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Systems Biology (system + biology)
Terms modified by Systems Biology Selected AbstractsSystems Biology in Yeasts , from Models to Applications: the 25th International Specialized Symposium on Yeasts (ISSY25), Hanasaari, Espoo (Finland), 18,21 June 2006FEMS YEAST RESEARCH, Issue 7 2006Andriy Sibirny No abstract is available for this article. [source] The First International Workshop on Systems Biology of Yeast, St. Louis, USA, 9 November, 2003FEMS YEAST RESEARCH, Issue 7 2004Jens Nielsen No abstract is available for this article. [source] A new holistic exploratory approach to Systems Biology by Near Infrared Spectroscopy evaluated by chemometrics and data inspectionJOURNAL OF CHEMOMETRICS, Issue 10-11 2007Lars Munck Abstract There is a need for an improved biological and theoretical interpretation of Near Infra-Red Spectral (NIRS) fingerprints from tissues that could contribute with holistic overview to fine-grained detail modelled in Systems Biology. The concept of gene expression in self-organised networks was experimentally tested in a barley endosperm model with molecularly defined and undefined mutants. Surprisingly reproducible gene-specific NIRS fingerprints were observed directly in log1/R MSC pre-treated spectra that could not be accurately represented by destructive mathematical models. A mutant spectrum in an isogenic background represents the physiochemical expression of the gene in the whole network (tissue). The necessary holistic overview that is needed experimentally to introduce Ilya Prigogine's theory on self-organisation in Systems Biology was supplied by defining the spectral phenome. Interval spectral information on genotypes and environment was classified by interval Extended Canonical Variates Analysis (iECVA). Genetic changes in spectra were interpreted by interval Partial Least Squares Regression (iPLSR) correlations to chemical variables. A new pathway regulation was detected. The finely grained ,bottom up' modelling of molecular and chemical data from pathways requires a coarsely grained exploratory ,top down' overview by NIRS to account for the outcome of self-organisation. The amplification of expression from a gene to the phenome (pleiotropy) can now for the first time be quantified as a whole reproducible phenomenological pattern by NIRS and compared to other gene spectra. It explains published findings that transformed respectively mutated genes in genetically modified organisms (GMOs) and cancer patients can be detected unsupervised from tissues by spectroscopy, chemometrics and data inspection. Copyright © 2007 John Wiley & Sons, Ltd. [source] Stochastic Modelling for Systems Biology by D. J. WilkinsonJOURNAL OF THE ROYAL STATISTICAL SOCIETY: SERIES A (STATISTICS IN SOCIETY), Issue 1 2007John Haigh No abstract is available for this article. [source] Systems Biology of Vascular Endothelial Growth FactorsMICROCIRCULATION, Issue 8 2008FEILIM MAC GABHANN ABSTRACT Several cytokine families have roles in the development, maintenance, and remodeling of the microcirculation. Of these, the vascular endothelial growth factor (VEGF) family is one of the best studied and one of the most complex. Five VEGF ligand genes and five cell-surface receptor genes are known in the human, and each of these may be transcribed as multiple splice isoforms to generate an extensive family of proteins, many of which are subject to further proteolytic processing. Using the VEGF family as an example, we describe the current knowledge of growth-factor expression, processing, and transport in vivo. Experimental studies and computational simulations are being used to measure and predict the activity of these molecules, and we describe avenues of research that seek to fill the remaining gaps in our understanding of VEGF family behavior. [source] Looking inside the box: bacterial transistor arraysMOLECULAR MICROBIOLOGY, Issue 1 2008Thomas S. Shimizu Summary One often compares cells to computers, and signalling proteins to transistors. Location and wiring of those molecular transistors is paramount in defining the function of the subcellular chips. The bacterial chemotactic sensing apparatus is a large, stable assembly consisting of thousands of receptors, signal transducing kinases and linking proteins, and is responsible for the motile response of the bacterium to environmental signals, whether chemical, mechanical, or thermal. Because of its rich functional repertoire despite its relative simplicity, this chemosome has attracted much attention from both experimentalists and theoreticians, and the bacterial chemotaxis response becoming a benchmark in Systems Biology. Structural and functional models of the chemotactic device have been developed, often based on particular assumptions regarding the topology of the receptor lattice. In this issue of Molecular Microbiology, Briegel et al. provide a detailed view of the receptor arrangement, unravelling the wiring of the molecular signal processors. [source] Systems Biology for Biotech