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15th International Conference on Metabolomics & Systems Biology, will be organized around the theme “Novel Trends in Metabolomics and Systems Biology”

eurometabolomics-2019 is comprised of 24 tracks and 88 sessions designed to offer comprehensive sessions that address current issues in eurometabolomics-2019.

Submit your abstract to any of the mentioned tracks. All related abstracts are accepted.

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Metabolomics is the systematic study of the metabolome, the unique biochemical fingerprint of all cellular processes. It is an Omics technology that allows simultaneous, global, and comprehensive characterization of small molecules in a biological system. It is the large-scale study of small molecules within a mass range of 50-1500 Daltons (Da), commonly known as metabolites, within cells, biofluids, tissues or organisms. These metabolites within biological samples under given genetic, nutritional or environmental conditions are known as the metabolome.

  • Track 1-1Metabolite identification and analysis
  • Track 1-2Metabolomics databases
  • Track 1-3Software workflow for metabolomics: Targeted and non targeted screening and validation

Systems biology is the study of biological systems at a cellular, molecular and organism level, as an integrated and interacting network of genes, proteins and biochemical reactions which give rise to life. It will become main stream in biological sciences this century. It can be used systematically at all levels, from molecules to entire systems and its integration into quantitative models to gain knowledge in order to make accurate simulation of biological processes possible. The technologies such as genomics, bioinformatics, proteomics, mathematical and computational models are used for predicting dynamical behaviour and quantitative measurements of the behaviour.

  • Track 2-1Systems biology methods to characterize biological systems
  • Track 2-2Multicellular systems biology
  • Track 2-3Quantitative systems pharmacology
  • Track 2-4Mathematical biology
  • Track 2-5Pathways and networks
  • Track 2-6Modelling and simulation tools in systems biology

Metabolomics along with systems biology can be used to identify endogenous metabolites that modify protein expression. The main aim of Omics technologies is to reveal unexpected properties of biological systems by their nature. On behalf of 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 quantitation of small molecular weight metabolites. This prospective is a prerequisite for the analysis of dynamic systems. Accordingly, metabolomics is a key technology for systems biology.

Synthetic biology main purposes is to create novel biological functions and systems by combining biology with engineering. The workflow of the development of novel biological functions with synthetic biology is ideally linear which will be attainable with the quantitative engineering approach, high-quality predictive models, and libraries of well-characterized parts. In particular phases of synthetic biology workflow different types of metabolic models, mathematical representations of metabolism and its components, enzymes and metabolites, are useful.

  • Track 4-1Genome-scale modelling & flux balance analysis
  • Track 4-2In silico design of novel pathways
  • Track 4-3Signal transduction
  • Track 4-4Architecture of human metabolome
  • Track 4-5Computational data analysis in metabolomics
  • Track 4-6Metabolic flux analysis and metabolic models
  • Track 4-7Metabolic network simulation

Computational Biology is a rapidly emerging field, at the interface of computer science, arithmetic, physics and biology to study, analyse and understand complex biological systems by taking a corresponding integrated systems view using computational methodologies. The recent advances in computational methodologies are high throughput techniques and computational power. Computational systems biology provides a point of merging for genomics, proteomics, metabolomics and computational modeling and plays a key role in the fast progression of the evolving field by the outstanding developments in biology and computer science.

  • Track 5-1Machine learning and pattern recognition
  • Track 5-2Knowledge discovery and data mining techniques
  • Track 5-3Bioinformatics and cheminformatics
  • Track 5-4Sequence motifs and alignments
  • Track 5-5Hidden markov model
  • Track 5-6Sequencing algorithms
  • Track 5-7Stochastic modelling

Plant metabolomics is a recent research field that has gained increasing interest in the past few years and is applied for sub atomic level of the total metabolite and metabolome of plants under particular conditions. Metabolomics is applied for a better understanding the relation between genes and the biochemical composition of a plant tissue in response to its environment conditions and this information can be further used to assess gene function. The environmental metabolomics is use of metabolomics strategies to investigate the connections of life forms with their surroundings.

