Method and system for interpreting and validating experimental data with automated reasoning
Patent 6813615 Issued on November 2, 2004. Estimated Expiration Date: September 6, 2020. Estimated Expiration Date is calculated based on simple USPTO term provisions. It does not account for terminal disclaimers, term adjustments, failure to pay maintenance fees, or other factors which might affect the term of a patent.
A method and system for interpreting experimental data with automated reasoning. Domain specific knowledge is acquired from one or more pharmaceutical information sources. A semantic representation of the domain specific knowledge is created meeting a desired set of criteria. Pharmaceutical data from a knowledge database is classified with the semantic representation, allowing construction of a set of reasons for any classified pharmaceutical data. The set of reasons may help interpret the classified pharmaceutical data to remove errors, such as “physical errors” and “biological errors”. Removing such errors helps improve fusion of knowledge from multiple data, information and knowledge sources which incorporates activity and selectivity against a target, desired pharmacokinetic and toxicity properties enabling selection of potential pharmaceutical compounds. The method and system may improve identification, selection, validation and screening of new real or virtual pharmaceutical compounds or may be used to provide bioinformatic techniques for storing and manipulating pharmaceutical knowledge.
Other References
W. Salmonsen, K.Y.C. Mok, P. Kolatkar, S. Subbiah, “BioJAKE: A Tool for the Creation, Visualization and Manipulation of Metabolic Pathways,” Bioinformatics Centre, Jan. 1999, pp. 392-400.
W. Fujibuchi, K. Sato, H. Ogata, S. Goto, M. Kanehisa, “KEGG and DBGET/LinkDB: Integration of Biological Relationships in Divergent Molecular Biology Data,” Institute for Chemical Research, Kyoto University, 1998, pp. 35-40.
P.D. Karp, “Database Links are a Foundation for Interoperability,” Aug. 1996, pp. 273-279, TibTech, (vol. 14).
Paley, P.D. Karp, “Adapting EcoCyc for Use on the World Wide Web,” Gene 172 (1996) GC43-GC50, Mar. 28, 1996, pp. 43-50.
P.D. Karp, “Computer Corner-Metabolic Databases,” Mar. 23, 1998, pp. 114-116, TIBS.
C. Allee, “Data Management for Automated Drug Discovery Laboratories,” XP-002134398, Aug. 21, 1996, pp. 307-310.
A.R. Kerlavage, W. FitzHugh, A. Glodek, J. Kelley, J. Scott, R. Shirley, G. Sutton, Man Wai-Chiu, O. White, M.D. Adams, “Data Management and Analysis for High-Throughput DNA Sequencing Projects,” IEEE Engineering in Medicine and Biology, Nov./Dec. 1995, pp. 710-717.
K.A. Giuliano, D. Lansing Taylor, “Flourescent-Protein Biosensors: New Tools for Drug Discovery,” Mar. 1998, pp. 135-140, TibTech (vol. 16).
Cellomics Vital Knowledge, Smarter Screening and Lead Optimization with Cellomics™ High content Screening Systems and Informatics Tools In An Integrated Drug Discovery Solution. 1999.
K.A. Giuliano, R.L. DeBiasio, R. T.Dunlay, A. Gough, J.M. Volosky, J. Zock, G.N. Pavlakis, D. Lansing Taylor, “High-Content Screening: A New Approach to Easing Key Bottlenecks in the Drug Discovery Process,” Journal of Biomolecular Screening, 1997, pp. 249-259, (vol. 2, No. 4) Winter.
B.R. Conway, L.K. Minor, J.Z. Xu, J.W. Gunnet, R. DeBiasio, M.R. D'Andrea, R. Rubin, R. DeBiasio, K. Giuliano, L. Zhou, K.T. Demarest, “Quantification of G-aprotein Couples Receptor Internalization Using G-Protein Coupled Receptor-Green Flourescent Protein Conjugates with the ArrayScan™ High-Content Screening System,” Journal of Biomolecular Screening, 1999, pp. 75-86, (vol. , No. 2), Apr.
Ethan B. Arutunian, Deirdre R. Meldrum, Neal A. Friedman and Stephen E. Moody, “Flexible Software Architecture for User-Interface and Machine Control in Laboratory Automation,” BioTechniques 25:698-705 (Oct. 1998).
Blaschke et al., “Automatic Extraction Of Biological Information From Scientific Text: Protein-Protein Interactions”, ISMB'99, pp. 60-67.
Chen et al., “Automatic Construction Of Networks Of Concepts Characterizing Document Databases”, IEEE Transactions On Systems, Man, And Cybernetics, vol. 22, No. 5, Sep./Oct. 1992, pp. 885-902.
Chen et al., “An Algorithmic Approach To Concept Exploration In A Large Knowledge Network (Automatic Thesaurus Consultation): Symbolic Branch-And-Bound Search vs. Connectionist Hopfield Net Activation”, Journal Of The American Society For Information Science, 3615), 1995, pp. 348-369.
Craven et al., “Constructing Biological Knowledge Bases By Extracting Information From Text Sources”, ISMB'99, pp. 77-86.
Gordon et al., “Toward Discovery Support Systems: A Replication, Re-Examination, And Extension Of Swanson's Work On Literature-Based Discovery Of A Connection Between Raynaud's And Fish Oil”, Journal Of The American Society For Information Science, 47(2), 1996, pp. 116-128.
Swanson et al., “An Interactive System For Finding Complementary Literatures: A Stimulus To Scientrlic Discovery”, Artifical Intelligence 91 (1997), pp. 183-203.
Overbeek et al., “Representation of Function: The Next Step”, Pub. On-line Jan. 31, 1997, www.mcs.anl.gov/compbio/publications/function_pap.html, pp. 1-13.
September 6, 2020. Estimated Expiration Date is calculated based on simple USPTO term provisions. It does not account for terminal disclaimers, term adjustments, failure to pay maintenance fees, or other factors which might affect the term of a patent.
