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A practical strategy for directed compound acquisition
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Oprea T. (Ed), Wiley-VCH, New York. This work discusses the pragmatic issues concerning the acquisition of compounds to support pharmacological screening and describes the reprocessing and filtering of compound files, initial compound selection, and assessment of diversity. The work also describes some of the software used to implement the strategy.
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Maggiora G.M., Shanmugasundaram V., Lajiness M.S., Doman T.N., and Schulz M.W. A practical strategy for directed compound acquisition. In: Oprea T. (Ed). Cheminformatics Aspects in Drug Discovery (2004), Wiley-VCH, New York 317-332. This work discusses the pragmatic issues concerning the acquisition of compounds to support pharmacological screening and describes the reprocessing and filtering of compound files, initial compound selection, and assessment of diversity. The work also describes some of the software used to implement the strategy.
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Cheminformatics Aspects in Drug Discovery
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Maggiora, G.M.1
Shanmugasundaram, V.2
Lajiness, M.S.3
Doman, T.N.4
Schulz, M.W.5
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Dunbar J.B. Compound acquisition strategies. Pac Symp Biocomput (2000) 555-565
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Martin Y.C. Diverse viewpoints on computational aspects of molecular diversity. J Comb Chem 3 (2001) 231-250
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Bajorath J. (Ed), Humana Press, Totowa, NJ
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Maggiora G.M., and Shanmugasundaram V. Molecular similarity measures. In: Bajorath J. (Ed). Chemoinformatics: Concepts, Methods, and Tools for Drug Discovery (2004), Humana Press, Totowa, NJ 1-50
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Chemoinformatics: Concepts, Methods, and Tools for Drug Discovery
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Maggiora, G.M.1
Shanmugasundaram, V.2
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8
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33644861784
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Diversity in medicinal chemistry space
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This review describes various molecular representations that lead to the definition of chemical space, drug space or activity space and strategies for compound selection. Potential sources of diversity that could be used to explore the medicinal space in quest of new drugs are also described.
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Gorse A.D. Diversity in medicinal chemistry space. Curr Top Med Chem 6 (2006) 3-18. This review describes various molecular representations that lead to the definition of chemical space, drug space or activity space and strategies for compound selection. Potential sources of diversity that could be used to explore the medicinal space in quest of new drugs are also described.
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Curr Top Med Chem
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Gorse, A.D.1
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9
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30844443282
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Molecular similarity and diversity in chemoinformatics: from theory to applications
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Approaches used to define and describe the concepts of molecular similarity and diversity in the context of chemoinformatics are described. Applications and problems involving molecular similarity and diversity are also discussed.
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Maldonado A.G., et al. Molecular similarity and diversity in chemoinformatics: from theory to applications. Mol Divers 10 (2006) 39-79. Approaches used to define and describe the concepts of molecular similarity and diversity in the context of chemoinformatics are described. Applications and problems involving molecular similarity and diversity are also discussed.
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Mol Divers
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Maldonado, A.G.1
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10
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33846020557
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Similarity metrics and descriptor spaces - Which combinations to choose?
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A description of possible combinations of molecular descriptors and analysis methods that can be combined to preselect compounds for virtual screening applications is provided. Factors that influence decisions as to the selection of descriptors and analysis methods are discussed along with applications that compare and contrast methods and their performance in different situations.
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Glen R.C., and Adams S.E. Similarity metrics and descriptor spaces - Which combinations to choose?. Qsar Comb Sci 25 (2006) 1133-1142. A description of possible combinations of molecular descriptors and analysis methods that can be combined to preselect compounds for virtual screening applications is provided. Factors that influence decisions as to the selection of descriptors and analysis methods are discussed along with applications that compare and contrast methods and their performance in different situations.
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Qsar Comb Sci
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Glen, R.C.1
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Cross K.P., Myatt G., Yang C., Fligner M.F., Verducci J.S., and Blower P.E. Finding discriminating structural features by reassembling common building blocks. J Med Chem 46 (2003) 4770-4775
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Daylight Chemical Information Systems Inc. 120 Vantis, Suite 550, Aliso Viejo, California 92656, USA (www.daylight.com).
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Daylight Chemical Information Systems Inc. 120 Vantis, Suite 550, Aliso Viejo, California 92656, USA (www.daylight.com).
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14
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0029783934
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Neighborhood behavior: a useful concept for validation of "molecular diversity" descriptors
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Patterson D.E., Cramer R.D., Ferguson A.M., Clark R.D., and Weinberger L.E. Neighborhood behavior: a useful concept for validation of "molecular diversity" descriptors. J Med Chem 39 (1996) 3049-3059
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Analysis of data fusion methods in virtual screening: theoretical model
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Whittle M., Gillet V.J., Willett P., and Loesel J. Analysis of data fusion methods in virtual screening: theoretical model. J Chem Inf Mod 46 (2006) 2193-2205
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Whittle M., Gillet V.J., Willett P., and Loesel J. Analysis of data fusion methods in virtual screening: similarity and group fusion. J Chem Inf Mod 46 (2006) 2206-2219
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Willett P. Similarity-based virtual screening using 2D fingerprints. Drug Discov Today 11 (2006) 1046-1053
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Willett, P.1
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Review of applications of the data-fusion approach to ligand-based virtual screening with a focus on the combination of multiple similarity searches and the combination of multiple machine-learning techniques and how they can improve the effectiveness of searching when compared with single-screening procedure.