  • Track 6-1Metabolomics for exposomics
  • Track 6-2Toxicometabolomics
  • Track 6-3Microbiome-related metabolome
  • Track 6-4Environmental metabolome
  • Track 6-5Metabolomics of genetically modified crops
  • Track 6-6Nutrigenomics and plant functional genomics

Pharmacometabolomics/Pharmacometabonomics is used to determine the metabolic biomarkers that could potentially predict different responses of clinical drugs by identifying differential metabolites at baseline and correlating their variations with the therapeutic outcomes. Presently, Pharmacometabolomics is still in its infancy because most pharmacometabolomics studies are merely focused on revealing the correlation between baseline metabotypes which are influenced by factors such as diets, ages, drug intake and gut microbiota with drug responses or disease susceptibility to study and minimize the metabolic biases.

NMR-based metabonomics categorizes and provides information regarding organ-specific toxicity, monitor the onset and progression of toxicological effects, and identify biomarkers of toxicity. An upcoming challenge of metabolomics is to describe the cellular metabolome for purposes of understanding cellular functions. Such information is crucial if metabolomics is to provide a balancing dataset together with genomics and proteomics can be used to construct computer network models to describe cellular functions. NMR data are vastly reproducible and quantitative over a wide vigorous range and are unparalleled for determining structures of unknowns.

Diverse analytical techniques are needed to achieve higher coverage of metabolites present within a biological system, which consists of a mass of molecules, having a variety of physical and chemical properties and existing as a dynamic range in biological samples. The application of mass spectrometry in metabolomics has increased exponentially since the discovery and development of electrospray ionization and matrix-assisted laser desorption ionization techniques.

Metabolomics Analytical approaches for can be categorized largely into two discrete groups targeted or untargeted. These approaches can further be segmented as metabolic profiling, using an untargeted approach or metabolite identification and quantitation using a targeted approach. A diverse terminology for the definition of metabolic approaches has been used by various metabolomic research areas.

  • Track 10-1Targeted Metabolomics
  • Track 10-2Untargeted Metabolomics

The recent analytical platforms based on mass spectrometry and nuclear magnetic resonance has enabled separation, characterization, detection, and quantification of such chemically diverse structures. This continued development of these analytical platforms will accelerate the extensive use and combination of metabolomics into systems biology

  • Track 11-1Metabolic profiling
  • Track 11-2Metabolic Fingerprinting
  • Track 11-3Nuclear magnetic resonance (NMR)
  • Track 11-4Gas chromatography–mass spectrometry (GC–MS)
  • Track 11-5Liquid chromatography–mass spectrometry (LC–MS)
  • Track 11-6Capillary Electrophoresis – Mass Spectrometry
  • Track 11-7Fourier-Transform Mass Spectrometry

Metabolomics is a recent area which potentials to contribute expressively to the characterization of various disease phenotypes and to the identification of personal metabolic features that can predict response to therapies and some of which are Microbiology, plants and medical science

  • Pharmacology & Pre-Clinical Drug Trials
  • Toxicology
  • Transplant Monitoring
  • New-Born Screening
  • Clinical Chemistry
  • Tool For Functional Genomics
  • Screening Services
  • Biomarker Search/Identification
  • Companion Diagnostics
  • Drug Development Optimization
  • LC/MS/MS Analysis
  • Combinatorics In Metabolomics
  • DATA Analysis & Interpretation

The application of metabolomics in the field of cancer research has led to the progress of metabolism in development of cancer. In the past ten years, the re-discovery of cancer as a metabolic disorder has happened due to the increased accessibility of metabolomics, identification of cancer metabolite biomarkers and the discovery of oncometabolites.