ApplicationsBIOTECHNOLOGY JOURNAL, Issue 7 2010Article first published online: 14 JUL 2010 Cover illustration: Systems Biology for Biotech Applications is the topic of this BTJ special issue edited by Nathan D. Price and Sang Yup Lee. You will find the latest progress on genome-scale in silico models of metabolism, building the blueprint of life and applications for biofuels and bioprocessing. Cover image: degradation, PHA biosynthesis, central metabolic networks (back) and genome-scale metabolic networks (front) in Pseudomonas putida. Courtesy of Tae Yong Kim, KAIST, Korea. [source] Meeting report: Systems Biology of MicroorganismsBIOTECHNOLOGY JOURNAL, Issue 7 2010Barbara Janssens First page of article [source] Systems Biology in the Microbial World and BeyondCHEMISTRY & BIODIVERSITY, Issue 5 2010Zhongming Zhao First page of article [source] Systems biology: in the broadest sense of the wordENVIRONMENTAL MICROBIOLOGY, Issue 4 2005David W. Ussery No abstract is available for this article. [source] Systems biology approaches for toxicology,JOURNAL OF APPLIED TOXICOLOGY, Issue 3 2007William Slikker Jr Abstract Systems biology/toxicology involves the iterative and integrative study of perturbations by chemicals and other stressors of gene and protein expression that are linked firmly to toxicological outcome. In this review, the value of systems biology to enhance the understanding of complex biological processes such as neurodegeneration in the developing brain is explored. Exposure of the developing mammal to NMDA (N -methyl- d -aspartate) receptor antagonists perturbs the endogenous NMDA receptor system and results in enhanced neuronal cell death. It is proposed that continuous blockade of NMDA receptors in the developing brain by NMDA antagonists such as ketamine (a dissociative anesthetic) causes a compensatory up-regulation of NMDA receptors, which makes the neurons bearing these receptors subsequently more vulnerable (e.g. after ketamine washout), to the excitotoxic effects of endogenous glutamate: the up-regulation of NMDA receptors allows for the accumulation of toxic levels of intracellular Ca2+ under normal physiological conditions. Systems biology, as applied to toxicology, provides a framework in which information can be arranged in the form of a biological model. In our ketamine model, for example, blockade of NMDA receptor up-regulation by the co-administration of antisense oligonucleotides that specifically target NMDA receptor NR1 subunit mRNA, dramatically diminishes ketamine-induced cell death. Preliminary gene expression data support the role of apoptosis as a mode of action of ketamine-induced neurotoxicity. In addition, ketamine-induced cell death is also prevented by the inhibition of NF- ,B translocation into the nucleus. This process is known to respond to changes in the redox state of the cytoplasm and has been shown to respond to NMDA-induced cellular stress. Although comprehensive gene expression/proteomic studies and mathematical modeling remain to be carried out, biological models have been established in an iterative manner to allow for the confirmation of biological pathways underlying NMDA antagonist-induced cell death in the developing nonhuman primate and rodent. Published in 2007 John Wiley & Sons, Ltd. [source] Systems biology and its application to the understanding of neurological diseases,ANNALS OF NEUROLOGY, Issue 2 2009Pablo Villoslada MD Recent advances in molecular biology, neurobiology, genetics, and imaging have demonstrated important insights about the nature of neurological diseases. However, a comprehensive understanding of their pathogenesis is still lacking. Although reductionism has been successful in enumerating and characterizing the components of most living organisms, it has failed to generate knowledge on how these components interact in complex arrangements to allow and sustain two of the most fundamental properties of the organism as a whole: its fitness, also termed its robustness, and its capacity to evolve. Systems biology complements the classic reductionist approaches in the biomedical sciences by enabling integration of available molecular, physiological, and clinical information in the context of a quantitative framework typically used by engineers. Systems biology employs tools developed in physics and mathematics such as nonlinear dynamics, control theory, and modeling of dynamic systems. The main goal of a systems approach to biology is to solve questions related to the complexity of living systems such as the brain, which cannot be reconciled solely with the currently available tools of molecular biology and genomics. As an example of the utility of this systems biological approach, network-based analyses of genes involved in hereditary ataxias have demonstrated a set of pathways related to RNA splicing, a novel pathogenic mechanism for these diseases. Network-based analysis is also challenging the current nosology of neurological diseases. This new knowledge will contribute to the development of patient-specific therapeutic