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Nucleic Acids Research Advance Access published online on December 12, 2008
Nucleic Acids Research, doi:10.1093/nar/gkn986
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© 2008 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Computational Biology

Identifying and classifying biomedical perturbations in text

Raul Rodriguez-Esteban*, Phoebe M. Roberts and Matthew E. Crawford

Pfizer Research Technology Center, 620 Memorial Dr., Cambridge, MA 02139, USA

*To whom correspondence should be addressed. Email: Raul.Rodriguez-Esteban{at}pfizer.com

Received September 11, 2008. Revised November 11, 2008. Accepted November 21, 2008.

Molecular perturbations provide a powerful toolset for biomedical researchers to scrutinize the contributions of individual molecules in biological systems. Perturbations qualify the context of experimental results and, despite their diversity, share properties in different dimensions in ways that can be formalized. We propose a formal framework to describe and classify perturbations that allows accumulation of knowledge in order to inform the process of biomedical scientific experimentation and target analysis. We apply this framework to develop a novel algorithm for automatic detection and characterization of perturbations in text and show its relevance in the study of gene–phenotype associations and protein–protein interactions in diabetes and cancer. Analyzing perturbations introduces a novel view of the multivariate landscape of biological systems.


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