共查询到20条相似文献,搜索用时 15 毫秒
1.
Lake-Ee Quek Christoph Wittmann Lars K Nielsen Jens O Krömer 《Microbial cell factories》2009,8(1):25-15
Background
The quantitative analysis of metabolic fluxes, i.e., in vivo activities of intracellular enzymes and pathways, provides key information on biological systems in systems biology and metabolic engineering. It is based on a comprehensive approach combining (i) tracer cultivation on 13C substrates, (ii) 13C labelling analysis by mass spectrometry and (iii) mathematical modelling for experimental design, data processing, flux calculation and statistics. Whereas the cultivation and the analytical part is fairly advanced, a lack of appropriate modelling software solutions for all modelling aspects in flux studies is limiting the application of metabolic flux analysis. 相似文献2.
Deepali Jhamb Nandini Rao Derek J Milner Fengyu Song Jo Ann Cameron David L Stocum Mathew J Palakal 《BMC bioinformatics》2011,12(1):80
Background
Studies on amphibian limb regeneration began in the early 1700's but we still do not completely understand the cellular and molecular events of this unique process. Understanding a complex biological process such as limb regeneration is more complicated than the knowledge of the individual genes or proteins involved. Here we followed a systems biology approach in an effort to construct the networks and pathways of protein interactions involved in formation of the accumulation blastema in regenerating axolotl limbs. 相似文献3.
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Background
Recent advances in molecular biology techniques provide an opportunity for developing detailed mathematical models of biological processes. An iterative scheme is introduced for model identification using available system knowledge and experimental measurements. 相似文献5.
Background
Advances in bioinformatic techniques and analyses have led to the availability of genome-scale metabolic reconstructions. The size and complexity of such networks often means that their potential behaviour can only be analysed with constraint-based methods. Whilst requiring minimal experimental data, such methods are unable to give insight into cellular substrate concentrations. Instead, the long-term goal of systems biology is to use kinetic modelling to characterize fully the mechanics of each enzymatic reaction, and to combine such knowledge to predict system behaviour. 相似文献6.
Background
Mathematical optimization aims to make a system or design as effective or functional as possible, computing the quality of the different alternatives using a mathematical model. Most models in systems biology have a dynamic nature, usually described by sets of differential equations. Dynamic optimization addresses this class of systems, seeking the computation of the optimal time-varying conditions (control variables) to minimize or maximize a certain performance index. Dynamic optimization can solve many important problems in systems biology, including optimal control for obtaining a desired biological performance, the analysis of network designs and computer aided design of biological units. 相似文献7.
Background
One central goal of computational systems biology is the mathematical modelling of complex metabolic reaction networks. The first and most time-consuming step in the development of such models consists in the stoichiometric reconstruction of the network, i. e. compilation of all metabolites, reactions and transport processes relevant to the considered network and their assignment to the various cellular compartments. Therefore an information system is required to collect and manage data from different databases and scientific literature in order to generate a metabolic network of biochemical reactions that can be subjected to further computational analyses. 相似文献8.
Jamie Twycross Leah R Band Malcolm J Bennett John R King Natalio Krasnogor 《BMC systems biology》2010,4(1):34
Background
Stochastic and asymptotic methods are powerful tools in developing multiscale systems biology models; however, little has been done in this context to compare the efficacy of these methods. The majority of current systems biology modelling research, including that of auxin transport, uses numerical simulations to study the behaviour of large systems of deterministic ordinary differential equations, with little consideration of alternative modelling frameworks. 相似文献9.
Background
A growing demand for tools to assist the building and analysis of biological networks exists in systems biology. We argue that the use of a formal approach is relevant and applicable to address questions raised by biologists about such networks. The behaviour of these systems being complex, it is essential to exploit efficiently every bit of experimental information. In our approach, both the evolution rules and the partial knowledge about the structure and the behaviour of the network are formalized using a common constraint-based language. 相似文献10.
Antonio Rosato Leonardo Tenori Marta Cascante Pedro Ramon De Atauri Carulla Vitor A. P. Martins dos Santos Edoardo Saccenti 《Metabolomics : Official journal of the Metabolomic Society》2018,14(4):37
Introduction
Metabolomics is a well-established tool in systems biology, especially in the top–down approach. Metabolomics experiments often results in discovery studies that provide intriguing biological hypotheses but rarely offer mechanistic explanation of such findings. In this light, the interpretation of metabolomics data can be boosted by deploying systems biology approaches.Objectives
This review aims to provide an overview of systems biology approaches that are relevant to metabolomics and to discuss some successful applications of these methods.Methods
We review the most recent applications of systems biology tools in the field of metabolomics, such as network inference and analysis, metabolic modelling and pathways analysis.Results
We offer an ample overview of systems biology tools that can be applied to address metabolomics problems. The characteristics and application results of these tools are discussed also in a comparative manner.Conclusions
Systems biology-enhanced analysis of metabolomics data can provide insights into the molecular mechanisms originating the observed metabolic profiles and enhance the scientific impact of metabolomics studies.11.