approaches, bringing the paradigm of personalized medicine one step closer to reality. Ann Neurol 2009;65:124,139 [source] Editorial: Microfluidics in system biologyELECTROPHORESIS, Issue 19 2005Niels Lion No abstract is available for this article. [source] The analysis of Neisseria meningitidis proteomes: Reference maps and their applications,PROTEINS: STRUCTURE, FUNCTION AND BIOINFORMATICS, Issue 16 2007Giulia Bernardini Abstract Neisseria meningitidis is an encapsulated Gram-negative bacterium responsible for significant morbidity and mortality worldwide. The availability of meningococcal genome sequences in combination with the rapid growth of proteomic techniques and other high-throughput methods, provided new approaches to the analysis of bacterial system biology. This review considers the meningococcal reference maps so far published as a starting point aimed to elucidate bacterial physiology and pathogenicity, paying particular attention to proteins with potential vaccine and diagnostic applications. [source] Metabolomics: Current technologies and future trendsPROTEINS: STRUCTURE, FUNCTION AND BIOINFORMATICS, Issue 17 2006Katherine Hollywood Abstract The ability to sequence whole genomes has taught us that our knowledge with respect to gene function is rather limited with typically 30,40% of open reading frames having no known function. Thus, within the life sciences there is a need for determination of the biological function of these so-called orphan genes, some of which may be molecular targets for therapeutic intervention. The search for specific mRNA, proteins, or metabolites that can serve as diagnostic markers has also increased, as has the fact that these biomarkers may be useful in following and predicting disease progression or response to therapy. Functional analyses have become increasingly popular. They include investigations at the level of gene expression (transcriptomics), protein translation (proteomics) and more recently the metabolite network (metabolomics). This article provides an overview of metabolomics and discusses its complementary role with transcriptomics and proteomics, and within system biology. It highlights how metabolome analyses are conducted and how the highly complex data that are generated are analysed. Non-invasive footprinting analysis is also discussed as this has many applications to in,vitro cell systems. Finally, for studying biotic or abiotic stresses on animals, plants or microbes, we believe that metabolomics could very easily be applied to large populations, because this approach tends to be of higher throughput and generally lower cost than transcriptomics and proteomics, whilst also providing indications of which area of metabolism may be affected by external perturbation. [source] Score Tests for Exploring Complex Models: Application to HIV Dynamics ModelsBIOMETRICAL JOURNAL, Issue 1 2010Julia Drylewicz Abstract In biostatistics, more and more complex models are being developed. This is particularly the case in system biology. Fitting complex models can be very time-consuming, since many models often have to be explored. Among the possibilities are the introduction of explanatory variables and the determination of random effects. The particularity of this use of the score test is that the null hypothesis is not itself very simple; typically, some random effects may be present under the null hypothesis. Moreover, the information matrix cannot be computed, but only an approximation based on the score. This article examines this situation with the specific example of HIV dynamics models. We examine the score test statistics for testing the effect of explanatory variables and the variance of random effect in this complex situation. We study type I errors and the statistical powers of this score test statistics and we apply the score test approach to a real data set of HIV-infected patients. [source] Monoclonal antibody proteomics: Discovery and prevalidation of chronic obstructive pulmonary disease biomarkers in a single stepELECTROPHORESIS, Issue 23 2007Eszter Csanky Abstract We define mAb proteomics as the global generation of disease specific antibodies that permit mass screening of biomarkers. An integrated, high-throughput, disease-specific mAb-based biomarker discovery platform has been developed. The approach readily provided new biomarker leads with the focus on large-scale discovery and production of mAb-based, disease-specific clinical assay candidates. The outcome of the biomarker discovery process was a highly specific and sensitive assay, applicable for testing of clinical validation paradigms, like response to treatment or correlation with other clinical parameters. In contrast to MS-based or systems biology-based strategies, our process produced prevalidated clinical assays as the outcome of the discovery process. By re-engineering the biomarker discovery paradigm, the encouraging results presented in this paper clearly demonstrate the efficiency of the mAb proteomics approach, and set the grounds for the next steps of studies, namely, the