On the public citation graph

QM/NN QSPR Models with Error Estimation: Vapor Pressure and LogP

0 signed · 110 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.

Claim with ORCID

Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.

See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/0470034378.ch6openalex-snapshot

The Thermochemistry of Alkanes and Cycloalkanes

inferredcites →https://doi.org/10.1002/aic.690401011openalex-snapshot

New group contribution method for estimating properties of pure compounds

inferredcites →https://doi.org/10.1002/jcc.540140502openalex-snapshot

Multicenter point charge model for high‐quality molecular electrostatic potentials from AM1 calculations

inferredcites →https://doi.org/10.1002/jcc.540140903openalex-snapshot

Assessment of methods used for predicting lipophilicity: Application to nucleosides and nucleoside bases

inferredcites →https://doi.org/10.1007/978-3-642-74140-1_18openalex-snapshot

Computation of Volumes and Surface Areas of Organic Compounds

inferredcites →https://doi.org/10.1007/bf00527479openalex-snapshot

Calcul th�orique des polarisabilit�s �lectroniques mol�culaires. Comparaison des diff�rentes m�thodes

inferredcites →https://doi.org/10.1007/s008940050027openalex-snapshot

Prediction of the n-Octanol/Water Partition Coefficient, logP, Using a Combination of Semiempirical MO-Calculations and a Neural Network

inferredcites →https://doi.org/10.1016/0022-2860(70)85028-1openalex-snapshot

Thermochemical kinetics

inferredcites →https://doi.org/10.1016/0045-6535(95)00084-lopenalex-snapshot

Group contribution methods to estimate water solubility of organic chemicals

inferredcites →https://doi.org/10.1016/s0040-4020(78)80003-9openalex-snapshot

Comprehensive organic chemistry

inferredcites →https://doi.org/10.1016/s0166-1280(97)00162-0openalex-snapshot

Statistical analysis of the molecular surface electrostatic potential: an approach to describing noncovalent interactions in condensed phases

inferredcites →https://doi.org/10.1016/s0169-409x(96)00423-1openalex-snapshot

Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings

inferredcites →https://doi.org/10.1021/acsinfocus.7e8012openalex-snapshot

Neural Networks for Chemists

inferredcites →https://doi.org/10.1021/ci00009a013openalex-snapshot

Estimation of aqueous solubility of organic molecules by the group contribution approach. Application to the study of biodegradation

inferredcites →https://doi.org/10.1021/ci00019a016openalex-snapshot

Estimation of normal boiling points from group contributions

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/ci960028nopenalex-snapshot

Assessment of n-Octanol/Water Partition Coefficient: When Is the Assessment Reliable?

inferredcites →https://doi.org/10.1021/ci970289copenalex-snapshot

QSPR Prediction of Vapor Pressure from Solely Theoretically-Derived Descriptors

inferredcites →https://doi.org/10.1021/ci9801318openalex-snapshot

Enhanced 3D-Databases: A Fully Electrostatic Database of AM1-Optimized Structures

inferredcites →https://doi.org/10.1021/jm9706776openalex-snapshot

A Scoring Scheme for Discriminating between Drugs and Nondrugs

inferredcites →https://doi.org/10.1049/pbce053e_ch1openalex-snapshot

Neural networks: an introduction

inferredcites →https://doi.org/10.1093/jaoac/62.6.1364bopenalex-snapshot

Lange’s Handbook of Chemistry

inferredcites →https://doi.org/10.1515/9783110226119.123openalex-snapshot

Systematic Introduction

inferredcites →https://doi.org/10.5860/choice.26-6311openalex-snapshot

Adaptive pattern recognition and neural networks

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1002/9781394159338.ch10openalex-snapshot

Utilization of Computational Methods for Rational Development of Nanoemulsions, Polymeric Micelles, and Dendrimers Drug Delivery Systems

inferred← citeshttps://doi.org/10.1002/9783527621286.ch15openalex-snapshot

Prediction of LogPwith Property‐Based Methods

inferred← citeshttps://doi.org/10.1002/9783527628766.biblioopenalex-snapshot

Bibliography

inferred← citeshttps://doi.org/10.1002/9783527806539.ch3openalex-snapshot

Prediction of Physicochemical Properties of Compounds

inferred← citeshttps://doi.org/10.1002/aic.12718openalex-snapshot

Prediction of the n‐hexane/water and 1‐octanol/water partition coefficients for environmentally relevant compounds using molecular simulation

inferred← citeshttps://doi.org/10.1002/aic.16678openalex-snapshot

An architecture of deep learning in QSPR modeling for the prediction of critical properties using molecular signatures

inferred← citeshttps://doi.org/10.1002/aic.17997openalex-snapshot

Improved vapor pressure prediction from PR + COSMOSAC EOS using normal boiling temperature

