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13th International Conference on Metabolomics and Systems Biology, will be organized around the theme “Scientific Advances In Metabolomics and Systems Biology”

Euro Metabolomics 2018 is comprised of 17 tracks and 97 sessions designed to offer comprehensive sessions that address current issues in Euro Metabolomics 2018.

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

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It is the large-scale study of small molecules, commonly known as metabolites, within cells, bio fluids, tissues or organisms. Collectively, these small molecules and their interactions within a biological system are known as the metabolome. Metabolomics represents the molecular phenotype. Four conceptual approaches in metabolomics - target analysis, metabolite profiling, metabolomics, and metabolic fingerprinting. Target analysis includes the determination and quantification of a small set of known metabolites (targets) using one of the specific analytical technique of best performance. On the other hand Metabolite profiling aims at the analysis of a larger set of compounds, both known and unknown with respect to their chemical nature. This approach has been applied for many different biological systems using GC-MS, including plants, microbes, urine, and plasma samples. Metabolomics employs complementary analytical methodologies, for example, LC-MS/MS, GC-MS, and/or NMR, in order to determine and quantify as many metabolites as possible, either identified or unknown compounds. The last approach is metabolic finger-printing.
  • Track 1-1Metabolite identification and analysis
  • Track 1-2Metabolomics databases
  • Track 1-3Software workflow for metabolomics: Targeted and non targeted screening and validation
Application of metabolomics in the field of cancer research has led to appreciation of metabolism in development of cancer and its progression. Cancer is a metabolic disease which changes the digestion system of the cell and encompassing milieu. Metabolomics in field of pharmaceuticals is turning into an inexorably mainstream instrument for life sciences as it is generally quick and also precise procedure this can be connected with either a specific centre or in a worldwide way to uncover new learning about organic frameworks.
  • Track 2-1Cancer immunotherapy
  • Track 2-2Gene therapy
  • Track 2-3Targeted therapeutics
  • Track 2-4Novel approaches to cancer therapeutics
  • Track 2-5Active immunotherapies
  • Track 2-6Metabolic profiling in cancer
  • Track 2-7Applications of metabolomics in oncology
A biomarker is a characteristic that is objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention. A biomarker reveals further information to presently existing clinical and pathological analysis. It facilitates screening and detecting the disease, monitoring the progression of the disease, and predicting the diagnosis and survival after clinical intervention. A biomarker can also be used to evaluate the process of drug development and optimally to improve the efficacy and safety of disease treatment by enabling physicians to tailor treatment for individual patients. These emerging biomarkers will be beneficial and critical in developing new and clinically reliable indicators that will have a high specificity for the diagnosis.
  • Track 3-1Metabolite platform for validation of biomarkers
  • Track 3-2Biomarkers in drug development
  • Track 3-3Disease related biomarkers
  • Track 3-4Imaging biomarkers
  • Track 3-5Metabolomics in biomarker discovery
This aims to create novel biological functions and systems not found in nature by combining biology with engineering. The workflow of the development of novel cell factories 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. Different types of metabolic models, mathematical representations of metabolism and its components, enzymes and metabolites, are useful in particular phases of the synthetic biology workflow.
  • 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
The new field of precision medicine is revolutionizing current medical practice and reshaping future medicine. Precision medicine aspires to put the patient as the central driver of healthcare by broadening biological knowledge and acknowledging the greater diversity of individuals. It is well established that complex gene–environment interactions shape normal physiological and disease processes at both the individual and population scale. Predicting normal and pathological states in patients requires dynamic and systematic understanding of these interactions. Systems medicine is a new concept based on holistic approaches for disease diagnosis and monitoring.
  • Track 5-1Regenerative medicine and predictive medicine
  • Track 5-2Inborn errors of metabolism (IEM)
  • Track 5-3Nutraceuticals
  • Track 5-4Pharmacometabolomics and precision medicine
  • Track 5-5Clinical applications of precision medicine
  • Track 5-6Precision medicine for mental disorders
  • Track 5-7Molecular biological profiling
Metabolomics is being used in Drug Discovery and in development from lead compound discovery to post approval drug surveillance. A consequence of disease leads to metabolic changes. These changes are the cause of disease advancement. 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 6-1Drug metabolism during drug design and development
  • Track 6-2Metabolites in identification of drug targets
  • Track 6-3Metabonomics in preclinical pharmaceutical discovery and development
  • Track 6-4Toxicology and drug metabolism
  • Track 6-5QSAR and ligand-receptor models
  • Track 6-6Applications in drug development
Nutritional metabolomics is rapidly growing to use small molecule chemical profiling to support integration of diet and nutrition in complex bio systems research. These developments are critical to facilitate transition of nutritional sciences from population based to individual-based criteria for nutritional research, assessment and management. Utilizing metabolomics, scientists can quantitatively dissect non-hereditary variables that are included in post genomic and posttranscriptional change. Food-omics has been recently defined as a new discipline that studies food and nutrition domains through the application of advanced omics technologies in which MS techniques are considered indispensable. Food-omics applications  include the genomic, transcriptomic, proteomic, metabolomics, study of foods for compound profiling, authenticity, biomarker-detection related to food quality or safety; the development of new transgenic foods.
  • Track 7-1Food Metabolome
  • Track 7-2Food and nutritional metabolomics
