The development of a scientific field is often punctuated by a period when diverse observations can be[unreadable] understood in terms of a set of unifying principles. This important moment in time occurs when a critical number[unreadable] (and type) of observations becomes available, and the mechanistic principles often result from an amalgamation[unreadable] of ideas drawn from different intellectual disciplines. This period also marks the emergence of predictive models.[unreadable] T lymphocytes (T cells) orchestrate (and can also misregulate) the adaptive immune response. I believe that T[unreadable] cell biology, especially T cell-mediated autoimmunity, is at a critical juncture where diverse data will soon be[unreadable] integrated in terms of overarching principles. Modern experiments are revealing, in unprecedented detail, the[unreadable] factors that are important in the emergence of T cell-mediated autoimmunity rather than tolerance to ?self?.[unreadable] However, general mechanistic principles necessary for predictive models have proven elusive. This is because T[unreadable] cell-mediated autoimmunity is characterized by cooperative dynamic processes that occur over a spectrum of[unreadable] length and time scales. Phenomena occurring on large scales (tissues) influence cooperative molecular events in a[unreadable] single T cell which, in turn, influences the tissue environment. This complex hierarchical cooperativity makes it[unreadable] difficult to intuit underlying mechanisms from experimental observations alone. I propose to develop the[unreadable] principles governing T cell-mediated autoimmunity by parsing the pertinent cooperative dynamics which occur in[unreadable] a complex space of molecular and cellular variables by integrating three great advances of the twentieth century:[unreadable] statistical mechanics, computational technology, and genetic, biochemical, and imaging experiments. A key to[unreadable] success will be collaborations with experimental immunologists, and I have recently demonstrated how such[unreadable] synergies can be fruitful. If successful, the work that I envisage will provide the principles that could guide the[unreadable] development of therapies for diseases such as multiple sclerosis and diabetes which afflict millions of people.