Genomics, Bioinformatics, and Computational Biology

In this chapter, we describe how computational biology can be aided by informatics infrastructure to provide the basis for in silico studies that no longer require the generation of data, and instead facilitate the collection, organization, and analysis of existing datasets that can drive discovery. A new reality is that we are awash in data and tools to analyze these data and one of the most significant challenges is that of enabling the researcher to discover datasets relevant to their work, collect these data, assess its quality, and analyze it. The development of an adequate infrastructure within a researcher's institution greatly facilitates progress on this front, both in terms of the development of tools and the development of local informatics expertise necessary to complement the domain-specific expertise of the researcher. As an informatics community we often ponder the heterogeneity of tools and resources on a global scale at the expense of the more immediate local problems encountered on a routine basis. Here, we suggest that getting our own houses in order by first employing interoperable solutions that support and facilitate collaboration amongst the complementary disciplines within our own institutions places the informatics community in a better position to address global informatics challenges. This approach can ensure that the solutions implemented employ an architecture and standards that support interoperability. Indeed, this is an organizational and cultural challenge rather than a technological one. Organizational structure and practices are described that provide a comprehensive base of talent capable of creating an environment that supports a sustainable informatics infrastructure, and that can quickly grow as needed to support the specific and rapidly evolving needs unique to that institution.