Collecting and harvesting biological data: the GPCRDB and NucleaRDB information systems

The amount of genomic and proteomic data that is entered each day into databases and the experimental literature is outstripping the ability of experimental scientists to keep pace. While generic databases derived from automated curation efforts are useful, most biological scientists tend to focus on a class or family of molecules and their biological impact. Consequently, there is a need for molecular class-specific or other specialized databases. Such databases collect and organize data around a single topic or class of molecules. If curated well, such systems are extremely useful as they allow experimental scientists to obtain a large portion of the available data most relevant to their needs from a single source. We are involved in the development of two such databases with substantial pharmacological relevance. These are the GPCRDB and NucleaRDB information systems, which collect and disseminate data related to G protein-coupled receptors and intra-nuclear hormone receptors, respectively. The GPCRDB was a pilot project aimed at building a generic molecular class-specific database capable of dealing with highly heterogeneous data. A first version of the GPCRDB project has been completed and it is routinely used by thousands of scientists. The NucleaRDB was started recently as an application of the concept for the generalization of this technology. The GPCRDB is available via the WWW at http://www.gpcr.org/7tm/ and the NucleaRDB at http://www.receptors.org/NR/.

The challenge of contracting for technological information

Contracting to provide technological information (TI) is a significant challenge. TI is an unusual commodity in five ways. (i) TI is difficult to count and value; conventional indicators, such as patents and citations, hardly indicate value. TI is often sold at different prices to different parties. (ii) To value TI, it may be necessary to “give away the secret.” This danger, despite nondisclosure agreements, inhibits efforts to market TI. (iii) To prove its value, TI is often bundled into complete products, such as a computer chip or pharmaceutical product. Efficient exchange, by contrast, would involve merely the raw information. (iv) Sellers’ superior knowledge about TI’s value make buyers wary of overpaying. (v) Inefficient contracts are often designed to secure rents from TI. For example, licensing agreements charge more than marginal cost. These contracting difficulties affect the way TI is produced, encouraging self-reliance. This should be an advantage to large firms. However, small research and development firms spend more per employee than large firms, and nonprofit universities are major producers. Networks of organizational relationships, particularly between universities and industry, are critical in transmitting TI. Implicit barter—money for guidance—is common. Property rights for TI are hard to establish. Patents, quite suitable for better mousetraps, are inadequate for an era when we design better mice. Much TI is not patented, and what is patented sets fuzzy demarcations. New organizational forms are a promising approach to contracting difficulties for TI. Webs of relationships, formal and informal, involving universities, start-up firms, corporate giants, and venture capitalists play a major role in facilitating the production and spread of TI.