Abstract: The field of biological data mining is essentially a cottage industry: as new categories of data become available on a regular basis, scientists identify new ways to 'chain' inferences across them. Different scientists bring different perspectives and hence a survey of biological data mining algorithms today will resemble a 'solution first' landscape of specialized applications. To further advance data mining, what is needed is a compositional approach to building complex data mining applications from simple algorithms. This will enable us to capture complex patterns as compositions of simpler patterns. In this talk, we present such an approach using two basic pattern classes: redescriptions and biclusters. Whereas redescriptions identify patterns within a domain, biclusters identify patterns across domains. Both of them mirror shifts-of-vocabulary that can be functionally cascaded in arbitrary ways to create rich chains of inferences. Given a relational database and its schema,we show how the schema can be automatically compiled into a compositional data mining program, and how compositional patterns can be efficiently computed without 'wasteful' data mining. Several applications will be described. The end-goal is to bring the same 'building block' emphasis to data mining that languages like SQL bring to querying.

Short Bio: Naren Ramakrishnan is an associate professor of computer science and faculty fellow in engineering at Virginia Tech. He also serves as an adjunct professor at the Institute of Bioinformatics and Applied Biotechnology (IBAB),Bangalore, India. His research interests include problem solving environments,mining scientific data, and information personalization. He is an area editor for IEEE Computer and is a general chair for the Eighth IEEE International Conference on Data Mining (ICDM'08) to be held in Pisa, Italy, Dec 2008. He was recently named to Computerworld's list of '40 under 40' innovative IT people to watch (July 2007). Ramakrishnan received his Ph.D. in computer sciences from Purdue University.