Temple F. Smith
Boston University

Dedication: To a friend and inspiration, Stanislaw Ulam.

I was lucky not only to have known Stan (Dr. Ulam), but to have been befriended by him.  I would note that it was with his support that my first “computational” biology paper was published and that I was then a physics graduate student who had not taken or read biology since the sixth grade!  I will outline just a few Ulam anecdotes in his memory.

Abstract:

The recognition of the role of mathematics and computer science in modern biology has led to new terminology, as did chemistry with biochemistry, and physics with biophysics.  We need to think only of bioinformatics, computational biology, and even system biology and genomics for example. These terms seem to strongly suggest that this is all rather new.  Yet a short review of the work of those such as J.B.S. Haldane, Sewell Wright, D’Arcy Thompson and R.A. Fisher, to say nothing of scientists like Luria and Delbrück or Hodgkin and Huxley or Thomas Hunt Morgan, is useful.  Their work and foresight set the stage for modern applications of mathematical modeling and statistics in the biological sciences.  
      
It has often been said that the only difference between now and then is the increase in data - a lot more data.  This is clearly not the full story.  In addition, we have computational power unimaginable to these earlier researchers, as well as to anyone only forty years ago.  So what are our challenges?  Some are clear, including the modeling and analysis of biology’s complex systems such as a cell’s signaling, metabolic and differentiation.  Also needed are analysis and models of complex neural systems and ecological structures.  The latter, for example, will require a nearly full revamping of the early field of population genetics and evolution in order to exploit both modern genomics and new field studies of multiple species and environmental interactions.  And there will be more, much of which will only become apparent as new data and questions arise.  One example would be RNAi and micro-arrays inducing the development of new analysis tools.

The recognition of the role of mathematics and computer science in modern biology has led to new terminology, as did chemistry with biochemistry, and physics with biophysics.  We need to think only of bioinformatics, computational biology, and even system biology and genomics for example. These terms seem to strongly suggest that this is all rather new.  Yet a short review of the work of those such as J.B.S. Haldane, Sewell Wright, D’Arcy Thompson and R.A. Fisher, to say nothing of scientists like Luria and Delbrück or Hodgkin and Huxley or Thomas Hunt Morgan, is useful.  Their work and foresight set the stage for modern applications of mathematical modeling and statistics in the biological sciences.  
      
It has often been said that the only difference between now and then is the increase in data - a lot more data.  This is clearly not the full story.  In addition, we have computational power unimaginable to these earlier researchers, as well as to anyone only forty years ago.  So what are our challenges?  Some are clear, including the modeling and analysis of biology’s complex systems such as a cell’s signaling, metabolic and differentiation.  Also needed are analysis and models of complex neural systems and ecological structures.  The latter, for example, will require a nearly full revamping of the early field of population genetics and evolution in order to exploit both modern genomics and new field studies of multiple species and environmental interactions.  And there will be more, much of which will only become apparent as new data and questions arise.  One example would be RNAi and micro-arrays inducing the development of new analysis tools.

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Last Modified on: 15 January 2008