E-Nios is at the forefront of addressing the challenges associated with the interpretation of multiomic data, which is crucial for advancing precision medicine and drug development. Their technology integrates semantic information into the processing of -omic data, facilitating both data-driven and biological knowledge-driven analyses. This approach enhances the reproducibility and standardization of biological interpretations, allowing for efficient biomarker and pathway prioritization. E-Nios supports a wide range of -omic analyses, including transcriptomics, genomics, epigenomics, and proteomics, and employs unsupervised analysis techniques to automate the transition from raw data to critical biomarkers, ultimately transforming bulk gene lists into prioritized signatures for multi-sample comparison.

In addition to their core technologies, E-Nios is involved in several collaborative projects aimed at advancing research and treatment strategies in various fields. Initiatives like DISCOVER and INSPIRED focus on understanding cell death signaling and IRE1 biology, respectively, to develop new cancer therapies. The TRAIN-ERS project addresses the implications of endoplasmic reticulum stress in various diseases, while the INNOCENT project leverages nanotechnology to enhance drug delivery for breast cancer treatment. Through these collaborations, E-Nios is contributing to a broader understanding of disease mechanisms and the development of innovative therapeutic strategies.

Greece

Reproducible -omics data interpretation, i.e. the derivation of actionable molecular biomarkers, is currently the main bottleneck in streamlined applications, obstructing the transformation of genomic information into insights for Biomedicine and Biotech.

BioInfoMiner delivers unsupervized, fast and integrative interpretation of -omics experiments, in the form of biomarker signatures. Prioritized genes are mapped to few, clear, systemic pathways and phenotypes, enabling seamless biomarker identification and prioritization.

E-Nios

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