hunt for candidate biomarkers that respond to drug treatment. [source] ESCI award lecture: from a little mouse to rationale medicine for bone lossEUROPEAN JOURNAL OF CLINICAL INVESTIGATION, Issue 10 2009A. Leibbrandt Abstract Completion of the human genome is one of the many significant milestones in the new era of systems biology. The current phase of genomic studies is focused upon parsing this new found genetic data with respect to scientific interest, and economic and health impact applications. As the sequences are now available and whole genome single nucleotide polymorphism maps for multiple human diseases will be available with the advent of modern genomics, the big challenge is to determine the function of these genes in the context of the entire organism. The emphasis is therefore on functional genomic analysis that represents the new front-line and limiting factor for realizing potential benefits of genome-based science. Defined gene targeting has been proven to be particularly useful as loss of expression mutants can reveal essential functions of molecules and the pathogenesis of disease. Using gene-targeted mice, my group has over the years identified genes that control heart and lung functions [1,5]; apoptosis [6,9]; lymphocyte activation [10,14]; cancer [15,17]; pain [18]; diabetes [19]; fertility [20] or wound healing [21]. In this study, I would like to review our work on RANKL in more detail. [source] Catabolite repression in Escherichia coli, a comparison of modelling approachesFEBS JOURNAL, Issue 2 2009Andreas Kremling The phosphotransferase system in Escherichia coli is a transport and sensory system and, in this function, is one of the key players of catabolite repression. Mathematical modelling of signal transduction and gene expression of the enzymes involved in the transport of carbohydrates is a promising approach in biotechnology, as it offers the possibility to achieve higher production rates of desired components. In this article, the relevance of methods and approaches concerning mathematical modelling in systems biology is discussed by assessing and comparing two comprehensive mathematical models that describe catabolite repression. The focus is thereby on modular modelling with the relevant input in the central modules, the impact of quantitative model validation, the identification of control structures and the comparison of model predictions with respect to the available experimental data. [source] Seed-based systematic discovery of specific transcription factor target genesFEBS JOURNAL, Issue 12 2008Ralf Mrowka Reliable prediction of specific transcription factor target genes is a major challenge in systems biology and functional genomics. Current sequence-based methods yield many false predictions, due to the short and degenerated DNA-binding motifs. Here, we describe a new systematic genome-wide approach, the seed-distribution-distance method, that searches large-scale genome-wide expression data for genes that are similarly expressed as known targets. This method is used to identify genes that are likely targets, allowing sequence-based methods to focus on a subset of genes, giving rise to fewer false-positive predictions. We show by cross-validation that this method is robust in recovering specific target genes. Furthermore, this method identifies genes with typical functions and binding motifs of the seed. The method is illustrated by predicting novel targets of the transcription factor nuclear factor kappaB (NF-,B). Among the new targets is optineurin, which plays a key role in the pathogenesis of acquired blindness caused by adult-onset primary open-angle glaucoma. We show experimentally that the optineurin gene and other predicted genes are targets of NF-,B. Thus, our data provide a missing link in the signalling of NF-,B and the damping function of optineurin in signalling feedback of NF-,B. We present a robust and reliable method to enhance the genome-wide prediction of specific transcription factor target genes that exploits the vast amount of expression information available in public databases today. [source] Bacteria as computers making computersFEMS MICROBIOLOGY REVIEWS, Issue 1 2009Antoine Danchin Abstract Various efforts to integrate biological knowledge into networks of interactions have produced a lively microbial systems biology. Putting molecular biology and computer sciences in perspective, we review another trend in systems biology, in which recursivity and information replace the usual concepts of differential equations, feedback and feedforward loops and the like. Noting that the processes of gene expression separate the genome from the cell machinery, we analyse the role of the separation between machine and program in computers. However, computers do not make computers. For cells to make cells requires a specific organization of the genetic program, which we investigate using available knowledge. Microbial genomes are organized into a paleome (the name emphasizes the role of the corresponding functions from the time of