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Ties in Proximity and Clustering Compounds
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inferredcites →https://doi.org/10.1080/00401706.1990.10484648openalex-snapshot
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inferredcites →https://doi.org/10.1109/t-c.1973.223640openalex-snapshot
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inferredcites →https://doi.org/10.1111/j.1469-185x.1982.tb00376.xopenalex-snapshot
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inferred← citeshttps://doi.org/10.1002/chin.200120223openalex-snapshot
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inferred← citeshttps://doi.org/10.1002/jcc.24423openalex-snapshot
Using the gini coefficient to measure the chemical diversity of small‐molecule libraries
inferred← citeshttps://doi.org/10.1002/qsar.200510009openalex-snapshot
Data and Graph Mining in Chemical Space for ADME and Activity Data Sets
inferred← citeshttps://doi.org/10.1002/qsar.200510157openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/11816102_80openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/3-540-38076-0_9openalex-snapshot
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The Scaffold Tree: An Efficient Navigation in the Scaffold Universe
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Mean residence time by hierarchical clustering analysis
inferred← citeshttps://doi.org/10.1007/s00357-008-9004-xopenalex-snapshot
Solving Non-Uniqueness in Agglomerative Hierarchical Clustering Using Multidendrograms
inferred← citeshttps://doi.org/10.1007/s10844-022-00703-xopenalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s11030-006-9042-4openalex-snapshot
JEDA: Joint entropy diversity analysis. An information-theoretic method for choosing diverse and representative subsets from combinatorial libraries
inferred← citeshttps://doi.org/10.1016/b978-0-323-85713-0.00019-0openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.cam.2018.05.062openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.chroma.2009.04.064openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.dss.2005.02.004openalex-snapshot
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inferred← citeshttps://doi.org/10.1023/b:nepl.0000023449.95030.8fopenalex-snapshot
LSISOM — A Latent Semantic Indexing Approach to Self-Organizing Maps of Document Collections
inferred← citeshttps://doi.org/10.1039/c0md00165aopenalex-snapshot
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inferred← citeshttps://doi.org/10.1080/1062936x.2012.728994openalex-snapshot
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inferred← citeshttps://doi.org/10.1093/bioinformatics/btl562openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/bibe.2013.6701698openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/iceit.2010.5608424openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/imsccs.2006.55openalex-snapshot
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inferred← citeshttps://doi.org/10.1137/060676532openalex-snapshot
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inferred← citeshttps://doi.org/10.1139/y2012-002openalex-snapshot
Dunn’s index for cluster tendency assessment of pharmacological data sets
inferred← citeshttps://doi.org/10.1177/1460458216675661openalex-snapshot
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inferred← citeshttps://doi.org/10.1186/s13321-016-0114-xopenalex-snapshot
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inferred← citeshttps://doi.org/10.1504/ijdmb.2008.019092openalex-snapshot
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