Dear Colleagues,

Data emerging from individual omics approaches are often insufficient to fully understand interactions and functions of biomolecules or processes underway in biological systems. Regardless of the number of molecules observed by any omics platform, isolation of each of these platforms still provides only a limited window into the biological activity of a system under study. In addition, omic measurements are often hampered by sampling issues (insufficient number of samples) as well as intrinsic experimental errors such as non-specific binding problems, over-lapping peaks and low sensitivity as well as assignment issues. Further, a lack of direct correlation between gene expression, protein expression and pathway activation and thus metabolite concentration leaves many unanswered questions. Integrated analysis of high throughput molecular data termed integromics or polyomics has been suggested for several years as a possible avenue to overcome the limitations of individual omics methods, in terms of intrinsic errors as well as biological process coverage, thus helping in furthering our understanding of biological systems as a whole. To understanding phenotype characteristics and to further define the biological processes that are leading to observed properties, it is arguably most appropriate to investigate cross-correlation of metabolic data with genetic, epigenetic and proteomics data.
In this issue we will consider research papers and reviewer that are focusing on integration of different types of omics data with metabolomics results aimed towards better understanding or more detailed description and models of biological systems, phenotype characteristics or phenotype changes. Manuscripts dealing with applications of polyomics approach or with the development for polyomics analysis tools are highly desired.

Miroslava Cuperlovic-Culf
Guest Editor

Manuscript Submission Information

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• Integromics
• Polyomics
• Data integration
• Meta-analysis
• Systems biology
• Computational biology
• Bioinformatics