**4. Towards a global understanding of physiology**

The large number of genomes, including human, that have been mapped and the knowledge of the genetic code, have increased the interest in other –OMICS technologies, such as proteomics and metabolomics. Both proteomics and metabolomics differ from genomics in terms of complexity and dynamic variability. Proteome and metabolome are constantly changing according to the genome and the environment, therefore the ultimate phenotype of cell, organ, and organism is reflected in proteomic and metabolomic profiles. This variability, enhanced by the using of different methodologies and equipments, usually impedes obtaining reliable and reproducible results when comparing patients and healthy controls. The study of a large number of healthy valves using a standardized protocol may provide useful informa‐ tion about the heterogeneity of its profiles. Thus, different profiles could be assigned to different states such as sex, age or risk factors. This way, the creation of a protein atlas unmasking the expression and localization of proteins coupled to metabolomic results would function as a global knowledgebase with valuable information about normal cellular function [97, 98]. All these information can be storage in conventional web-based databases, in order to obtain a reference material to be used in further studies, when studying different valve diseases, helping to deepen the understanding of the beginning and development of the disease. It would also be possible to find some variation involving metabolic predisposition to develop the disease in the future. This will exponentially increase the possibilities to discover potential therapeutic targets and will open the door to develop a personalized medicine in this disease.

The major challenge of generating a complete database of AV tissue is obtaining enough biological material to be described, since it is not an easily accessible specimen. It is necessary a complex coordination of basic research activities, facilities and infrastructures, as well as the creation of an integrated and multidisciplinary environment with the participation of several different specialists in cardiovascular diseases, i.e. basic researchers, cardiologists, surgeons, pathologists, epidemiologists, patients, patient advocacy groups, funding agencies and industrial partners. Issues related to sample collection, handling and storage, standardization of protocols, common references, number of patients, availability of normal controls, access to bio-banks, tissue arrays, clinical information, follow-up clinical data, computational and statistical analysis, as well as ethical considerations are critical, and must be carefully consid‐ ered and dealt with from the beginning [99]. With such a big collaborating work, there will be a more effective translation of basic discoveries into clinical applications.

No matter how much ambitious and complete the descriptive study is, it is essential integration of the results through a system biology approach. This consists of placing proteins and molecules from experimental analysis in the context of a network of biological interactions, such as gene–gene, gene–protein or protein–protein interactions, followed by different 'guiltby-association' analyses [100]. Usually, these networks are deduced from previously published interactions or from computational prediction models. Different tools exist to perform these analyses, most of them based on Cytoscape Web, a freely available network visualization tool for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework [101-103]. Using an integrative approach, we can obtain a more holistic picture of the molecular mechanisms that occurs in normal aortic valves.
