and quick reference tools. Essentially all databases listed focus on interactions or pathways/networks. However, we also include a number of protein-sequence databases that store pathway information as secondary information, e.g. the REBASE database of restriction enzymes contains information about catalytic events involving DNA. COVERAGE As one might expect, the categories of information captured in databases, so far, are biased by community biological interests and do not evenly cover the space of available pathway and interaction data (Figure 1). For instance, there are many protein–protein and protein–compound databases, plausibly because of technical developments in proteomics and interest in drug discovery, but there appear to be only two protein– RNA databases and none for RNA–compound interactions, although these categories are clearly of biological interest. Interactions and pathways deﬁne biological function at the molecular level. Therefore, pathway databases must grow to support the evolution of biological knowledge. There is still signiﬁcant room for pathway database growth in underrepre- sented categories and areas of new biological discoveries, such as microRNA targets. Nucleic Acids Research, 2006, Vol. 34, Database issue D505 META-DATA AND LINKS Database names in Pathguide are linked to the database home- page and clicking on ’more’ next to each database leads to a structured description of the database listing short name, full name, homepage Uniform Resource Locator (URL), last observed date, text description, sample data URL, availability (e.g. free to all users, license purchase required), PubMed links, Pathguide category, types of tools available, database statistics, organisms covered and a popularity measure. The popularity measure used is the number of web pages, as indexed by the Google Internet search engine, that mention a given pathway database homepage URL. A user can rank all databases by this measure by clicking ’Order list by web popularity’ at the top of the Pathguide homepage. The measure is rough because not all websites mentioning a pathway data- base are relevant. Thus the exact ranking is likely not sound, but it is useful as an overview of the most popular set of databases in each category. STANDARDS Many computational pathway analysis methods gain power given a larger biological network. A single new link can lead to a signiﬁcant new biological discovery. Collecting Figure 1. The 40 largest databases in Pathguide. Pathway databases are diverse, both in volume of data (Database size, vertical) and in the attention they appear to generate (Popularity Estimate, horizontal). Database size is the sum of interaction and pathway records (where available; some database statistics may be incomplete). Popularity Estimate is taken to be the number of web pages in Google that mention the database homepage URL. Five main database categories (see symbol legend) out of eight are represented in the top 40. Databases in multiple categories are only represented in one (arbitrarily chosen) category. See the Pathguide website for expanded database names.