional regulatory networks [4]. The nodes in these networks represent bio-molecular species (e.g. metabolites, proteins, RNAs) and the edges represent functional, causal or physical interactions between the nodes. The abstract representation of bio-molecular regulatory systems as networks is fruitful because it provides the ability to study the systems as a whole while ignoring many irrelevant details [5, 6]. All chemistry and physics is removed (or considered only implicitly) in order to concentrate on the essence of the system: the 'wiring scheme'. As for all abstractions of natural systems, we are doomed to lose some information when we represent bio-molecular regulatory systems as networks [6-8]. Large bio-molecular network have been subjected extensively to topological analysis for over a decade now. Many interesting topological features have been identified and their potential functions have been proposed [5, 6]. However, relating the structure of large bio-molecular network to dynamics and function is still a largely unexplored subject. Studies on dynamical properties have mostly been restricted to very small bio-molecular networks, due to the limited amount of quantitative data. Fortunately, several studies have shown that even without detailed quantitative knowledge, much can still be learned about the dynamical properties of large bio-molecular networks [9-13]. This special issue provides a recent update of the current state of art in relating structure to dynamics applied to large bio-molecular networks. The goal of the studies reviewed in this special issue is not to study the dynamics of any specific bio-molecular network, but rather to identify topological patterns which imply the possibility of certain dynamical/functional behaviors. By no means can we definitely state that 'structure determines function' as networks with the same structure could display distinct dynamics depending on their parameter values (for instance the strength or signs of interactions). Networks could for instance display oscillations or reach a stable steady state depending on the specific model parameters. To be able to characterize the true behavior of bio-molecular networks we need the quantitative information of all the parameters. Experimental identification of the large numbers of parameters is currently infeasible, even with modern high throughput techniques. Nevertheless, we can still learn much about dynamics from topology alone. Inspection of the network topology can immediately exclude certain dynamical behaviors completely …
期刊介绍:
The Open Bioinformatics Journal is an Open Access online journal, which publishes research articles, reviews/mini-reviews, letters, clinical trial studies and guest edited single topic issues in all areas of bioinformatics and computational biology. The coverage includes biomedicine, focusing on large data acquisition, analysis and curation, computational and statistical methods for the modeling and analysis of biological data, and descriptions of new algorithms and databases. The Open Bioinformatics Journal, a peer reviewed journal, is an important and reliable source of current information on the developments in the field. The emphasis will be on publishing quality articles rapidly and freely available worldwide.