inferred← citeshttps://doi.org/10.1002/cjoc.20020200805openalex-snapshot

Radial Basis Function Neural Networks Based QSPR for the Prediction of log P

inferred← citeshttps://doi.org/10.1002/jccs.201900232openalex-snapshot

Prediction of some thermodynamic properties of sulfonamide drugs using genetic algorithm‐multiple linear regressions

inferred← citeshttps://doi.org/10.1002/jps.21494openalex-snapshot

Calculation of Molecular Lipophilicity: State-of-the-Art and Comparison of LogP Methods on more than 96,000 Compounds

inferred← citeshttps://doi.org/10.1002/minf.201200131openalex-snapshot

Applicability Domain Dependent Predictive Uncertainty in QSAR Regressions

inferred← citeshttps://doi.org/10.1002/qsar.200610112openalex-snapshot

QSPR ofn‐Octanol/Water Partition Coefficient of Nonionic Organic Compounds Using Extended Topochemical Atom (ETA) Indices

inferred← citeshttps://doi.org/10.1007/978-1-4419-0197-2_1openalex-snapshot

Artificial Neural Network Modeling of the Environmental Fate and Ecotoxicity of Chemicals

inferred← citeshttps://doi.org/10.1007/978-3-319-33290-1_5openalex-snapshot

Computational Models

inferred← citeshttps://doi.org/10.1007/s00894-003-0153-xopenalex-snapshot

Local molecular properties and their use in predicting reactivity

inferred← citeshttps://doi.org/10.1007/s00894-008-0320-1openalex-snapshot

The use of local surface properties for molecular superimposition

inferred← citeshttps://doi.org/10.1007/s00894-014-2322-5openalex-snapshot

Industrial applications of in silico ADMET

inferred← citeshttps://doi.org/10.1007/s10822-010-9401-1openalex-snapshot

Toward better QSAR/QSPR modeling: simultaneous outlier detection and variable selection using distribution of model features

inferred← citeshttps://doi.org/10.1007/s10822-011-9504-3openalex-snapshot

Lions and tigers and bears, oh my! Three barriers to progress in computer-aided molecular design

inferred← citeshttps://doi.org/10.1016/b0-08-045044-x/00144-9openalex-snapshot

Rule-Based Systems to Predict Lipophilicity

inferred← citeshttps://doi.org/10.1016/b0-08-045044-x/00259-5openalex-snapshot

Quantum Mechanical Calculations in Medicinal Chemistry: Relevant Method or a Quantum Leap Too Far?

inferred← citeshttps://doi.org/10.1016/b978-0-12-821092-5.00012-7openalex-snapshot

Deep learning in QSPR modeling for the prediction of critical properties

inferred← citeshttps://doi.org/10.1016/j.cbi.2025.111644openalex-snapshot

Preliminary prediction of toxicologically relevant physicochemical properties of Novichoks: the first comparative in silico studies

inferred← citeshttps://doi.org/10.1016/j.ceja.2025.100750openalex-snapshot

GRAPPA—A hybrid graph neural network for predicting pure component vapor pressures

inferred← citeshttps://doi.org/10.1016/j.ces.2025.121269openalex-snapshot

Boiling point enhanced vapor pressure prediction by Antoine-based quantitative structure–property relationship

inferred← citeshttps://doi.org/10.1016/j.compchemeng.2006.10.001openalex-snapshot

Rapid QSPR model development technique for prediction of vapor pressure of organic compounds

inferred← citeshttps://doi.org/10.1016/j.comptc.2013.11.021openalex-snapshot

A software tool for visualization of molecular face (VMF) by improving marching cubes algorithm

inferred← citeshttps://doi.org/10.1016/j.fluid.2006.05.020openalex-snapshot

SVRC–QSPR model for predicting saturated vapor pressures of pure fluids

inferred← citeshttps://doi.org/10.1016/j.fluid.2015.07.005openalex-snapshot

The effect of fluorination on the physical properties and the free energies of hydration of 1-alcohols

inferred← citeshttps://doi.org/10.1016/j.fluid.2020.112595openalex-snapshot

Estimation of vapor pressures of liquid and solid organic and organometallic compounds at 298.15 K

inferred← citeshttps://doi.org/10.1016/j.fuel.2021.121437openalex-snapshot

Machine learning-quantitative structure property relationship (ML-QSPR) method for fuel physicochemical properties prediction of multiple fuel types

inferred← citeshttps://doi.org/10.1016/j.jhazmat.2021.127497openalex-snapshot

Simulating the impact of volatilization on atmospheric concentrations of pesticides with the 3D chemistry-transport model CHIMERE: Method development and application to S-metolachlor and folpet

inferred← citeshttps://doi.org/10.1016/j.jmgm.2004.03.012openalex-snapshot

QSAR and QSPR based solely on surface properties?

