Automatic construction of gene relation networks using text mining and gene expression data

References

• EISEN, M., et al., 1998, Cluster analysis and display of genome-wide expression patterns. PNAS, 95(25), 14863– 14868.
   PubMed Web of Science ®Google Scholar
• TAMAYO, P., 1999, Interpreting patterns of gene expression with self-organizing maps: methods and application to hematopoietic differentiation. Proceedings of the National Academy of Sciences, 96, 2907– 2912.
   PubMed Web of Science ®Google Scholar
• QUACKENBUSCH, J., 2001, Computational analysis of microarray data. Nature Genetics, 2, 418– 427.
   Google Scholar
• DOUGHERTY, E., et al., 2002, Inference from clustering with application to gene-expression microarrays. Journal of Computational Biology, 9(1), 105– 126.
   PubMed Web of Science ®Google Scholar
• GOLUB, T., et al., 1999, Molecular Classification of Cancer: Class Discovery and class Prediction by Gene Expression Monitoring. Science, 286, 531– 537.
   PubMed Web of Science ®Google Scholar
• VAN’T VEER, L., et al., 2002, Gene expression profiling predicts clinical outcome of breast cancer. Nature, 415.
   Google Scholar
• CHUNG, C., BERNARD, P. and PEROU, C., 2002, Molecular portraits and the family tree of cancer. Nature Genetics Supplement, 32.
   Google Scholar
• SØRLIE, T., et al., 2001, Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. PNAS, 98, 10869– 10874.
   PubMed Web of Science ®Google Scholar
• THYKJAER, T., et al., 2001, Identification of Gene Expression Patterns in Superficial and Invasive Human Bladder Cancer. Cancer Research, 61, 2492– 2499.
   PubMed Web of Science ®Google Scholar
• KHAN, J., et al., 2001, Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks. Nature Medicine, 7(6), 673– 679.
   PubMed Web of Science ®Google Scholar
• HARTWELL, L., et al., 1999, From molecular to modular cell biology. Nature, 402, 47– 52.
   PubMed Web of Science ®Google Scholar
• FRIEDMAN, N., et al., 2000, Using Bayesian Networks to analyze expression data. Journal of Computational Biology, 7, 601– 620.
   PubMed Web of Science ®Google Scholar
• SOMOGYI, R. and SNIEGOSKI, C., 1996, Modeling the complexity of genetic networks: Understanding multigenic and pleiotropic regulation. Complexity, 1(6), 45– 63.
   Google Scholar
• D’HAESELEER, P., et al., 1999, Linear modeling of mRNA expression levels during CNS development and injury. In Pacific Symposium on Biocomputing 4. Hawaii.
   Google Scholar
• DE JONG, H., 2002, Modeling and Simulation of Genetic Regulatory Systems: A Literature Review. Journal of Computational Biology, 9(1), 67– 103.
   PubMed Web of Science ®Google Scholar
• AKUTSU, T., et al., 1998, Identification of gene regulatory networks by strategic gene disruptions and gene overexpressions. In Ninth Annual ACM-SIAM Symposium on Discrete Algorithms (San Francisco: Society for Industrial and Applied Mathematics), pp. 695 – 702.
   Google Scholar
• WAGNER, A., 2002, Estimating coarse gene network structure from large-scale gene perturbation data. Genome Research, 309– 315.
   Google Scholar
• LEROY, G. and CHEN, H., 2002, Filling preposition-based templates to capture information from medical abstracts. In Pacific Symposium on Biocomputing 7, edited by Altman, R. B., Dunker, K. A., Hunter, L., Lauderdale, K., and Klein, T.E. (New Jersey: Word Scientific), pp. 350 – 361.
   Google Scholar
• PUSTEJOVSKY, J., CASTANO, J., and ZHANG, J., 2002, Robust Relational over Biomedical Literature: Extracting Inhibit Relations. In Pacific Symposium on Biocomputing 7. Lihue, Hawaii, edited by Altman, R. B., Dunker, K. A., Hunter, L., Lauderdale, K., and Klein, T.E. (New Jersey: Word Scientific), pp. 362 – 373.
   Google Scholar
• WONG, L., 2001, PIES A Protein Interaction Extraction System. In Pacific Symposium on Biocomputing 6, edited by Altman, R. B., Dunker, K. A., Hunter, L., Lauderdale, K., and Klein, T.E. (New Jersey: Word Scientific), pp. 520 – 531.
   Google Scholar
• YAKUSHIJI, A., et al., 2001, Event Extraction from Biomedical Papers Using a Full Parser. In Pacific Symposium on Biocomputing 6, edited by Altman, R. B., Dunker, K. A., Hunter, L., Lauderdale, K., and Klein, T.E. (New Jersey: Word Scientific), pp. 408 – 419.
