Applying Text Mining to Search for Protein Patterns

Authors:
Pablo V. Carrera;Daniel Glez-Peña;Eva L. Iglesias;Lourdes Borrajo;Reyes Pavón;Rosalía Laza;Carmen M. Redondo
Affiliations:
Complejo Hospitalario Universitario de Vigo, Hospital do Rebullón, Vigo, Spain 36200;Department of Computer Science, University of Vigo, Ourense, Spain 32004;Department of Computer Science, University of Vigo, Ourense, Spain 32004;Department of Computer Science, University of Vigo, Ourense, Spain 32004;Department of Computer Science, University of Vigo, Ourense, Spain 32004;Department of Computer Science, University of Vigo, Ourense, Spain 32004;Complejo Hospitalario Universitario de Vigo, Hospital do Rebullón, Vigo, Spain 36200
Venue:
IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part II: Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living
Year:
2009

Citing 4
Cited 0

GeneWays: a system for extracting, analyzing, visualizing, and integrating molecular pathway data

Journal of Biomedical Informatics
BioRAT: extracting biological information from full-length papers

Bioinformatics
Automatic assignment of biomedical categories: toward a generic approach

Bioinformatics
Methodological Review: Extracting interactions between proteins from the literature

Journal of Biomedical Informatics

Quantified Score

Hi-index	0.01

Visualization

Abstract

In this work the problem associated to the obtaining of protein patterns associated with certain cancer types starting from biomedical texts is presented. The research is based on the study of the application of text mining and retrieval techniques to biomedical texts and its adaptation to this problem.Our goal is to annotate a significant corpus of biomedical texts, select the more relevant ones and to train machine learning methods to automatically categorize them along certain dimensions that we have previously defined. The idea behind this project is to identify a group of proteins associated with different cancer types.