DrugBank

Abstract

During the past ten years, the life sciences (i.e., biology, medicine, and pharmaceutical research) have evolved from being largely low-throughput, observational disciplines to primarily high-throughput, data-driven disciplines. In other words, life sciences are becoming a "data science." Thanks to advances in DNA sequencing, medical imaging, robotic sample handling, and high-throughput screening, it is possible to generate as much data in a day-long experiment as it might have taken for an entire scientific career. For instance, a single eight-hour sequencing run on a DNA pyrosequencer can generate enough sequence data to fill a 1,000-page book (1, 2). The resulting genome sequence could be automatically annotated in a few hours yielding an enormous volume of information that could easily occupy ten large telephone books (3, 4).