PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

An information retrieval perspective on visualization of gene expression data with ontological annotation
Jaakko Peltonen, Helena Aidos, Nils Gehlenborg, Alvis Brazma and Samuel Kaski
In: ICASSP 2010, the 2010 IEEE International Conference on Acoustics, Speech and Signal Processing, 14-19 Mar 2010, Dallas, USA.

Abstract

High-dimensional data are often visualized by dimensionality reduction methods whose goals are not directly related to visualization. We use a recent formalization of visualization as information retrieval and apply that formalism to data with structured annotations: we analyze gene expression data with annotations from the Gene Ontology (GO). We show that using the GO information in visualization yields better retrieval with respect to known ontological relationships and allows discovery of data properties not explained by the ontology. Copyright 2010 IEEE. Published in the IEEE 2010 International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2010), scheduled for 14-19 March 2010 in Dallas, Texas, U.S.A. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works, must be obtained from the IEEE. Contact: Manager, Copyrights and Permissions / IEEE Service Center / 445 Hoes Lane / P.O. Box 1331 / Piscataway, NJ 08855-1331, USA. Telephone: + Intl. 908-562-3966. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

EPrint Type:Conference or Workshop Item (Paper)
Additional Information:http://www.cis.hut.fi/projects/mi/papers/icassp10_preprint.pdf
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Computational, Information-Theoretic Learning with Statistics
Theory & Algorithms
Information Retrieval & Textual Information Access
ID Code:6327
Deposited By:Jaakko Peltonen
Deposited On:08 March 2010