Biostatistics meets bioinformatics in integrating information from highdimensional heterogeneous genomic data: Two examples from rare genetic diseases and infectious diseases (original) (raw)

2012

Abstract

Understanding genetic information to code and interpret disease phenotypes represents one major goal in modern biology. The challenge of integrating separate scientific vocabularies and insight is daunting because of the vastness and rapid evolution of the disciplines. New models and tools are needed to allow scientists to bridge knowledges, integrate concepts and information, and enable complex analysis. In this contribution we show two examples of datasets from Gene Therapy and Tubercolosis to highlight how integration between biostatistics and bioinformatics allows to gain information from the extremely large biogical databases produced with the new biotechnologies, such as Next Generation Sequencing (NGS) data.

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