the origin of life), comprising a constructor and a replicator, and a cenome (emphasizing community-relevant genes), made up of genes that permit life in a particular context. The cell duplication process supposes rejuvenation of the machine and replication of the program. The paleome also possesses genes that enable information to accumulate in a ratchet-like process down the generations. The systems biology must include the dynamics of information creation in its future developments. [source] Genome-scale models of bacterial metabolism: reconstruction and applicationsFEMS MICROBIOLOGY REVIEWS, Issue 1 2009Maxime Durot Abstract Genome-scale metabolic models bridge the gap between genome-derived biochemical information and metabolic phenotypes in a principled manner, providing a solid interpretative framework for experimental data related to metabolic states, and enabling simple in silico experiments with whole-cell metabolism. Models have been reconstructed for almost 20 bacterial species, so far mainly through expert curation efforts integrating information from the literature with genome annotation. A wide variety of computational methods exploiting metabolic models have been developed and applied to bacteria, yielding valuable insights into bacterial metabolism and evolution, and providing a sound basis for computer-assisted design in metabolic engineering. Recent advances in computational systems biology and high-throughput experimental technologies pave the way for the systematic reconstruction of metabolic models from genomes of new species, and a corresponding expansion of the scope of their applications. In this review, we provide an introduction to the key ideas of metabolic modeling, survey the methods, and resources that enable model reconstruction and refinement, and chart applications to the investigation of global properties of metabolic systems, the interpretation of experimental results, and the re-engineering of their biochemical capabilities. [source] The 21st century hepatologist and a systems biology based approach to liver diseases,HEPATOLOGY, Issue 6 2008Lopa Mishra No abstract is available for this article. [source] Anatomics: the intersection of anatomy and bioinformaticsJOURNAL OF ANATOMY, Issue 1 2005Jonathan B. L. Bard Abstract Computational resources are now using the tissue names of the major model organisms so that tissue-associated data can be archived in and retrieved from databases on the basis of developing and adult anatomy. For this to be done, the set of tissues in that organism (its anatome) has to be organized in a way that is computer-comprehensible. Indeed, such formalization is a necessary part of what is becoming known as systems biology, in which explanations of high-level biological phenomena are not only sought in terms of lower-level events, but are articulated within a computational framework. Lists of tissue names alone, however, turn out to be inadequate for this formalization because tissue organization is essentially hierarchical and thus cannot easily be put into tables, the natural format of relational databases. The solution now adopted is to organize the anatomy of each organism as a hierarchy of tissue names and linking relationships (e.g. the tibia is PART OF the leg, the tibia IS-A bone) within what are known as ontologies. In these, a unique ID is assigned to each tissue and this can be used within, for example, gene-expression databases to link data to tissue organization, and also used to query other data sources (interoperability), while inferences about the anatomy can be made within the ontology on the basis of the relationships. There are now about 15 such anatomical ontologies, many of which are linked to organism databases; these ontologies are now publicly available at the Open Biological Ontologies website (http://obo.sourceforge.net) from where they can be freely downloaded and viewed using standard tools. This review considers how anatomy is formalized within ontologies, together with the problems that have had to be solved for this to be done. It is suggested that the appropriate term for the analysis, computer formulation and use of the anatome is anatomics. [source] Systems biology approaches for toxicology,JOURNAL OF APPLIED TOXICOLOGY, Issue 3 2007William Slikker Jr Abstract Systems biology/toxicology involves the iterative and integrative study of perturbations by chemicals and other stressors of gene and protein expression that are linked firmly to toxicological outcome. In this review, the value of systems biology to enhance the understanding of complex biological processes such as neurodegeneration in the developing brain is explored. Exposure of the developing mammal to NMDA (N -methyl- d -aspartate) receptor antagonists perturbs the endogenous NMDA receptor system and results in enhanced neuronal cell death. It is proposed that continuous blockade of NMDA receptors in the developing brain by NMDA antagonists such as ketamine (a dissociative anesthetic) causes a compensatory up-regulation of NMDA receptors, which