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Development of a Spectral Clustering Method for the Analysis of Molecular Data Sets
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Quantitative Measures of Change Based on Feature Organization: Eigenvalues and Eigenvectors
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Clustering Files of Chemical Structures Using the Fuzzy k -Means Clustering Method
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A Hierarchical Clustering Approach for Large Compound Libraries
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Database Clustering with a Combination of Fingerprint and Maximum Common Substructure Methods
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Use of Structure−Activity Data To Compare Structure-Based Clustering Methods and Descriptors for Use in Compound Selection
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The Information Content of 2D and 3D Structural Descriptors Relevant to Ligand-Receptor Binding
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The Characterization of Chemical Structures Using Molecular Properties. A Survey
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A Robust Clustering Method for Chemical Structures
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HierS: Hierarchical Scaffold Clustering Using Topological Chemical Graphs
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Biological spectra analysis: Linking biological activity profiles to molecular structure
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What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1002/chin.200749224openalex-snapshot
Development of a Spectral Clustering Method for the Analysis of Molecular Data Sets.
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Discovery of novel inhibitors of Trypanosoma cruzi trans-sialidase from in silico screening
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Investigation of the Use of Spectral Clustering for the Analysis of Molecular Data
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Using Electrophysiology and In Silico Three-Dimensional Modeling to Reduce Human Ether-à-go-go Related Gene K + Channel Inhibition in a Histamine H3 Receptor Antagonist Program
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Integration of phenotypic metadata and protein similarity in Archaea using a spectral bipartitioning approach
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A Similarity‐based Data‐fusion Approach to the Visual Characterization and Comparison of Compound Databases
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The complete genome sequence of Staphylothermus marinus reveals differences in sulfur metabolism among heterotrophic Crenarchaeota
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Pharmacological affinity fingerprints derived from bioactivity data for the identification of designer drugs
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Genomic Characterization of Methanomicrobiales Reveals Three Classes of Methanogens
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Novel Insights into the Diversity of Catabolic Metabolism from Ten Haloarchaeal Genomes
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Multi-view spectral clustering and its chemical application
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Catch the next designer drug: bioactivity data derived pharmacological affinity fingerprints and performance in similarity searching and unsupervised clustering
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Classification with binary gene expressions
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A Robust Topology-Based Algorithm for Gene Expression Profiling
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Additional file 1 of Pharmacological affinity fingerprints derived from bioactivity data for the identification of designer drugs
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