Profiling of global RNA abundance, using gene-chip technology, is a powerful systems biology tool for determining the molecular alterations in human skeletal muscle. The present research strategy was designed to move beyond the large number of small studies carried out in the human muscle physiology field, by providing data that could be more easily compared across physiological or pathophysiology states. In many cases the data is directly associated with skeletal muscle function or exercise capacity, to yield a more physiological interpretation of molecular phenotype. Data will be presented on a range of age related muscle conditions, under a variety of physiological states from > 300 subjects. This will include the largest analysis of human muscle phenotype in Type II diabetes, and the first global molecular analysis of cancer cachexia, intensive-care and exercise responses in human skeletal muscle. The dangers of drawing conclusions from small, poorly matched, cohorts will be exemplified using several examples, while I will show how global transcript profiling highlights the limitations of muscle protein synthesis approaches to study muscle physiology. Contrast will made across these studies, to exemplify how physiological context can facilitate interpretation of data and why systems biology extends beyond, yet benefits from the physiological sciences. Finally, current limitations of gene-chip strategies and studies will be discussed and future directions suggested.