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PubMed2006

BiologicalNetworks: visualization and analysis tool for systems biology.

Systems level investigation of genomic scale information requires the development of truly integrated databases dealing with heterogeneous data, which can be queried for simple properties of genes or other database objects as well as for complex network level properties, for the analysis and modelling of complex biological processes. Towards that goal, we recently constructed PathSys, a data integration platform for systems biology, which provides dynamic integration over a diverse set of databases [Baitaluk et al. (2006) BMC Bioinformatics 7, 55]. Here we describe a server, BiologicalNetworks, which provides visualization, analysis services and an information management framework over PathSys. The server allows easy retrieval, construction and visualization of complex biological networks, including genome-scale integrated networks of protein-protein, protein-DNA and genetic interactions. Most importantly, BiologicalNetworks addresses the need for systematic presentation and analysis of high-throughput expression data by mapping and analysis of expression profiles of genes or proteins simultaneously on to regulatory, metabolic and cellular networks. BiologicalNetworks Server is available at http://brak.sdsc.edu/pub/BiologicalNetworks.

Computer Graphics↗
PubMed2006

Systems biology in systemic lupus erythematosus: integrating genes, biology and immune function.

Overactive B cells, abnormally activated T cells and inappropriate handling of cellular debris by the innate immune system are central in the pathogenesis of systemic lupus erythematosus (SLE). Genetic studies in SLE patients have unraveled allelic variations in genes encoding key molecules that control inter- and intra-cellular signaling and play a role in the abnormal handling of apoptotic material. Despite recent breakthroughs though, it is still unclear how exactly genes and environment interact to produce the characteristic immune dysregulation in SLE.

Animals↗
PubMed2002

Computational systems biology.

To understand complex biological systems requires the integration of experimental and computational research -- in other words a systems biology approach. Computational biology, through pragmatic modelling and theoretical exploration, provides a powerful foundation from which to address critical scientific questions head-on. The reviews in this Insight cover many different aspects of this energetic field, although all, in one way or another, illuminate the functioning of modular circuits, including their robustness, design and manipulation. Computational systems biology addresses questions fundamental to our understanding of life, yet progress here will lead to practical innovations in medicine, drug discovery and engineering.

Animals↗
PubMed2006

Optical molecular imaging for systems biology: from molecule to organism.

The development of highly efficient analytical methods capable of probing biological systems at system level is an important task that is required in order to meet the requirements of the emerging field of systems biology. Optical molecular imaging (OMI) is a very powerful tool for studying the temporal and spatial dynamics of specific biomolecules and their interactions in real time in vivo. In this article, recent advances in OMI are reviewed extensively, such as the development of molecular probes that make imaging brighter, more stable and more informative (e.g., FPs and semiconductor nanocrystals, also referred to as quantum dots), the development of imaging approaches that provide higher resolution and greater tissue penetration, and applications for measuring biological events from molecule to organism level, including gene expression, protein and subcellular compartment localization, protein activation and interaction, and low-mass molecule dynamics. These advances are of great significance in the field of biological science and could also be applied to disease diagnosis and pharmaceutical screening. Further developments in OMI for systems biology are also proposed.

Animals↗
PubMed2003

Metabolomics in systems biology.

The primary aim of "omic" technologies is the nontargeted identification of all gene products (transcripts, proteins, and metabolites) present in a specific biological sample. By their nature, these technologies reveal unexpected properties of biological systems. A second and more challenging aspect of omic technologies is the refined analysis of quantitative dynamics in biological systems. For metabolomics, gas and liquid chromatography coupled to mass spectrometry are well suited for coping with high sample numbers in reliable measurement times with respect to both technical accuracy and the identification and quantitation of small-molecular-weight metabolites. This potential is a prerequisite for the analysis of dynamic systems. Thus, metabolomics is a key technology for systems biology. The aim of this review is to (a) provide an in-depth overview about metabolomic technology, (b) explore how metabolomic networks can be connected to the underlying reaction pathway structure, and (c) discuss the need to investigate integrative biochemical networks.

Models, Biological↗
PubMed2006

The application of systems biology to drug discovery.