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Willett P. Enhancing the effectiveness of ligand-based virtual screening using data fusion. QSAR Comb Sci 25 (2006) 1143-1152. Review of applications of the data-fusion approach to ligand-based virtual screening with a focus on the combination of multiple similarity searches and the combination of multiple machine-learning techniques and how they can improve the effectiveness of searching when compared with single-screening procedure.
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QSAR Comb Sci
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Willett, P.1
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Enhancing the effectiveness of similarity-based virtual screening using nearest-neighbour information
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Hert J., Willett P., Wilton D.J., Acklin P., Azzaoui K., Jacoby E., and Schuffenhauer A. Enhancing the effectiveness of similarity-based virtual screening using nearest-neighbour information. J Med Chem 48 (2005) 7049-7054
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Hert, J.1
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Azzaoui, K.5
Jacoby, E.6
Schuffenhauer, A.7
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Wale N, Watson I, Karypis G: Comparison of descriptor spaces for chemical compound classification and retrieval, knowledge and information systems. in press.
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Wale N, Watson I, Karypis G: Comparison of descriptor spaces for chemical compound classification and retrieval, knowledge and information systems. in press. Shows how machine learning based on different substructural features exhibits different performance across different targets. Various exhaustively produced algorithmic substructural features are shown to offer uniformly good performance.
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21
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12144283651
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Hit-directed nearestneighbor searching
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Description of strategy used for identifying compounds for follow-up screening subsequent to an initial HTS campaign against targets where no 3D structural information is available and preliminary SAR models do not exist. The approach uses several different representations of chemistry space and identifies compounds for follow-up screening that are probably to provide the best overall coverage of the chemistry spaces considered. The results suggest that the use of multiple searches based upon a variety of molecular representations provides an effective way of identifying more hits in HDNN searches of chemistry spaces than can be realized with single searches.
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Shanmugasundaram V., Maggiora G.M., and Lajiness M.S. Hit-directed nearestneighbor searching. J Med Chem 48 (2005) 240-248. Description of strategy used for identifying compounds for follow-up screening subsequent to an initial HTS campaign against targets where no 3D structural information is available and preliminary SAR models do not exist. The approach uses several different representations of chemistry space and identifies compounds for follow-up screening that are probably to provide the best overall coverage of the chemistry spaces considered. The results suggest that the use of multiple searches based upon a variety of molecular representations provides an effective way of identifying more hits in HDNN searches of chemistry spaces than can be realized with single searches.
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J Med Chem
, vol.48
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Shanmugasundaram, V.1
Maggiora, G.M.2
Lajiness, M.S.3
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22
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0036567220
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A modification of the Jaccard-Tanimoto similarity index for diverse selection of chemical compounds using binary strings
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This review demonstrates how the standard Tanimoto similarity coefficient applied to sequential compound selection can introduce a size bias in the set of selected molecules. A solution is presented that is capable of removing this bias.
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Fligner M.A., Verducci J.S., and Blower P.E. A modification of the Jaccard-Tanimoto similarity index for diverse selection of chemical compounds using binary strings. Technometrics 44 (2004) 110-119. This review demonstrates how the standard Tanimoto similarity coefficient applied to sequential compound selection can introduce a size bias in the set of selected molecules. A solution is presented that is capable of removing this bias.
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Technometrics
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Fligner, M.A.1
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Higgs R.E., Bemis K.G., Watson I.A., and Wikel J.H. Experimental designs for selecting molecules from large chemical databases. J Chem Inf Comp Sci 37 (1997) 861-870
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33645265985
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Clustering methods and their uses in computational chemistry
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Lipkowitz K.B., and Boyd D.B. (Eds), Wiley and Sons, New York. This is a very good overview of different clustering methods commonly used in chemical applications, with an emphasis on descriptor-based methods.
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Downs G.M., and Barnard J.M. Clustering methods and their uses in computational chemistry. In: Lipkowitz K.B., and Boyd D.B. (Eds). Reviews in Computational Chemistry vol. 18 (2002), Wiley and Sons, New York 1-40. This is a very good overview of different clustering methods commonly used in chemical applications, with an emphasis on descriptor-based methods.
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Reviews in Computational Chemistry
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Downs, G.M.1
Barnard, J.M.2
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49949152447
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Accelrys Incorporated, 10188 Telesis Court, Suite 100, San Diego, CA 92121, USA (www.scitegic.com).
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Accelrys Incorporated, 10188 Telesis Court, Suite 100, San Diego, CA 92121, USA (www.scitegic.com).
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49949152029
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Symyx Incorporated, 3100 Central Expressway, Santa Clara, CA 95051, USA (www.mdli.com).
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Symyx Incorporated, 3100 Central Expressway, Santa Clara, CA 95051, USA (www.mdli.com).