  • Biomarker in cancer diagnosis, prognosis, & therapeutic response Screening tool
  • Detection of micro metastases
  • As both predictive & pharmacodynamics marker of drug effect including search for new drugs 
  • In Nutrigenomics it is used to see the effect of diet on cancer prevention and its response to treatment
  • As translational research tool which can provide link between clinical & laboratory
  • Molecular analyses of cancers to know the information about the mechanisms of initiation, progression & provide foundation for clinical tests
  • Track 13-1Cancer immunotherapy
  • Track 13-2Gene therapy
  • Track 13-3Targeted therapeutics
  • Track 13-4Novel approaches to cancer therapeutics
  • Track 13-5Active immunotherapies
  • Track 13-6Applications of metabolomics in oncology

Precision medicine is developing as a strategy to alter medical treatment to a small group or even discrete patients based on their genetics, environment and lifestyle.The increasing advance in metabolomics technology identifies the enormous potential of its application in personalized medicine. Merging metabolomics with genomics, transcriptomics, and proteomics studies will result in a significantly improved understanding of the disease mechanisms and the pathophysiology of the target clinical phenotype. The final goal of personalized medicine is to enable clinicians to prescribe the right medicine to the right patient at the right time with maximum efficacy and minimal toxicity.

  • Track 14-1Clinical applications of precision medicine
  • Track 14-2Precision medicine for mental disorders
  • Track 14-3Molecular biological profiling
  • Track 14-4Regenerative medicine and predictive medicine
  • Track 14-5Inborn errors of metabolism (IEM)
  • Track 14-6Nutraceuticals
  • Track 14-7Pharmacometabolomics and precision medicine

Over a period of time, metabolomics studies have identified several relevant biomarkers involved in complex clinical phenotypes using diverse biological systems. Metabolomics can be applied to identify biomarkers related to the perturbation being investigated and these biomarkers can be used to develop personalized prognostic, diagnostic, and treatment approaches. These discovered biomarkers can also be applied further in monitoring of disease progression, treatment efficacy, predisposition to drug-related side effects, and potential relapse.

  • Track 15-1Metabolite platform for validation of biomarkers
  • Track 15-2Biomarkers in drug development
  • Track 15-3Disease related biomarkers
  • Track 15-4Imaging biomarkers
  • Track 15-5Metabolomics in biomarker discovery

Metabolomics is being used in Drug Discovery and in development from lead compound discovery to post approval drug surveillance. Metabolomics can help in finding potential new sites for therapeutic intervention by identifying metabolic changes. Metabolomics can provide activity information about possible novel drugs and drug scaffolds, indicate interesting targets for drug development and suggest binding partners of compounds. Furthermore, metabolomics can be used for the discovery of novel natural products and in drug development. Metabolomics can enhance the discovery and testing of new drugs and provide insight into the on- and off-target effects of drugs.

  • Track 16-1Drug metabolism during drug design and development
  • Track 16-2Metabolites in identification of drug targets
  • Track 16-3Metabonomics in preclinical pharmaceutical discovery and development
  • Track 16-4Toxicology and drug metabolism
  • Track 16-5QSAR and ligand-receptor models
  • Track 16-6Applications in Drug Development

Chemotherapy drugs capable to cause significant, irreversible, life threatening organ damage which is distressing for patients and might affect the optimal delivery of treatment. Various studies have predicted the risk factors for drug induced organ damage because of lack of biomarker to pick-up these changes in early phase causes potential morbidity and mortality. Metabolomics can address relation between gene, drugs environment and thus increase our ability to predict individual variation in drug response phenotypes.

Nutritional metabolomics is rapidly developing small molecule chemical profiling to support integration of diet and nutrition in complex bio systems research. Foodomics is a new discipline that studies food and nutrition domains through the application of advanced Omics technologies which include the genomic, transcriptomic, proteomic, and metabolomics study of foods for compound profiling, authenticity, and biomarker detection related to food quality or safety, the development of new transgenic foods, food contaminants, and whole toxicity studies and the new investigations on food bioactivity, food effects on human health.

