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Paper short abstract:

The variety of omics data and their large volume require bioinformatics approaches in data handling and processing. This paper discusses the impact of bioinformatics on cancer research and the consequences it may have for the process of knowledge production in biomedicine.

Paper long abstract:

In biomedical research, high-throughput technologies for molecular profiling are employed to produce large amounts of data on genomes, transciptomes, proteomes and epigenomes, often summarized under the label of omics data. The variety of such data and their large volume require new approaches in data storage and processing. Bioinformatics tools have been used to resolve the challenges of systematising, integrating and sharing these large data stocks. At a first glance, the application of bioinformatics simply seems to support data handling. However, a careful analysis of the acquisition and processing of such data in cancer research will show that they are systematically transformed by the supporting bioinformatics procedures. In particular, automation, standardization and quantification of omics data are regarded as necessary preconditions before they are regarded as reliable, valid and finally useful for cancer research. However, these procedures are usually not seen as being an integral part of the research process itself. In contrast to this we argue that data processing not only supports scientific endeavours, but also fundamentally influence the nature of data, and hence the knowledge produced. This argument is based on ongoing empirical analysis of research consortia that use omics data in post-genomic cancer research in Germany. Using qualitative ethnographic methods, we will trace how omics data are processed by bioinformatics requirements, how scientists using such data in research perceive such processing and which consequences for knowledge production arise from it.