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49949152483
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Leadscope Incorporated, 1393 Dublin Road, Columbus, OH 43214, USA (www.leadscope.com).
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Leadscope Incorporated, 1393 Dublin Road, Columbus, OH 43214, USA (www.leadscope.com).
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49949151935
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Tripos, 1699 South Hanley Road, St. Louis, MO 63144, USA (www.tripos.com).
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Tripos, 1699 South Hanley Road, St. Louis, MO 63144, USA (www.tripos.com).
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49949151815
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ChemNavigator, 6126 Nancy Ridge Drive, Suite 117, San Diego, CA 92121, USA (www.chemnavigator.com).
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ChemNavigator, 6126 Nancy Ridge Drive, Suite 117, San Diego, CA 92121, USA (www.chemnavigator.com).
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Muresan S., and Sadowski J. "In house likeness": comparison of large compound collections using artificial neural networks. J Chem Inf Model 45 (2005) 888-893
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Sadowski, J.2
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Key aspects of the Novartis compound collection project for the compilation of a comprehensive chemogenomics drug discovery screening collection
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Description of the compound collection enrichment and enhancement project at Novartis that integrates corporate internal combinatorial compound synthesis and external compound acquisition activities to build up a comprehensive screening collection. The strategy integrates focused and diversity-based compound sets from synthetic and natural product sources to attack the so-called druggable and undruggable targets.
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Jacoby E., Schuffenhauer A., Popov M., Azzaoui K., Havill B., Schopfer U., Engeloch C., Stanek J., Acklin P., Rigollier P., et al. Key aspects of the Novartis compound collection project for the compilation of a comprehensive chemogenomics drug discovery screening collection. Curr Top Med Chem 5 4 (2005) 397-411. Description of the compound collection enrichment and enhancement project at Novartis that integrates corporate internal combinatorial compound synthesis and external compound acquisition activities to build up a comprehensive screening collection. The strategy integrates focused and diversity-based compound sets from synthetic and natural product sources to attack the so-called druggable and undruggable targets.
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(2005)
Curr Top Med Chem
, vol.5
, Issue.4
, pp. 397-411
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Jacoby, E.1
Schuffenhauer, A.2
Popov, M.3
Azzaoui, K.4
Havill, B.5
Schopfer, U.6
Engeloch, C.7
Stanek, J.8
Acklin, P.9
Rigollier, P.10
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Livingston D, Lease T: Behind the scenes at the nih molecular libraries small molecule repository. Society of Biomolecular Sciences Newsletter 2005 (http://www.sbsonline.org/publications/news/issues/2005_12/index.php).
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Livingston D, Lease T: Behind the scenes at the nih molecular libraries small molecule repository. Society of Biomolecular Sciences Newsletter 2005 (http://www.sbsonline.org/publications/news/issues/2005_12/index.php). NIH is funding screening centers at nine academic institutions. The screening collection is needed to provide adequate input, and adequate diversity coverage for the available screening capacity. A very good discussion is presented of the considerations used to identify molecules for acquisition, including Lipinski scores, predicted solubility, target specific considerations and diversity. Good description of a current state-of-the-art effort.
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36
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Pursuing the leadlikeness concept in pharmaceutical research
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Hann M.M., and Oprea T.I. Pursuing the leadlikeness concept in pharmaceutical research. Curr Opin Chem Biol 8 (2004) 255-263
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Oprea T.I., Davis A.M., Teague S.J., and Leeson P.D. Is there a difference between leads and drugs? A historical perspective. J Chem Inf Comp Sci 41 (2001) 1308-1315
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Lipinski C.A. Drug-like properties and the causes of poor solubility and poor permeability. J Pharmacol Toxicol Methods 44 (2001) 235-249. Seminal paper in the field, widely cited and implemented.
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Assessment of the consistency of medicinal chemists in reviewing sets of compounds
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Medicinal chemists were found to be inconsistent in the compounds they rejected as being undesirable. The inconsistency arises from the subjective analysis that all humans utilize when considering 'data sets' of any kind. This has important implications for pharmaceutical project teams where individual medicinal chemists review lists of primary screening hits to identify those compounds suitable for follow-up. This can also have an impact on computational chemists who are developing models for assessing the desirability or attractiveness of different classes of compounds for lead discovery.
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Lajiness M.S., Maggiora G.M., and Shanmugasundaram V. Assessment of the consistency of medicinal chemists in reviewing sets of compounds. J Med Chem 47 20 (2004) 4891-4896. Medicinal chemists were found to be inconsistent in the compounds they rejected as being undesirable. The inconsistency arises from the subjective analysis that all humans utilize when considering 'data sets' of any kind. This has important implications for pharmaceutical project teams where individual medicinal chemists review lists of primary screening hits to identify those compounds suitable for follow-up. This can also have an impact on computational chemists who are developing models for assessing the desirability or attractiveness of different classes of compounds for lead discovery.
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(2004)
J Med Chem
, vol.47
, Issue.20
, pp. 4891-4896
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Lajiness, M.S.1
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