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SLIF - Subcellular Location Image Finderand Departments of Biological Sciences, Biomedical Engineering, and Machine Learning Carnegie Mellon University, Pittsburgh, Pennsylvania, U.S.A. About This Service
An on-line summary of the architecture of SLIF can be found here. AcknowledgmentsThe initial development of SLIF was supported by grant 017396 from the Commonwealth of Pennsylvania Tobacco Settlement Fund. Further development is supported by National Institutes of Health grant R01 GM078622, and interfacing between SLIF and the National Center for Integrative Biomedical Informatics is supported by grant U54 DA021519. Papers from the Proceedings of the National Academy of Sciences (USA) used in development and testing of SLIF were obtained with the generous permission of Bruce Alberts and Ken Fulton of the National Academy of Sciences and with the kind assistance of David Lipman and his group at the PublicationsR. F. Murphy, M. Velliste, J. Yao, and G. Porreca (2001). Searching Online Journals for Fluorescence Microscope Images Depicting Protein Subcellular Location Patterns. Proceedings of the 2nd IEEE International Symposium on Bio-Informatics and Biomedical Engineering (BIBE 2001), pp. 119-128. William W. Cohen, Richard Wang, and Robert Murphy (2003). Understanding Captions in Biomedical Publications. Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2003), pp. 499-504. William W. Cohen, Zhenzhen Kou, and Robert F. Murphy (2003). Extracting Information from Text and Images for Location Proteomics. Proceedings of the 3nd ACM SIGKDD Workshop on Data Mining in Bioinformatics (BIOKDD 2003), pp. 2-9. Robert F. Murphy, Zhenzhen Kou, Juchang Hua, Matthew Joffe, and William W. Cohen (2004). Extracting and Structuring Subcellular Location Information from On-line Journal Articles: The Subcellular Location Image Finder Proceedings of IASTED International Conference on Knowledge Sharing and Collaborative Engineering (KSCE-2004). Z. Kou, W.W. Cohen, and R.F. Murphy (2005). High-recall protein entity recognition using a dictionary. Bioinformatics 21(suppl_1):i266-i273 (Proceedings of the 13th Annual International Conference on Intelligent Systems for Molecular Biology). People
Using SLIFImages found with SLIF can be queried via the SLIF Web database. |
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Last Updated: 07 May 2007 |
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