Call for Abstract

18th International Conference on Metabolomics & Systems Biology, will be organized around the theme “Novel Trends in Metabolomics and Systems Biology”

Eurometabolomics-2022 is comprised of keynote and speakers sessions on latest cutting edge research designed to offer comprehensive global discussions that address current issues in Eurometabolomics-2022

Submit your abstract to any of the mentioned tracks.

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Metabolomics is the large-scale study of small molecules, commonly known as metabolites, within cells, biofluids, tissues or organisms. Collectively, these small molecules and their interactions within a biological system 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
  • Track 1-4Quantitative systems pharmacology

Systems biology is an approach in biomedical research to understanding the larger picture be it at the level of the organism, tissue, or cell—by putting its pieces together. It's in stark contrast to decades of reductionist biology, which involves taking the pieces apart.

  • Track 2-1Systems biology methods to characterize biological systems
  • Track 2-2Multicellular systems biology
  • Track 2-3Quantitative systems pharmacology
  • Track 2-4Mathematical 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.  Thus, metabolomics is a key technology for systems biology


  • Track 3-1Plant Systems
  • Track 3-2Metabolomics: genotype/phenotype classification and pattern recognition
  • Track 3-3Technical and Biological variability
  • Track 3-4System modeling and stochastic noise
  • Track 3-5Differential metabolomics by snapshot analysis

In this context, metabolic engineering is about engineering cell factories for the biological manufacturing of chemical and pharmaceutical products, whereas the main focus of synthetic biology is fundamental biological research facilitated by the use of synthetic DNA and genetic circuits.

  • 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

Computational research methods utilize new advances in computing such as algorithms, models, simulations, and systems in order to understand complex social, biological, technological, and endless other patterns and behaviors.

  • 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

Changes in plant metabolism are at the heart of plant developmental processes, underpinning many of the ways in which plants respond to the environment. As such, the comprehensive study of plant metabolism, or metabolomics, is highly valuable in identifying phenotypic effects of abiotic and biotic stresses on plants.

  • Track 6-1Metabolomics for exposomics
  • Track 6-2Toxicometabolomics
  • Track 6-3Microbiome-related metabolome
  • Track 6-4Environmental metabolome

Pharmacometabolomics is a branch of metabolomics, the disciple that quantifies and analyzes the metabolites existing in a biological sample

  • Track 7-1Drug response
  • Track 7-2metabotypes
  • Track 7-3Drug toxicity

NMR-based metabolomics provides a means to categorize organ-specific toxicity, monitor the onset and progression of toxicological effects, and identify biomarkers of toxicity. A future challenge, however, is to describe the cellular metabolome for purposes of understanding cellular functions


Mass spectrometry-based metabolomics offers quantitative analyses with high selectivity and sensitivity and the potential to identify metabolites. Mass spectrometry-based metabolomics approaches can enable detection and quantification of many thousands of metabolite features simultaneously. However, compound identification and reliable quantification are greatly complicated owing to the chemical complexity and dynamic range of the metabolome.

The two most common analytical approaches for the generation of metabolomics data are nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS). NMR is a spectroscopic technique based on the principle of energy absorption and re-emission of the atom nuclei due to variations in an external magnetic field.

Two main analytical techniques are currently being used in metabolomicsnuclear magnetic resonance (NMR) spectroscopy and high-resolution mass spectrometry (HRMS). Modern separation techniques, such as liquid chromatography (LC), gas chromatography (GC), or capillary electrophoresis (CE), are often coupled with HRMS.

 


At present, metabolomics is applied to investigate several human diseases, to improve their diagnosis and prevention, and to design better therapeutic strategies. In addition, metabolomic studies are also being carried out in areas such as toxicology and pharmacology, crop breeding, and plant biotechnology.

Metabolomics cancer research is being used to discover diagnostic cancer biomarkers in the clinic and in a research institute, to a better understand its complex heterogeneous nature, to discover pathways which involved in cancer that could be used for new targets and to monitor metabolic biomarkers during therapeutic intervention. These metabolomics approaches may also provide evidence to personalized cancer treatments by providing useful information to the clinician about the cancer patient’s response to medical interventions. The ultimate aims of most metabolomics cancer studies are to discover cancer-specific diagnostic, prognostic or predictive biomarkers for a patient. Untargeted metabolomics is an important and excellent tool for probing cancer-altered biochemical pathways.

Metabolomics, which is the metabolites profiling in biological matrices, is a key tool for biomarker discovery and personalized medicine and has great potential to elucidate the ultimate product of the genomic processes.

Metabolomics is an emerging analytical technique for systemic determination of metabolite profiles, which is useful for understanding the biochemical changes in related diseases. It is increasingly being applied towards the identification of biomarkers for disease diagnosis and risk prediction

Microbial metabolomics is one of the platforms for integrating biological information into systems microbiology to facilitate the understanding of microbial interactions and cellular functions.

Proteomics is the study of proteomes on a vast scale. A proteome is a collection of proteins made by a living creature, system, or biological milieu. We can talk about a species' proteome (for example, Homo sapiens) or an organ's proteome (for example, the liver). The proteome is dynamic, varying from cell to cell and changing throughout time. The proteome reflects the underlying transcriptome to some extent. However, in addition to the expression level of the relevant gene, many other factors influence protein activity (which is generally measured by the response rate of the processes in which the protein is engaged).


The structure, function, evolution, mapping, and editing of genomes are all studied in genomics, which is an interdisciplinary subject of biology. A genome is a full set of DNA that includes all of an organism's genes. In contrast to genetics, which focuses on individual genes and their functions in inheritance, genomics tries to characterise and quantify all of an organism's genes, as well as their interrelationships and effects on the organism as a whole. With the help of enzymes and messenger molecules, genes may direct the production of proteins. Proteins, in turn, are responsible for the formation of body structures such as organs and tissues, as well as the management of chemical reactions and the transmission of information between cells. Genomics also entails the assembly and analysis of complete genomes using high-throughput DNA sequencing and bioinformatics to assemble and study their function and structure. Advances in genomes have sparked a revolution in discovery-based research and systems biology, making even the most complicated biological systems like the brain easier to comprehend.