makes the neurons bearing these receptors subsequently more vulnerable (e.g. after ketamine washout), to the excitotoxic effects of endogenous glutamate: the up-regulation of NMDA receptors allows for the accumulation of toxic levels of intracellular Ca2+ under normal physiological conditions. Systems biology, as applied to toxicology, provides a framework in which information can be arranged in the form of a biological model. In our ketamine model, for example, blockade of NMDA receptor up-regulation by the co-administration of antisense oligonucleotides that specifically target NMDA receptor NR1 subunit mRNA, dramatically diminishes ketamine-induced cell death. Preliminary gene expression data support the role of apoptosis as a mode of action of ketamine-induced neurotoxicity. In addition, ketamine-induced cell death is also prevented by the inhibition of NF- ,B translocation into the nucleus. This process is known to respond to changes in the redox state of the cytoplasm and has been shown to respond to NMDA-induced cellular stress. Although comprehensive gene expression/proteomic studies and mathematical modeling remain to be carried out, biological models have been established in an iterative manner to allow for the confirmation of biological pathways underlying NMDA antagonist-induced cell death in the developing nonhuman primate and rodent. Published in 2007 John Wiley & Sons, Ltd. [source] Discrimination of dynamical system models for biological and chemical processesJOURNAL OF COMPUTATIONAL CHEMISTRY, Issue 8 2007Sönke Lorenz Abstract In technical chemistry, systems biology and biotechnology, the construction of predictive models has become an essential step in process design and product optimization. Accurate modelling of the reactions requires detailed knowledge about the processes involved. However, when concerned with the development of new products and production techniques for example, this knowledge often is not available due to the lack of experimental data. Thus, when one has to work with a selection of proposed models, the main tasks of early development is to discriminate these models. In this article, a new statistical approach to model discrimination is described that ranks models wrt. the probability with which they reproduce the given data. The article introduces the new approach, discusses its statistical background, presents numerical techniques for its implementation and illustrates the application to examples from biokinetics. © 2007 Wiley Periodicals, Inc. J Comput Chem, 2007 [source] The Human Ageing Genomic Resources: online databases and tools for biogerontologistsAGING CELL, Issue 1 2009Joćo Pedro De Magalhćes Summary Aging is a complex, challenging phenomenon that requires multiple, interdisciplinary approaches to unravel its puzzles. To assist basic research on aging, we developed the Human Ageing Genomic Resources (HAGR). This work provides an overview of the databases and tools in HAGR and describes how the gerontology research community can employ them. Several recent changes and improvements to HAGR are also presented. The two centrepieces in HAGR are GenAge and AnAge. GenAge is a gene database featuring genes associated with aging and longevity in model organisms, a curated database of genes potentially associated with human aging, and a list of genes tested for their association with human longevity. A myriad of biological data and information is included for hundreds of genes, making GenAge a reference for research that reflects our current understanding of the genetic basis of aging. GenAge can also serve as a platform for the systems biology of aging, and tools for the visualization of protein,protein interactions are also included. AnAge is a database of aging in animals, featuring over 4000 species, primarily assembled as a resource for comparative and evolutionary studies of aging. Longevity records, developmental and reproductive traits, taxonomic information, basic metabolic characteristics, and key observations related to aging are included in AnAge. Software is also available to aid researchers in the form of Perl modules to automate numerous tasks and as an SPSS script to analyse demographic mortality data. The HAGR are available online at http://genomics.senescence.info. [source] Methodological and statistical issues in pharmacogenomicsJOURNAL OF PHARMACY AND PHARMACOLOGY: AN INTERNATI ONAL JOURNAL OF PHARMACEUTICAL SCIENCE, Issue 2 2010Bas J. M. Peters Abstract Pharmacogenomics strives to explain the interindividual variability in response to drugs due to genetic variation. Although technological advances have provided us with relatively easy and cheap methods for genotyping, promises about personalised medicine have not yet met our high expectations. Successful results that have been achieved within the field of pharmacogenomics so far are, to name a few, HLA-B*5701 screening to avoid hypersensitivity to the antiretroviral abacavir, thiopurine S-methyltransferase (TPMT) genotyping to avoid thiopurine toxicity, and CYP2C9 and VKORC1 