  • Track 7-3Dietary metabolites and cellular metabolism
  • Track 7-4Food safety and contamination assessment using metabolomics
  • Track 7-5Applications of metabolomics to food processing
Lipids are the important participant in control and regulation of cellular function. The diversity of chemical structure of these lipids is a major challenge for managing high volumes of complex data. 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. They play diverse roles in human physiology. Lipidomics is a growing field with numerous applications. For analysing 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.
  • Track 8-1Membrane lipidomics and cellular lipidomics
  • Track 8-2Lipid associated networks and pathways
  • Track 8-3Lipid extraction and bio-fluids
  • Track 8-4Bioinformatics tools for lipidomics research
  • Track 8-5Lipid molecular databases
  • Track 8-6Neutral Lipidomics
  • Track 8-7Shotgun Lipidomics
Metabolomics is the analysis of low atomic mass metabolites inside a cell, tissue, or bio fluid. The sub control of environmental metabolomics is the application of metabolomic strategies to investigate the connections of life forms with their surroundings. Drug metabolism system is the procedure by which the body separates and changes over pharmaceutical into dynamic concoction substances. Toxicology is a branch of Medical Science that arrangements with the impacts of synthetic compound utilized as a part of the conclusion, treatment, or counteractive action of ailment or other unusual condition on the body. Plant Metabolomics is to characterise at sub atomic level of the total metabolite pool (metabolome) of plants under particular conditions. Metabolomics is used for a better understanding of the correlation between genes and the biochemical composition of a plant tissue in response to its environment can be obtained, and this information can be further used to assess gene function. 
  • Track 9-1Metabolomics for exposomics
  • Track 9-2Green systems biology
  • Track 9-3Toxicometabolomics
  • Track 9-4Microbiome-related metabolome
  • Track 9-5Environmental metabolome
  • Track 9-6Metabolomics of genetically modified crops
  • Track 9-7Nutrigenomics and plant functional genomics
The transcriptomics refers to study of transcriptome. The transcriptome is dynamic, as the levels of RNA transcripts vary during response to certain conditions in the cell or in different developmental stages of the cell. RNA-Seq or Transcriptome sequencing is a next-generation sequencing (NGS)-based approach for RNA profiling and analysis. Proteomics refers to study of large-scale proteomes. Proteome is a set of proteins produced in an organism or biological environment. One of the Systems Biology’s important objectives is to understand the regulation of cell behavior. And important approaches involve are Measure of transcriptomic profiles through microarrays, RNA-seq etc. and Measure of proteomic profiles through techniques such as gel electrophoresis and mass spectrometry.
  • Track 10-1RNA-seq technology
  • Track 10-2Next generation sequencing (NGS) technologies
  • Track 10-3Gene Expression Profiling and Epigenetics
  • Track 10-4Transcriptome and proteome analysis
  • Track 10-5RNAi gene silencing technology
Systems biology is the mathematical and computational modelling of biological components, which may be molecules, cells, organisms or entire species. Living systems are complex and dynamic, and their activities are difficult to predict from the properties of individual parts. For studying all these, quantitative measurements of the behaviour of groups of interacting components are used and also technologies such as genomics, bioinformatics, proteomics, mathematical and computational models are used for describing and predicting dynamical behaviour.
  • Track 11-1Systems biology methods to characterize biological systems
  • Track 11-2Multicellular systems biology
  • Track 11-3Quantitative systems pharmacology
  • Track 11-4Mathematical biology
  • Track 11-5Pathways and networks
  • Track 11-6Modelling and simulation tools in systems biology
Computational Biology is a rapidly emerging field, at the interface of computer science, arithmetic, physics and biology. It endeavours to study, analyse and understand complex biological systems by taking a corresponding integrated systems view using computational methodologies. The recent advances in sophisticated computational methodologies are high throughput techniques and computational power. The striking developments in biology and computer science are playing a key role in the fast progression of the evolving field. Computational systems biology provides a point of merging for genomics, proteomics, metabolomics and computational modelling.
  • Track 12-1Machine learning and pattern recognition
  • Track 12-2Knowledge discovery and data mining techniques
  • Track 12-3Bioinformatics and cheminformatics
  • Track 12-4Sequence motifs and alignments
  • Track 12-5Hidden markov model
  • Track 12-6Sequencing algorithms
  • Track 12-7Stochastic modelling
Metabolomics is the quantitative and qualitative study of small molecules. It is said to be an important technique in systems biology. Metabolites include a diverse group of low molecular weight structures such as lipids, nucleic acids, vitamins, amino acids, peptides, thiols, organic acids and carbohydrates, which makes analysis a big task. The recent development of analytical platforms, such as GC, HPLC, UPLC, CE coupled to MS and NMR spectroscopy, enables separation, detection, characterization and quantification of these metabolites and other related metabolic pathways. Because of the complexity of the metabolome and diverse properties of the metabolites, single analytical platform cannot be used for detecting all metabolites in a sample. The combined use of modern instrumental analytical approaches has led to the ideal outcomes, and is important for increasing the coverage of metabolites which cannot be achieved by single-analysis techniques. Integrated platforms are frequently being used for providing sensitive and reliable detection of thousands of metabolites in a bio fluid sample. Continuous development of these analytical platforms will accelerate extensive use and integration of metabolomics into systems biology.
  • Track 13-1Targeted metabolic profiles
  • Track 13-2Mass spectrometry
  • Track 13-3Capillary electrophoresis–mass spectrometry (CE–MS)
  • Track 13-4Ratio analysis of NMR/MS
  • Track 13-5Nuclear magnetic resonance (NMR)
  • Track 13-6Gas chromatography–mass spectrometry (GC–MS)
  • Track 13-7Liquid chromatography–mass spectrometry (LC–MS)