Recent advances in the 'omics' technologies, scientific computing and mathematical modeling of biological processes have started to fundamentally impact the way we approach drug discovery. Recent years have witnessed the development of genome-scale functional screens, large collections of reagents, protein microarrays, databases and algorithms for data and text mining. Taken together, they enable the unprecedented descriptions of complex biological systems, which are testable by mathematical modeling and simulation. While the methods and tools are advancing, it is their iterative and combinatorial application that defines the systems biology approach.

Animals↗
PubMed2004

A function-based framework for understanding biological systems.

Systems biology research is currently dominated by integrative, multidisciplinary approaches. Although important, these strategies lack an overarching systems perspective such as those used in engineering. We describe here the Axiomatic Design approach to system analysis and illustrate its utility in the study of biological systems. Axiomatic Design relates functions at all levels to the behavior of biological molecules and uses a Design Matrix to understand these relationships. Such an analysis reveals that robustness in many biological systems is achieved through the maintenance of functional independence of numerous subsystems. When the interlinking (coupling) of systems is required, biological systems impose a functional period in order to maximize successful operation of the system. Ultimately, the application of Axiomatic Design methods to the study of biological systems will aid in handling cross-scale models, identifying control points, and predicting system-wide effects of pharmacological agents.

Algorithms↗
PubMedDate not supplied

Bioinformatics for the genomic sciences and towards systems biology. Japanese activities in the post-genome era.

The knowledge gleaned from genome sequencing and post-genome analyses is having a very significant impact on a whole range of life sciences and their applications. 'Genome-wide analysis' is a good keyword to represent this tendency. Thanks to innovations in high-throughput measurement technologies and information technologies, genome-wide analysis is becoming available in a broad range of research fields from DNA sequences, gene and protein expressions, protein structures and interactions, to pathways or networks analysis. In fact, the number of research targets has increased by more than two orders in recent years and we should change drastically the attitude to research activities. The scope and speed of research activities are expanding and the field of bioinformatics is playing an important role. In parallel with the data-driven research approach that focuses on speedy handling and analyzing of the huge amount of data, a new approach is gradually gaining power. This is a 'model-driven research' approach, that incorporates biological modeling in its research framework. Computational simulations of biological processes play a pivotal role. By modeling and simulating, this approach aims at predicting and even designing the dynamic behaviors of complex biological systems, which is expected to make rapid progress in life science researches and lead to meaningful applications to various fields such as health care, food supply and improvement of environment. Genomic sciences are now advancing as great frontiers of research and applications in the 21st century. This article starts with surveying the general progress of bioinformatics (Section 1), and describes Japanese activities in bioinformatics (Section 2). In Section 3, I will introduce recent developments in Systems Biology which I think will become more important in the future.

Animals↗
PubMed2001

A basis for a visual language for describing, archiving and analyzing functional models of complex biological systems.

BACKGROUND: We propose that a computerized, internet-based graphical description language for systems biology will be essential for describing, archiving and analyzing complex problems of biological function in health and disease. RESULTS: We outline here a conceptual basis for designing such a language and describe BioD, a prototype language that we have used to explore the utility and feasibility of this approach to functional biology. Using example models, we demonstrate that a rather limited lexicon of icons and arrows suffices to describe complex cell-biological systems as discrete models that can be posted and linked on the internet. CONCLUSIONS: Given available computer and internet technology, BioD may be implemented as an extensible, multidisciplinary language that can be used to archive functional systems knowledge and be extended to support both qualitative and quantitative functional analysis.

Animals↗
PubMed2004

Applications of eTag trade mark assay platform to systems biology approaches in molecular oncology and toxicology studies.

We have developed a universal eTag trade mark multiplex assay platform that can be uniquely applied to survey the molecule profiles of biologic systems in sub-global large-scale analyses. The effectiveness of eTag trade mark assays when applied to focused system biology studies in molecular oncology and predictive toxicology is herein described while reviewing the current methods commonly used. The multi-analyte and multi-parameter assay approach for parallel analysis will form the basis of an emerging paradigm of multiplexed molecular profiling for signaling pathway networks and various aspects of drug development processes.