Background
The amount of available biological information is rapidly increasing and the focus of biological research has moved from single components to networks and even larger projects aiming at the analysis, modelling and simulation of biological networks as well as large scale comparison of cellular properties. It is therefore essential that biological knowledge is easily accessible. However, most information is contained in the written literature in an unstructured way, so that methods for the systematic extraction of knowledge directly from the primary literature have to be deployed. 相似文献12.
Monica Chagoyen Pedro Carmona-Saez Concha Gil Jose M Carazo Alberto Pascual-Montano 《BMC bioinformatics》2006,7(1):363-13
Background
Recent analyses in systems biology pursue the discovery of functional modules within the cell. Recognition of such modules requires the integrative analysis of genome-wide experimental data together with available functional schemes. In this line, methods to bridge the gap between the abstract definitions of cellular processes in current schemes and the interlinked nature of biological networks are required. 相似文献13.
Background
The need to execute a sequence of events in an orderly and timely manner is central to many biological processes, including cell cycle progression and cell differentiation. For self-perpetuating systems, such as the cell cycle oscillator, delay times between events are defined by the network of interacting proteins that propagates the system. However, protein levels inside cells are subject to genetic and environmental fluctuations, raising the question of how reliable timing is maintained. 相似文献14.
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Background
Multiple sequence alignment algorithms are very important tools in molecular biology today. Accurate alignment of proteins is central to several areas such as homology modelling, docking studies, understanding evolutionary trends and study of structure-function relationships. In recent times, improvement of existing progressing programs and implementation of new iterative algorithms have made a significant change in this field. 相似文献16.
Background
Within the emerging field of synthetic biology, engineering paradigms have recently been used to design biological systems with novel functionalities. One of the essential challenges hampering the construction of such systems is the need to precisely optimize protein expression levels for robust operation. However, it is difficult to design mRNA sequences for expression at targeted protein levels, since even a few nucleotide modifications around the start codon may alter translational efficiency and dramatically (up to 250-fold) change protein expression. Previous studies have used ad hoc approaches (e.g., random mutagenesis) to obtain the desired translational efficiencies for mRNA sequences. Hence, the development of a mathematical methodology capable of estimating translational efficiency would greatly facilitate the future design of mRNA sequences aimed at yielding desired protein expression levels. 相似文献17.
Alexander L Tournier Paul W Fitzjohn Paul A Bates 《Algorithms for molecular biology : AMB》2006,1(1):25-11
Background
Simulation methods can assist in describing and understanding complex networks of interacting proteins, providing fresh insights into the function and regulation of biological systems. Recent studies have investigated such processes by explicitly modelling the diffusion and interactions of individual molecules. In these approaches, two entities are considered to have interacted if they come within a set cutoff distance of each other. 相似文献18.
Background
Automated identification of cell cycle phases of individual live cells in a large population captured via automated fluorescence microscopy technique is important for cancer drug discovery and cell cycle studies. Time-lapse fluorescence microscopy images provide an important method to study the cell cycle process under different conditions of perturbation. Existing methods are limited in dealing with such time-lapse data sets while manual analysis is not feasible. This paper presents statistical data analysis and statistical pattern recognition to perform this task. 相似文献19.
Microarray data analysis: a practical approach for selecting differentially expressed genes
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David M Mutch Alvin Berger Robert Mansourian Andreas Rytz Matthew-Alan Roberts 《Genome biology》2001,2(12):preprint00-29
Background
The biomedical community is rapidly developing new methods of data analysis for microarray experiments, with the goal of establishing new standards to objectively process the massive datasets produced from functional genomic experiments. Each microarray experiment measures thousands of genes simultaneously producing an unprecedented amount of biological information across increasingly numerous experiments; however, in general, only a very small percentage of the genes present on any given array are identified as differentially regulated. The challenge then is to process this information objectively and efficiently in order to obtain knowledge of the biological system under study and by which to compare information gained across multiple experiments. In this context, systematic and objective mathematical approaches, which are simple to apply across a large number of experimental designs, become fundamental to correctly handle the mass of data and to understand the true complexity of the biological systems under study. 相似文献20.