Data analysis and mining in the life sciences

Nam Huyn
2001 SIGMOD record  
Biotech companies routinely generate vast amounts of biological measurement data that must be analyzed rapidly and mined for diagnostic, prognostic, or drug evaluation purposes. While these data analysis tasks are critical to their success, they have not benefited from recent advances that emerged from database and KDD research. In this paper, we focus on two such tasks: on-line analysis of clinical study data, and mining broad datasets for biomarkers. We examine the new requirements that are
more » ... irements that are not met by current data analysis technologies and we identify new database and KDD research to address these needs. We describe our experience implementing a Scientific OLAP system and a data mining platform for the support of biomarker discovery at SurroMed, and we outline some key technical challenges that must be overcome before data analysis and data mining technologies can be widely adopted in the biotech industry.
doi:10.1145/603867.603880 fatcat:unk5kldfcfh3xfwixult3ecrxe