Abstract
The exploration of complex interactions in biological systems is one of the main aims in nature science nowadays. Progress in this area is possible because of high-throughput omics technologies and the computational surge. The development of analytical methods “is trying to keep pace” with the development of molecular biology methods that provide increasingly large amounts of data – omics data. Specialized databases consist of ever-larger collections of experiments that are usually conducted by one next-generation sequencing technique (e.g. RNA-seq). Other databases integrate data by defining qualitative relationships between individual objects in the form of ontologies, interactions, and pathways (e.g. GO, KEGG, and String). However, there are no open-source complementary quantitative data sets for the biological processes studied, including information from many levels of the organism organization, which would allow the development of multidimensional data analysis methods (multiscale and insightful overviews of biological processes). In the paper, the lack of omics complementary quantitative data set, which would help integrate the defined qualitative biological relationships of individual biomolecules with statistical, computational methods, is discussed.
Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
Research funding: None declared.
Employment or leadership: None declared.
Honorarium: None declared.
Competing interests: The funding organization(s) played no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the report for publication.
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