When humans are the exception: cross-species databases at the interface of biological and clinical research.

Cross-species comparison has long been regarded as a stepping-stone for medical research, enabling the discovery and testing of prospective treatments before they undergo clinical trial on humans. Post-genomic medicine has made cross-species comparison crucial in another respect: the 'community databases' developed to collect and disseminate data on model organisms are now often used as a template for the dissemination of data on humans and as a tool for comparing results of medical significance across the human-animal boundary. This paper identifies and discusses four key problems encountered by database curators when integrating human and non-human data within the same database: (1) picking criteria for what counts as reliable evidence, (2) selecting metadata, (3) standardising and describing research materials and (4) choosing nomenclature to classify data. An analysis of these hurdles reveals epistemic disagreement and controversies underlying cross-species comparisons, which in turn highlight important differences in the experimental cultures of biologists and clinicians trying to make sense of these data. By considering database development through the eyes of curators, this study casts new light on the complex conjunctions of biological and clinical practice, model organisms and human subjects, and material and virtual sources of evidence--thus emphasizing the fragmented, localized and inherently translational nature of biomedicine.