Snowball: extracting relations from large plain-text collections
DL '00 Proceedings of the fifth ACM conference on Digital libraries
Biclustering of Expression Data
Proceedings of the Eighth International Conference on Intelligent Systems for Molecular Biology
GeneWays: a system for extracting, analyzing, visualizing, and integrating molecular pathway data
Journal of Biomedical Informatics
Selection of Patient Samples and Genes for Outcome Prediction
CSB '04 Proceedings of the 2004 IEEE Computational Systems Bioinformatics Conference
Biclustering Algorithms for Biological Data Analysis: A Survey
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Accurate unlexicalized parsing
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Text Mining for Biology And Biomedicine
Text Mining for Biology And Biomedicine
Deciphering Drug Action and Escape Pathways: An Example on Nasopharyngeal Carcinoma
BICoB '09 Proceedings of the 1st International Conference on Bioinformatics and Computational Biology
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We survey the progress in the analysis of gene expression data for the purposes of disease subtype diagnosis, new subtype discovery, and understanding of diseases and treatment responses. We find existing works fall short on several issues: these works provide little information on the interplay between selected genes; the collection of pathways that can be used, evaluated, and ranked against the observed expression data is limited; and a comprehensive set of rules for reasoning about relevant molecular events has not been compiled and formalized. We thus envision an advanced integrated framework, and are developing a system based on it, to provide biologically inspired solutions. It comprises: (i) automated analysis and extraction of information from biomedical texts; (ii) targeted construction of known pathways; and (iii) direct hypothesis generation based on logical reasoning on, and tests for, consistencies and inconsistencies of observed data against known pathways.