   Google Scholar
• FUKUDA, K., et al., 1998, Towards information extraction: Identifying protein names from biological papers. In Pacific Symposium of Biocomputing 3. Hawaii, edited by Altman, R. B., Dunker, K. A., Hunter, L., Lauderdale, K., and Klein, T.E. (New Jersey: Word Scientific), pp. 705 – 716.
   Google Scholar
• HISHIKI, T., et al., 1989, Developing NLP Tools for Genome Informatics: An information extraction perspective. Genome Informatics, 9, 81– 90.
   Google Scholar
• HUMPHREYS, K., DEMETRIOU, G., and GAIZAUSKAS, R., 2000, Two Applications of Information Extraction to Biological Science Journal Articles: Enzyme Interactions and Protein Structures. In Pacific Symposium on Biocomputing 5. Oahu, Hawaii. edited by Altman, R. B., Dunker, K. A., Hunter, L., Lauderdale, K., and Klein, T.E. (New Jersey: Word Scientific), pp. 502 – 513.
   Google Scholar
• PROUX, D., et al., 1998, Detecting gene symbols and names in biological texts: A first step toward pertinent information extraction. In Genome Informatics, edited by S. Moyano and T. Takegi (Universal Academy Press), pp. 72 – 80.
   Google Scholar
• FRIEDMANN, C., et al., 2001, GENIES: A natural-language processing system for the extraction of molecular pathways from journal articles. Bioinformatics Supplement, 1, 74– 82.
   Google Scholar
• THOMAS, J., et al., 2000, Automatic extraction of protein interactions from scientific abstracts. In Pacific Symposium on Biocomputing 5. edited by Altman, R. B., Dunker, K. A., Hunter, L., Lauderdale, K., and Klein, T.E. (New Jersey: Word Scientific), pp. 538 – 549.
   Google Scholar
• RINDFLESH, T., et al., 2000, EDGAR: Extraction of drugs, genes and relations from the biomedical literature. In Pacific Symposium on Biocomputing. 2000. Oahu, Hawaii, edited by Altman, R. B., Dunker, K. A., Hunter, L., Lauderdale, K., and Klein, T.E. (New Jersey: Word Scientific), pp. 514 – 525.
   Google Scholar
• HOELZER, S., et al., 2001, Value of XML in the implementation of clinical practice guidelines - the issue of content retrieval and presentation. Medical Informatics and the Internet in Medicine, 26(2), 131– 146.
   PubMedGoogle Scholar
• DUGAS, M., et al., 2001, XML-based visualization of design and completeness in medical databases. Medical Informatics and the Internet in Medicine, 26(4), 237– 250.
   PubMedGoogle Scholar
• REBHAN, M., et al., 1997, GeneCards: encyclopedia for genes, proteins and diseases. Weizmann Institute of Science, Bioinformatics Unit and Genome Center: Rehovot.
   Google Scholar
• SCHWARTZ, A. S. andHEARST, M.A., 2003, A simple algorithm for identifying abbreviation definitions in biomedical text. In Pacific Symposium on Biocomputing 8, Kawai, Hawaii, edited by R. B. Altman, K. A. Dunker, L. Hunter, T. A. Jung, T. E. Klein (New Jersey: World Scientific), pp. 451 – 462.
   Google Scholar
• WREN, J. D. andGARNER, H. R., 2002, Heuristics for identification of acronym-definition patterns within text: towards an automated construction of comprehensive acronym-definition dictionaries. Methods of Information in Medicine, 41(5), 426– 434.
   PubMedGoogle Scholar
• JENSSEN, T., et al., 2001, A literature network of human genes for high-throughput analysis of gene expression. Nature Genetics, 28, 21– 28.
   PubMed Web of Science ®Google Scholar
• STAPLEY, B. and BENOIT, G., 2000, Biobibliometrics: Information retrieval and Visualization from co-occurrences of gene names in medline abstracts. In Pacific Symposium on Biocomputing, Oahu, Hawaii, edited by Altman, R. B., Dunker, K. A., Hunter, L., Lauderdale, K., and Klein, T.E. (New Jersey: Word Scientific), pp. 526 – 537.
   Google Scholar
• BADER, G., et al., 2002, BIND-The biomolecular interaction network database. Nucleic Acids Research, 29, 242– 245.
   Google Scholar
• ZANZONI, A., et al., 2002, MINT: a Molecular INTeraction database. FEBS Letters, 513, 135– 140.
   PubMed Web of Science ®Google Scholar