Pilot Actions


The Marine Biology research activity aims at strengthening the analysis of marine ecosystem omics data by providing researchers with essential bioinformatics support. The overall objective is to assist materializing national aims like the characterization of the biochemical potential of marine organisms, bioprospecting, and the monitoring of marine biodiversity.

The Institute of Marine Biology, Biotechnology and Aquaculture (IMBBC/HCMR) has a strong -omics research component aligned with the above aims and generates pertinent data of various formats and context. Among others, the techniques employed include environmental sequencing (metabarcoding, metagenomics, meta-transcriptomics) targeted metabolomics, genomics and phylogenomics, as well as omics applications on aquaculuture fish.

The Hellenic Pasteur Institute (HPI) and the Institute of Chemical Engineering Sciences (ICE-HT/FORTH), among others, have experience in non-coding RNA and in metabolics data analysis, respectively.
The joint Marine Biology, Biotechnology and Bioinformatics efforts of IMBBC, HPI, and ICE-HT, within ELIXIR-GREECE aim to:

  • map nationally the pertinent research needs, available resources and Bioinformatics tools
  • support omics data analyses tasks, like, the evaluation and application of pipelines for::
    • NGS transcriptomics data analysis of non-model marine organisms
    • metagenomics analysis of marine ecosystems samples
  • support targeted metabolomics data analyses assisted by literature mining


Computational Metabolomics Analysis and analysis of Protein Networks
The metabolism is a very important part of molecular physiology. Consequently, the research and defining of the structure and regulation of metabolic pathways is of great importance, in order to fully understand the function of cells and the mechanisms that characterise their disorders. In this context, the high-precision and high-reliability mapping of the activity of metabolic pathways, under different physiological settings, is among the main targets of systemic biology in various biological/biotechnological and biomedical applications.
Metabolomics analysis has recently been recognised as the high-performance analysis of the concentration profile of the free metabolites of small molecular weight, that act as reactants and products of metabolic reactions. This metabolic profile can act as a "fingerprint" of the metabolic activity, through the simultaneous analysis of tens or hundreds of molecules of pathophysiological and pharmacological interest.
While metabolites have been analysed mainly in regard to their function as reactants or products of metabolic networks, most of them also have a regulatory role contributing to the activity of proteins by taking part in many biological processes and also by contributing to the parameters that define the active protein network under specific physiology conditions. In this context, the prototype use of combined metabolomic and proteomic data for the complete combinational reconstruction and analysis of metabolic and protein networks of biological systems can help develop the knowledge about the mechanisms that govern important biological processes and serious disorders.


A pilot study for the discovery of ncRNA biomarkers.
The activities of this action include:

  • Functional annotation of epigenetic and transcription regulation factors. This includes the collection of data about the functional action of epigenetic and transcription regulation factors from multiple sources (RNA-Seq, sRNA-seq, CLIP-Seq, ChIP-Seq and DNase-Seq) as well as the collection of genetic data from the GWAS Catalog and bibliography.
  • Extraction of molecular signatures. The aim is the development of systematic methods for molecular signature extraction. This approach provides a significant advantage, since it reduces the cost of experimental implementation by advancing only the most notable markers (from an informational standpoint) in the synthesis of prediction models.
  • Clarification of the regulatory pathways in homeostasis and malignancy. The aim is the discovery of expression data for the whole transcriptome (mRNAs, pseudogenes, lncRNAs and small RNAs) as well as information about the regulators (upstream and downstream) of the lncRNAs, including functional SNPs is the recognition of regulatory modules and pathways.


A platform for metagenomic analysis of pathogens

This action focuses on the strengthening of the diagnosis of infectious diseases, epidemiological research and the control of epidemic outbreaks. Furthermore, it will also strive to strengthen the understanding of transmission patterns, the development of vaccines targeted in resistant strains and the clarification of the molecular base of the resistance to antibiotics.
The action will also enable the extension of developing sectors of research and development, including a) transcriptional studies for the clarification of the mechanisms of chronic diseases, b) the understanding of the interaction between host microbes, their impact on the manifestation of various pathologies and the role of the human microbiome in the disruption of homeostasis, c) quality validation of biological products, d) reverse engineering of vaccines and analysis of the pan-genome of the various pathogens. The function of the High Content infrastructure will also be supported, through the use of novel image analysis technologies, aiming towards the discovery of functional factors against infectious or neurodegenerative diseases.
In order to achieve optimal and patient-personalised treatment, quick and reliable interconnection between and sample and result is required. This can provide a detailed picture about the disease and the pathogen strains, as well as their resistance. It is also important to define the types of bacteria, which can potentially be involved in hospital infections.
Finally, the aim of this action is the development of algorithmic flows that include bioinformatics analysis and interpretation of new NGS technology data for the diagnosis of Bacterial Infections and the Microbial Resistance profile.