Biomedical research and healthcare clinical transactions are generating huge volumes of information. Biomedical research literature doubles every 19 years and AIDS literature in particular doubles every 22 months. Biomedical research is now an information-based science marked by factory-scale sequencing generating huge amounts of data. A clinician, on the other hand, needs approximately 2 million facts to practice. There is a critical need to speed "translation" of genomic research insights into clinical research and practice and vice versa. In this talk, we will discuss the challenges faced by a healthcare enterprise in realizing the vision of Translational Medicine. In this talk, we will discuss some of these challenges, such as: * The need to create structured and semantic representations of genotypic and phenotypic data such as orders, observations, molecular diagnostic test results, etc. * The need for as-needed data and information integration achieved in an incremental and cost-efficient manner. * The need for actionable decision support for suggesting molecular diagnostic tests in response to phenotypic information and therapies in response to genotypic test results. * The need for knowledge update, propagation and consistency to keep abreast of the rapid pace of knowledge discovery being witnessed in the life sciences, a crucial pre-requisite to reduce the cost of knowledge acquisition and maintenance. There is a need and applicability of semantic web-based specifications and technologies to address the above challenges. We will present semantics-based approaches to address the challenges enumerated above. The role and applicability of various semantic web standards (such as RDF and OWL) in the proposed solutions will also be discussed .