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Chemical Graph Theory for Property Modeling in QSAR and QSPR—Charming QSAR & QSPR
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/jcc.23022openalex-snapshot
Coral: QSPR modeling of rate constants of reactions between organic aromatic pollutants and hydroxyl radical
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Best Practices for QSAR Model Development, Validation, and Exploitation
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ISIDA Property‐Labelled Fragment Descriptors
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GTM‐Based QSAR Models and Their Applicability Domains
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Substructural fragments: an universal language to encode reactions, molecular and supramolecular structures
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Outliers in SAR and QSAR: Is unusual binding mode a possible source of outliers?
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Fragment-based QSAR: perspectives in drug design
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QSAR models for ACE-inhibitor activity of tri-peptides based on representation of the molecular structure by graph of atomic orbitals and SMILES
inferredcites →https://doi.org/10.1016/j.apm.2018.03.016openalex-snapshot
Valency-based topological descriptors of chemical networks and their applications
inferredcites →https://doi.org/10.1016/j.bmc.2005.05.002openalex-snapshot
An approach toward the problem of outliers in QSAR
inferredcites →https://doi.org/10.1016/j.chemosphere.2019.124604openalex-snapshot
Predicting the acute ecotoxicity of chemical substances by machine learning using graph theory
inferredcites →https://doi.org/10.1021/acs.jcim.5b00206openalex-snapshot
Beware of R 2 : Simple, Unambiguous Assessment of the Prediction Accuracy of QSAR and QSPR Models
inferredcites →https://doi.org/10.1021/acs.jcim.6b00088openalex-snapshot
A Historical Excursus on the Statistical Validation Parameters for QSAR Models: A Clarification Concerning Metrics and Terminology
inferredcites →https://doi.org/10.1021/ci000068yopenalex-snapshot
QSAR Comparative Study of Wiener Descriptors for Weighted Molecular Graphs
inferredcites →https://doi.org/10.1021/ci00025a001openalex-snapshot
Chemical Graphs: Looking Back and Glimpsing Ahead
inferredcites →https://doi.org/10.1021/ci00047a033openalex-snapshot
Applications of graph theory in chemistry
inferredcites →https://doi.org/10.1021/ci00057a005openalex-snapshot
SMILES, a chemical language and information system. 1. Introduction to methodology and encoding rules
inferredcites →https://doi.org/10.1021/ci00062a008openalex-snapshot
SMILES. 2. Algorithm for generation of unique SMILES notation
inferredcites →https://doi.org/10.1021/ci020388copenalex-snapshot
Anti-HIV Activity of HEPT, TIBO, and Cyclic Urea Derivatives: Structure−Property Studies, Focused Combinatorial Library Generation, and Hits Selection Using Substructural Molecular Fragments Method
inferredcites →https://doi.org/10.1021/ci600476ropenalex-snapshot
Stochastic versus Stepwise Strategies for Quantitative Structure−Activity Relationship GenerationHow Much Effort May the Mining for Successful QSAR Models Take?
inferredcites →https://doi.org/10.1021/ci700443vopenalex-snapshot
Combinatorial QSAR Modeling of Chemical Toxicants Tested against Tetrahymena pyriformis
inferredcites →https://doi.org/10.1021/ci9901340openalex-snapshot
Modeling of Ion Complexation and Extraction Using Substructural Molecular Fragments
inferredcites →https://doi.org/10.1021/cr0780006openalex-snapshot
Some New Trends in Chemical Graph Theory
inferredcites →https://doi.org/10.1088/1742-6596/1139/1/012060openalex-snapshot
Computation of topological Indices using python program for chemical graph structure
inferredcites →https://doi.org/10.1111/j.1747-0285.2011.01117.xopenalex-snapshot
coral Software: QSAR for Anticancer Agents
inferredcites →https://doi.org/10.1134/s0012501617060033openalex-snapshot
A graph theory method for determining the basis of homodesmic reactions for acyclic chemical compounds
inferredcites →https://doi.org/10.1134/s0036024416020345openalex-snapshot
Graph theory in structure–property correlations
inferredcites →https://doi.org/10.1201/9780203642627-23openalex-snapshot
Development and Evaluation of QSARs for Ecotoxic Endpoints: The Benzene Response-Surface Model for Tetrahymena Toxicity
inferredcites →https://doi.org/10.1515/ci.2001.23.1.18bopenalex-snapshot
IUPAC Stability Constants Database
inferredcites →https://doi.org/10.2174/092986708785747607openalex-snapshot
Random Molecular Fragment Methods in Computational Medicinal Chemistry
inferredcites →https://doi.org/10.2174/138620708785739907openalex-snapshot
Building a Chemical Space Based on Fragment Descriptors
inferredcites →https://doi.org/10.2174/157340908785747465openalex-snapshot
ISIDA - Platform for Virtual Screening Based on Fragment and Pharmacophoric Descriptors
inferredcites →https://doi.org/10.48550/arxiv.1201.0490openalex-snapshot
Scikit-learn: Machine Learning in Python
inferredcites →https://doi.org/10.6060/mhc2012.121104sopenalex-snapshot
New Approach for Accurate QSPR Modeling of Metal Complexation: Application to Stability Constants of Complexes of Lanthanide Ions Ln3+, Ag+, Zn2+, Cd2+ and Hg2+ with Organic Ligands in Water
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Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Exploring carboxylic acid collectors for rhodochrosite flotation: Machine learning-driven QSAR in concert with quantum chemical calculations
inferred← citeshttps://doi.org/10.1021/acssuschemeng.5c03294openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/ijcnn55064.2022.9892419openalex-snapshot
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Vertex energy of some integral graphs
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