References
-
Agrawal, R., Imieli
$\'n$ ski, T., and Swami, A. (1993). Mining association rules between sets of items in large databases. In Proceedings of the 1993 ACM SIGMOD international conference on Management of data 207-216 - Andrade, M.A. and Valencia, A. (1998). Automatic extraction of keywords from scientific text: application to the knowledge domain of protein families. Bioinformatics 14(7), 600-607 https://doi.org/10.1093/bioinformatics/14.7.600
- Andrade, M.,A., and Borka, P. (2000). Automated extraction of information in molecular biology. FEBS Letters 476, 12-17 https://doi.org/10.1016/S0014-5793(00)01661-6
- Blaschke, C., Andrade, M.A., Ouzounis, C., and Valencia, A. (1999). Automatic extraction of biological information from scientific text: protein-protein interactions. In Proc. Int. Conf. Intell. Syst. Mol. Biol., 60-67
- Blaschke, C. and Valencia, A. (2002). The frame-based module of the SUISEKI information extraction system. IEEE Intelligent Systems 17(2), 14-20
- Chiang, J.,H., Yu, H.,C., and Hsu, H., J. (2004). GIS: a biomedical text-mining system for gene information discovery. Bioinformatics 20(1), 120-121 https://doi.org/10.1093/bioinformatics/btg369
- Christie, K.R., Weng, S., Balakrishnan, R., Costanzo, M.C., Dolinski, K., Dwight, S.S., Engel, S.R., Feierbach, B., Fisk, D.G., Hirschman, J.E., Hong, E.L., Issel-Tarver, L., Nash, R., Sethuraman, A., Starr, B., Theesfeld, C.L., Andrada, R., Binkley, G., Dong, Q., Lane, C., Schroeder, M., Botstein, D., and Cherry, J.M. (2004). Saccharomyces Genome Database (SGD) Provides tools to identify and analyze sequences from Saccharomyces cerevisiae and related sequences from other organisms. Nucleic Acids Res. 32(1), D311-D314 䝊䭈䉒弲〰㉟瘱㉮㕟ㄶ㌮灤昀 䝊䭈䉒弲〰㉟瘱㉮㕟ㄶ㌮瑩昀 䝊䭈䉒弲〰㉟瘱㉮㔀 瑫浳 Ȁ᐀ 堰?⨀ Ȁጀ ቇ䩋䡂剟㈰〲彶ㄲ渵 樀 敮最 Ȁጀ 퀰?⨀ Ȁሀ ᅇ䩋䡂剟㈰〲彶ㄲ渵 돀?⨀ 塨?⨀ ࡌ?⨀ 섚 돐 잖⨀ 잖⨀ が?⨀ 餚 덐 䁌?⨀ 頚 砚 https://doi.org/10.1093/nar/gkh033
- Daraselia, N., Yuryev, A., Egorov, S., Novichkova, S., Nikitin, A., and Mazo, I. (2004). Extracting human protein interactions from MEDLINE using a full-sentence parser. Bioinformatics 20(5), 604-611 https://doi.org/10.1093/bioinformatics/btg452
- Friedman, C., Kra, P., Yu, H., Krauthammer, M.,and Rzhetsky, A. (2001). GENIES: a natural-language processing system for the extraction of molecular pathways from journal articles. Bioinformatics 17(SuppI.1), S74-S82 https://doi.org/10.1093/bioinformatics/17.suppl_1.S74
- Humphreys, B.L., Lindberg, D.A., Schoolman, H.M., and Barnett, G.O. (1998). The Unified Medical Language System: an informatics research collaboration. J. Am. Med. Inform. Assoc. 5(1), 1-11 https://doi.org/10.1136/jamia.1998.0050001
- Hwang, Y.S., Chung, H.J, and Rim, H.C. (2003). Weighted Probabilistic Sum Model based on Decision Tree Decomposition for Text Chunking, Journal of Computer Processing of Oriental Languages 16(1), 1 -20 https://doi.org/10.1142/S0219427903000796
- Kim, J.D., Ohta, T., Tateisi, Y., and Tsujii, J. (2003). GENIA corpus - semantically annotated corpus for bio-textmining. Bioinformatics 19(SuppI. 1), i180-182 https://doi.org/10.1093/bioinformatics/btg1023
- Lee, K.J., Hwang, Y.S., and Rim, H.C. (2003). Two-Phase Biomedical NE Recognition based on SVMs. In Proc. of ACL 2003 Workshop on Natural Language Processing in Biomedicine, 33-40
- Mewes, H.W., Amid, C., Arnold, R., Frishman, D., Guldener, U., Mannhaupt, G., Munsterkotter, M., Pagel, P., Strack, N., Stumpflen, V., Warfsmann, J., and Ruepp, A. (2004). MIPS: analysis and annotation of proteins from whole genomes. Nucleic Acids Res. 32(1), D41-D44 https://doi.org/10.1093/nar/gkh092
- Oyama, T., Kitano, K., Satou, K., and Ito, T. (2002). Extraction of knowledge on proteinprotein interaction by association rule discovery. Bioinformatics 18, 705-714 https://doi.org/10.1093/bioinformatics/18.5.705
- Perez-lratxeta, C., Bork, P., and Andrade, M.A. (2000). XpIorMed: a tool for exploring MEDLINE abstracts. Trends Biochem Sci. 26, 573-575 https://doi.org/10.1016/S0968-0004(01)01926-0
- Press, W.H., Flannery, B.P., Teukolsky, S.A., and Vetterling, W.T. (1998). Numerical recipes in C (Cambridge: Cambridge University Press)
- Quinlan, J.R. (1993). C4.5: Programs for machine learning (San Francisco: Morgan Kaufmann Publishers Inc.).
- Safran, M., ChaIifa-Caspi, V., Shmueli, O., Olender, T., Lapidot, M., Rosen, N., Shmoish, M., Peter, Y., Glusman, G., Feldmesser, E., Adato, A., Peter, I., Khen, M., Atarot, T., Groner, Y., and Lancet, D. (2003). Human gene-centric databases at the Weizmann institute of science: GeneCards, UDB, CroW 21 and HORDE. Nucleic Acids Res. 31(1), 142-146 https://doi.org/10.1093/nar/gkg050
- Slonim, N. and Tishby, N. (2000). Document clustering using word clusters via the information bottleneck method. In Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval, 208-215
- Stapley, B.J. and Benoit, G. (2000). Biobibliometrics: information retrieval and visualization from co-occurrences of gene names in Medline abstracts. In Proc. of Pac. Symp. Biocomput., 529-40
- Tanabe, L., Scherf, U., Smith, L.H., Lee. J.K., Hunter. L., and Weinstein, J.N. (1999). MedMiner: an internet text-mining tool for biomedical information, with application to gene expression profiling. BioTechniques 27, 1210-1217
- Yu, L. and Liu, H. (2003). Feature selection for high dimensional data: a fast correlation-based filter solution. In Proceeding of the 20th International Conference on Machine Learning, 856-863