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On Combining Recursive Partitioning and Simulated Annealing To Detect Groups of Biologically Active Compounds
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Analysis of a Large Structure‐Activity Data Set Using Recursive Partitioning
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Classification and regression trees
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CANCER CHEMOTHERAPEUTIC AGENTS
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Topics in Applied Multivariate Analysis
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AUTOMATIC INTERACTION DETECTION
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LeadScope: Software for Exploring Large Sets of Screening Data
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Results of a New Classification Algorithm Combining K Nearest Neighbors and Recursive Partitioning
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A Novel Method for Building Regression Tree Models for QSAR Based on Artificial Ant Colony Systems
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Chemical Similarity Using Physiochemical Property Descriptors
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Rational Combinatorial Library Design. 3. Simulated Annealing Guided Evaluation (SAGE) of Molecular Diversity: A Novel Computational Tool for Universal Library Design and Database Mining
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Analysis of a Large Structure/Biological Activity Data Set Using Recursive Partitioning
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Automated Pharmacophore Identification for Large Chemical Data Sets
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Ant colony system: a cooperative learning approach to the traveling salesman problem
inferredcites →https://doi.org/10.1126/science.220.4598.671openalex-snapshot
Optimization by Simulated Annealing
inferredcites →https://doi.org/10.7551/mitpress/1090.001.0001openalex-snapshot
Adaptation in Natural and Artificial Systems
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Application of Data Mining Algorithms in Pharmaceutical Research and Development
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ChemInform Abstract: Combining Recursive Partitioning and Simulated Annealing to Detect Groups of Biologically Active Compounds.
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Structure–activity relationship analysis of N-benzoylpyrazoles for elastase inhibitory activity: A simplified approach using atom pair descriptors
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