Gene Expression Profiling↗
PubMed2006

Biological systems modeling and analysis: a biomolecular technique of the twenty-first century.

It is proposed that computational systems biology should be considered a biomolecular technique of the twenty-first century, because it complements experimental biology and bioinformatics in unique ways that will eventually lead to insights and a depth of understanding not achievable without systems approaches. This article begins with a summary of traditional and novel modeling techniques. In the second part, it proposes concept map modeling as a useful link between experimental biology and biological systems modeling and analysis. Concept map modeling requires the collaboration between biologist and modeler. The biologist designs a regulated connectivity diagram of processes comprising a biological system and also provides semi-quantitative information on stimuli and measured or expected responses of the system. The modeler converts this information through methods of forward and inverse modeling into a mathematical construct that can be used for simulations and to generate and test new hypotheses. The biologist and the modeler collaboratively interpret the results and devise improved concept maps. The third part of the article describes software, BST-Box, supporting the various modeling activities.

Computational Biology↗
PubMed2004

Systems biology in drug discovery.

The hope of the rapid translation of 'genes to drugs' has foundered on the reality that disease biology is complex, and that drug development must be driven by insights into biological responses. Systems biology aims to describe and to understand the operation of complex biological systems and ultimately to develop predictive models of human disease. Although meaningful molecular level models of human cell and tissue function are a distant goal, systems biology efforts are already influencing drug discovery. Large-scale gene, protein and metabolite measurements ('omics') dramatically accelerate hypothesis generation and testing in disease models. Computer simulations integrating knowledge of organ and system-level responses help prioritize targets and design clinical trials. Automation of complex primary human cell-based assay systems designed to capture emergent properties can now integrate a broad range of disease-relevant human biology into the drug discovery process, informing target and compound validation, lead optimization, and clinical indication selection. These systems biology approaches promise to improve decision making in pharmaceutical development.

Animals↗
PubMed2005

Systems Biology Toolbox for MATLAB: a computational platform for research in systems biology.

We present a Systems Biology Toolbox for the widely used general purpose mathematical software MATLAB. The toolbox offers systems biologists an open and extensible environment, in which to explore ideas, prototype and share new algorithms, and build applications for the analysis and simulation of biological and biochemical systems. Additionally it is well suited for educational purposes. The toolbox supports the Systems Biology Markup Language (SBML) by providing an interface for import and export of SBML models. In this way the toolbox connects nicely to other SBML-enabled modelling packages. Models are represented in an internal model format and can be described either by entering ordinary differential equations or, more intuitively, by entering biochemical reaction equations. The toolbox contains a large number of analysis methods, such as deterministic and stochastic simulation, parameter estimation, network identification, parameter sensitivity analysis and bifurcation analysis.

Database Management Systems↗
PubMedDate not supplied

Dose-response modeling in reproductive toxicology in the systems biology era.

Systems biology approaches for modeling cellular signaling networks affected by chemical exposures should soon produce integrated methodologies capable of predicting dose-response relationships for developmental toxicants and for other toxic responses. This paper outlines an emerging strategy for systems biology approaches in dose-response modeling. Genome-wide functional screens, bioinformatic tools, and network mapping technologies together can provide directed graph representations of the cellular signaling networks. The graphical representations can be converted into mathematical models that permit predicting the shapes of dose-response curves for altered cell signaling by test compounds during development. Systems biology approaches require interdisciplinary teams with expertise in reproduction, cell biology, signal transduction, mathematical/biomedical modeling, and risk assessment. In addition to outlining a systems approach for dose-response research, this paper discusses initial stages of application of this strategy to examine inhibition of steroidogenesis in testes by phthalate esters.

Animals↗
PubMed2005

Pathway information for systems biology.

Pathway information is vital for successful quantitative modeling of biological systems. The almost 170 online pathway databases vary widely in coverage and representation of biological processes, making their use extremely difficult. Future pathway information systems for querying, visualization and analysis must support standard exchange formats to successfully integrate data on a large scale. Such integrated systems will greatly facilitate the constructive cycle of computational model building and experimental verification that lies at the heart of systems biology.

Animals↗