A component-based framework for knowledge discovery in bioinformatics

  • Authors:
  • Julien Etienne;Bernd Wachmann;Lei Zhang

  • Affiliations:
  • Siemens Corporate Research, Princeton, NJ;Siemens Corporate Research, Princeton, NJ;Siemens Corporate Research, Princeton, NJ

  • Venue:
  • Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
  • Year:
  • 2006

Quantified Score

Hi-index 0.00

Visualization

Abstract

Motivation: In the field of bioinformatics there is an emerging need to integrate all knowledge discovery steps into a standardized modular framework. Indeed, component-based development can significantly enhance reusability and productivity for short timeline projects with a small team. We present Interactive Knowledge Discovery and Data mining (iKDD), an application framework written in Java that was specifically designed for these purposes.Results: iKDD consists of a component-based architecture and a web-based tool for pre-clinical research and prototype development. The platform provides an intuitive and consistent interface to create and maintain components, e.g., data structures, algorithms and utilities to load, save and visualize data and pipelines. The rich-featured tool supplies database connectivity, workflow processing and rapid prototype building. The architecture was carefully designed using an object-oriented approach that respects crucial goals: usability, openness, robustness and functionality, especially in the abstraction and description of the components, which distinguishes it from other packages. iKDD is well-suited to serve as a public repository of components, to run scientific experiments with a high-level of reproducibility, and also to rapidly build prototypes. This paper describes the general architecture, and demonstrates through examples the ease by which a complex scenario implementation can be facilitated with iKDD.