The latest addition of “omics” disciplines is Metabolomics and it has shown rapid growth in the application to human health research because of major advancements in measurement and analysis techniques. Metabolomics has unique advantages in systems biology and biomarker discovery. The next generation of analysis techniques promises even richer and more complete analysis capabilities that will enable earlier clinical diagnosis, drug refinement, and personalized medicine. The advancements in methodologies and statistical analysis that are enhancing and improving the performance of metabolomics is presented along with highlights of some recent successful applications

  • Track 14-1Spatial metabolomics
  • Track 14-2Network and pathway analysis for metabolomics
  • Track 14-3Chemical and structural characterization of new metabolites
  • Track 14-4Chemometrics, statistical analysis, and other approaches to data analysis
  • Track 14-5Novel sensors and instrumentation for detecting metabolites
  • Track 14-6Computational MS
  • Track 14-7Databases
Metabolic syndrome is a set of conditions such as increase in blood pressure, high blood sugar, excess body fat, and abnormal cholesterol or triglyceride levels all these symptoms occur together which in turn increases the risk of heart disease, diabetes and stroke. More than one of these conditions leads to increased risk. Metabolomics provides molecular information that has potential applications in understanding pathogenesis. It has been playing an important role in unravelling the pathophysiology and identifying early biomarkers of specific physiological responses of complex human diseases in particular metabolic syndrome.
  • Track 15-1Metabolic and endocrine science
  • Track 15-2Metabolomics in diabetes
  • Track 15-3Metabolomics in neuroscience and neurology
  • Track 15-4Metabolomics in cardiovascular diseases
Metabolomics, alternately metabonomics, a growing field of biochemical exploration, is a reciprocal procedure to genomics, transcriptomics, and proteomics. Direct quantitative estimations of metabolite expressions in pee, serum, plasma, and tissue are crucial for the investigation of organic procedures in typical and illness states. Subsequent to the quantity of metabolites in a natural example is extensive partition science assumes an imperative part in metabolomic research. Atomic attractive reverberation (NMR) spectroscopy is especially capable for focused investigation since it is quantitative, reproducible, and suitable for complex examples, for example, blood, pee, or tissue removes with practically zero preparing. Thermo Fisher, AB SCIEX, and Bruker likewise offer instruments for imaging MS, additionally called MALDI imaging. To meet difficulties of searchability and information reconciliation, the metabolomics group has a few activities to build up information vaults. Cases are Metabolights in the United Kingdom, bolstered by the European COSMOS (COordination of Standards in MetabOlomicS) consortium that is creating metabolomics information norms, and Metabolomics Workbench, which means to be the database for NIH-subsidized metabolomics ventures. 

They are a vital direct source of confirmation in pharmaceutical and a device regularly utilized as a part of practice to craft data and create a more extended quest for proof. A decent case report will be vibrant about the significance of the perception being accounted for. In addition to the “evidence of what happened”, single or multiple cases are an important origin for further and more advanced research on diagnosis, treatment adequacy, reasons and results of ailment. Case reports might be first to give signs in differentiating another ailment or unfriendly wellbeing impact from a presentation. 

  • Track 17-1Cardiovascular diseases
  • Track 17-2Cancer
  • Track 17-3Auto immune diseases
  • Track 17-4Neurodegenerative diseases
  • Track 17-5Metabolomic diseases
  • Track 17-6Clinical case reports
  • Track 17-7Diabetes