Links and Paths through Life Sciences Data Sources

Abstract

An abundance of biological data sources contain data on classes of scientific entities, such as genes and sequences. Logical relationships between scientific objects are implemented as URLs and foreign IDs. Query processing typically involves traversing links and paths (concatenation of links) through these sources. We model the data objects in these sources and the links between objects as an object graph. Analogous to database cost models, we use samples and statistics from the object graph to develop a framework to estimate the result size for a query on the object graph.