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  • Life Out of Sequence: A Data-Driven History of Bioinformatics by Hallam Stevens
  • Joel B. Hagen (bio)
Life Out of Sequence: A Data-Driven History of Bioinformatics. By Hallam Stevens. Chicago: University of Chicago Press, 2013. Pp. 294. $30.

Almost all areas of modern biology have been strongly influenced, and in some cases transformed, by sequence data and the computers necessary to manage and analyze these data. Hallam Stevens explores the development of this new area of bioinformatics beginning in the 1980s and continuing to the present. Although the amino acid sequences of some proteins were first elucidated in the 1950s and nucleic acid (RNA and DNA) sequencing began in the late 1960s, Stevens argues that bioinformatics only emerged when enough sequence data became available to necessitate the use of computers. Prior to this time, computers were something of a novelty that most biologists rarely, if ever, used. Thus, Stevens claims that computers became important in the 1980s not because of changes in computing, but because biology itself had changed in a decisive way. Computers were not specifically designed to solve biological problems, but with the advent of sequence data [End Page 301] the questions that biologists began to ask were strongly shaped by statistical and other analytical problems that physicists (and others) originally had designed computers to solve. Stevens ably details the legacy of big science programs in physics in the late-twentieth-century developments of the Human Genome Project and large databases such as GenBank. According to Stevens, the HGP and bioinformatics formed a positive feedback loop that continues to drive the production of ever more data and more powerful methods for managing, analyzing, and visualizing them.

Stevens argues that by the end of the twentieth century, bioinformatics had become a recognizable discipline with its own epistemic and institutional structures. While a recognizable discipline, tensions persisted from the never-complete hybridization of molecular biology and computer science. Despite some attempts to develop unified curricula for training in bioinformatics, the field continues to attract two quite different groups of people, and there is an uneasy division of labor between bioinformaticians trained in computer science and computational biologists drawn from the life sciences. These differences are reflected in hierarchies of pay, prestige, and even work environments, with computer scientists often relegated to a service role managing the databases that computational biologists use for what is generally perceived as higher-status scientific research.

Although Stevens makes the ambitious claim that eventually all of biology will become fused with informatics (pp. 11, 207), he characterizes the ongoing debates in molecular biology about sequencing and the uses of computers as a “battle” for the future of the discipline (p. 78). This characterization and Stevens’s compelling descriptions of the divisions within bioinformatics suggest that the union of molecular biology and computer science continues to be problematic, despite the field’s great successes. Whether or not this union will extend to the many non-molecular areas of biology that use sequences and other forms of “big data” is certainly open to question.

Perhaps the most interesting and informative aspect of Stevens’s book is the ethnographic studies that he conducted while working at the Broad Institute, a biomedical research organization, and in the Department of Biology at MIT. His own participation in bioinformatics research, his observations of institutional and social structures of the labs, and his interviews with various workers add a personal dimension to the historical claims that he makes both about the way molecular biology is conducted and the internal dynamics of the field of bioinformatics. He effectively uses this anthropological approach to highlight his frequent claims about how computers and statistical methods have radically transformed biology.

A recurring theme in Life Out of Sequence is the major break that bioinformatics has made with older approaches to biology. On a superficial level it would be foolish to dispute the degree to which sequences have changed modern biology, but some historians have made compelling cases for [End Page 302] examples of continuity between earlier traditions in experimental biology, and even natural history, and the later development of large-scale databases and computational methods. Although briefly acknowledging some alternative interpretations, Stevens doesn...


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