  • Track 18-1Food Metabolome
  • Track 18-2Food and Nutritional Metabolomics
  • Track 18-3Dietary metabolites and cellular metabolism
  • Track 18-4Food safety and contamination assessment using metabolomics
  • Track 18-5Applications of metabolomics to food processing

In field of pharmaceuticals, metabolomics is turning into an inevitably mainstream instrument for life sciences as it is generally fast and also precise procedure this can be connected with either a particular centre or in a international way to discover new learning about organic frameworks.

In paediatric medicine, the potential applications for metabolomics a highly informative technique that can also be used on non-invasively collected samples. NMR- based Metabolomics might serve as a promising approach for the diagnosis and prediction of mortality in septic shock in a paediatric population and that quantitative metabolomics methods can be applied in the clinical evaluations of paediatric septic shock.

Metabolomics is a novel approach that potentials to enable the detection of states of disease, to categories the patients based on biochemical profiles and to monitor disease progression. Metabolomic analysis may also be able to orient the choice of therapy, identify responders and predict toxicity, paving the way to a customized therapy.

  • Track 21-1Metabolomics in Neuropsychiatric Disorders
  • Track 21-2Metabolomics in Metabolic Disorders
  • Track 21-3Metabolomics in Cardiovascular Diseases
  • Track 21-4Metabolomic studies in Rheumatoid Arthritis
  • Track 21-5Metabolomic studies in Systemic Lupus Erythematous
  • Track 21-6Metabolomic studies in Ankylosing Spondylitis
  • Track 21-7Metabolomic studies in Psoriatic Arthritis
  • Track 21-8Metabolomic studies in Osteoarthritis
  • Track 21-9Metabolomic studies in Gouty Arthritis
  • Track 21-10Metabolomics in Nephrology

Metabolic engineering is the use of genetic engineering to modify the metabolism of an organism which deals with the measurement of metabolic fluxes and elucidation of their control as determinants of metabolic function and cell physiology. An innovative aspect of metabolic engineering is that it departs from the outdated reductionist paradigm of cellular metabolism, taking instead a holistic view. Metabolic engineering is appropriate as a framework for the analysis of genome wide differential gene expression data, in combination with data on protein content and in vivo metabolic fluxes. The main aim of metabolic engineering is to manipulate metabolite production.

The transcriptomics refers to study of transcriptome, which is a dynamic levels of RNA transcripts vary during response to certain conditions in the cell or in different developmental stages of the cell. RNA- sequencing or Transcriptome sequencing is a next-generation sequencing (NGS)-based approach for RNA profiling and analysis by measuring the transcriptomic profiles through microarrays, RNA-seq etc... Proteomics refers to study of large-scale proteomes, which is the set of proteins produced in an organism or biological environment. One of the important objectives of Systems biology is to understand the regulation of cell behaviour by measuring the proteomic profiles through techniques such as gel electrophoresis and mass spectrometry.

  • Track 23-1RNA-seq technology
  • Track 23-2Next generation sequencing (NGS) technologies
  • Track 23-3Gene Expression Profiling and Epigenetics
  • Track 23-4Transcriptome and Proteome analysis
  • Track 23-5RNAi gene silencing technology

Lipidomics is an increasing field with plentiful applications. For investigating different cell types ESI mass spectroscopy is used. Identification of lipid composition and quantification of cellular lipids gives us details about the lipid related pathway which also helps in identification of metabolic pathways and the effected enzymes. The need for bioinformatics is to manage and integrate the experimental data in various aspects, such as, for lipid classification, ontologies, database design, analysis, and visual display and play diverse roles in human physiology.

  • Track 24-1Membrane Lipidomics and Cellular Lipidomics
  • Track 24-2Lipid associated networks and pathways
  • Track 24-3Lipid extraction and Bio-Fluids
  • Track 24-4Bioinformatics tools for Lipidomics Research
  • Track 24-5Lipid molecular databases
  • Track 24-6Neutral Lipidomics