genotyping for better dosing of the anticoagulant warfarin. However, few pharmacogenetic examples have made it into clinical practice in the treatment of complex diseases. Unfortunately, lack of reproducibility of results from observational studies involving many genes and diseases seems to be a common pattern in pharmacogenomic studies. In this article we address some of the methodological and statistical issues within study design, gene and single nucleotide polymorphism (SNP) selection and data analysis that should be considered in future pharmacogenomic research. First, we discuss some of the issues related to the design of epidemiological studies, specific to pharmacogenomic research. Second, we describe some of the pros and cons of a candidate gene approach (including gene and SNP selection) and a genome-wide scan approach. Finally, conventional as well as several innovative approaches to the analysis of large pharmacogenomic datasets are proposed that deal with the issues of multiple testing and systems biology in different ways. [source] Genomics and systems biology , how relevant are the developments to veterinary pharmacology, toxicology and therapeutics?JOURNAL OF VETERINARY PHARMACOLOGY & THERAPEUTICS, Issue 3 2005R. F. WITKAMP This review discusses some of the recent developments in genomics and its current and future relevance for veterinary pharmacology and toxicology. With the rapid progress made in this field several new approaches in pharmacological and toxicological research have developed and drug discovery and drug development strategies have changed dramatically. In this review, the term genomics is used to encompass the three sub-disciplines transcriptomics, proteomics and metabolomics (or metabonomics) to describe the formation and fate of mRNA, proteins and metabolites, respectively. The current status and methods of the technology and some applications are briefly described. Although the DNA sequencing programmes are receiving considerable attention, the real value of genomics for pharmacology and toxicology is brought by the parallel developments in bio-informatics, bio-statistics and the integration of biology with mathematics and information technology. The ultimate level of integration is now mostly called systems biology, where mRNA, proteins and metabolites are being analysed in parallel, using a complete arsenal of analytical techniques (DNA-array, LC-MS/MS, GC-MS/MS, NMR, etc.). The information thus collected is analysed, integrated, linked to database information and translated to pathways and systems. This approach offers an enormous potential to study disease mechanisms and find new drug targets. Thus far, genomics and systems biology have not been introduced significantly in typical veterinary pharmacological and toxicological research programmes. The high costs and complexity connected to these large projects often form major obstacles for research groups with limited budgets. In other veterinary areas and disciplines, including infectious diseases, animal production and food-safety more examples of application are available. Genomics and bio-informatics provide outstanding opportunities to study pharmacology and toxicology in a more holistic way, taking into account the complexity of biological systems and based on the basic principles of physiology and the concept of homeostasis. Knowledge of biology, in vivo and in vitro models, and comparative pharmacology/toxicology is essential here, creating excellent opportunities for the veterinary trained scientist. [source] Application of 31P NMR spectroscopy and chemical derivatization for metabolite profiling of lipophilic compounds in human serumMAGNETIC RESONANCE IN CHEMISTRY, Issue S1 2009M. Aruni DeSilva Abstract New methods for obtaining metabolic fingerprints of biological samples with improved resolution and sensitivity are highly sought for early disease detection, studies of human health and pathophysiology, and for better understanding systems biology. Considering the complexity of biological samples, interest in biochemical class selection through the use of chemoselective probes for improved resolution and quantitation is increasing. Considering the role of lipids in the pathogenesis of a number of diseases, in this study fingerprinting of lipid metabolites was achieved by 31P labeling using the derivatizing agent 2-chloro-4,4,5,5-tetramethyldioxaphospholane. Lipids containing hydroxyl, aldehyde and carboxyl groups were selectively tagged with 31P and then detected with good resolution using 31P NMR by exploiting the 100% natural abundance and wide chemical shift range of 31P. After standardizing the reaction conditions using representative compounds, the derivatization approach was used to profile lipids in human serum. The results show that the 31P derivatization approach is simple, reproducible and highly quantitative, and has the potential to profile a number of important lipids in complex biological samples. Copyright © 2009 John Wiley & Sons, Ltd. [source] | ||||||||||||||||||||||||||||||||||