inferred← citeshttps://doi.org/10.1016/s0039-9140(01)00537-9openalex-snapshot

Non-linear QSAR modeling by using multilayer perceptron feedforward neural networks trained by back-propagation

inferred← citeshttps://doi.org/10.1016/s0048-9697(02)00467-9openalex-snapshot

QSPR models for physicochemical properties of polychlorinated diphenyl ethers

inferred← citeshttps://doi.org/10.1016/s0065-7743(01)36065-7openalex-snapshot

Chapter 25. ADME by computer

inferred← citeshttps://doi.org/10.1016/s0097-8485(01)00093-6openalex-snapshot

Radial basis function neural network based QSPR for the prediction of critical pressures of substituted benzenes

inferred← citeshttps://doi.org/10.1016/s0169-409x(03)00117-0openalex-snapshot

Prediction of physicochemical properties based on neural network modelling

inferred← citeshttps://doi.org/10.1016/s0378-5173(02)00101-1openalex-snapshot

Modelling partitioning of sparingly soluble drugs in a two-phase liquid system

inferred← citeshttps://doi.org/10.1016/s1001-8042(08)60042-1openalex-snapshot

Prediction of thermodynamic properties of actinide and lanthanide compounds

inferred← citeshttps://doi.org/10.1016/s1359-6446(04)03365-3openalex-snapshot

Predicting aqueous solubility from structure

inferred← citeshttps://doi.org/10.1021/acs.chemrev.8b00728openalex-snapshot

Concepts of Artificial Intelligence for Computer-Assisted Drug Discovery

inferred← citeshttps://doi.org/10.1021/acs.estlett.4c00524openalex-snapshot

Screening Environmentally Benign Ionic Liquids for CO 2 Absorption Using Representation Uncertainty-Based Machine Learning

inferred← citeshttps://doi.org/10.1021/acs.iecr.6b02040openalex-snapshot

Prediction of pH Effect on the Octanol–Water Partition Coefficient of Ionizable Pharmaceuticals

inferred← citeshttps://doi.org/10.1021/acs.jcim.5b00110openalex-snapshot

The Relative Importance of Domain Applicability Metrics for Estimating Prediction Errors in QSAR Varies with Training Set Diversity

inferred← citeshttps://doi.org/10.1021/acs.jcim.8b00114openalex-snapshot

General Approach to Estimate Error Bars for Quantitative Structure–Activity Relationship Predictions of Molecular Activity

inferred← citeshttps://doi.org/10.1021/acs.jcim.8b00542openalex-snapshot

Deep Confidence: A Computationally Efficient Framework for Calculating Reliable Prediction Errors for Deep Neural Networks

inferred← citeshttps://doi.org/10.1021/acs.jcim.9b00212openalex-snapshot

Calculating the Partition Coefficients of Organic Solvents in Octanol/Water and Octanol/Air

inferred← citeshttps://doi.org/10.1021/acs.jcim.9b00297openalex-snapshot

Reliable Prediction Errors for Deep Neural Networks Using Test-Time Dropout

inferred← citeshttps://doi.org/10.1021/acs.jctc.6b00449openalex-snapshot

Calculating Partition Coefficients of Small Molecules in Octanol/Water and Cyclohexane/Water

inferred← citeshttps://doi.org/10.1021/ci0004614openalex-snapshot

A Quantum Mechanical/Neural Net Model for Boiling Points with Error Estimation

inferred← citeshttps://doi.org/10.1021/ci000462wopenalex-snapshot

Neural Network Based Temperature-Dependent Quantitative Structure Property Relations (QSPRs) for Predicting Vapor Pressure of Hydrocarbons

inferred← citeshttps://doi.org/10.1021/ci010315dopenalex-snapshot

Novel Methods for the Prediction of logP, pKa, and logD

inferred← citeshttps://doi.org/10.1021/ci0103222openalex-snapshot

A Temperature-Dependent Quantum Mechanical/Neural Net Model for Vapor Pressure

inferred← citeshttps://doi.org/10.1021/ci010323uopenalex-snapshot

A Fuzzy ARTMAP Based on Quantitative Structure−Property Relationships (QSPRs) for Predicting Aqueous Solubility of Organic Compounds

inferred← citeshttps://doi.org/10.1021/ci0103267openalex-snapshot

Fuzzy ARTMAP and Back-Propagation Neural Networks Based Quantitative Structure−Property Relationships (QSPRs) for Octanol−Water Partition Coefficient of Organic Compounds

inferred← citeshttps://doi.org/10.1021/ci034215eopenalex-snapshot

New Molecular Descriptors Based on Local Properties at the Molecular Surface and a Boiling-Point Model Derived from Them

inferred← citeshttps://doi.org/10.1021/ci049744copenalex-snapshot

Generalized Fragment-Substructure Based Property Prediction Method

inferred← citeshttps://doi.org/10.1021/ci0498564openalex-snapshot

A Partition Coefficient Calculation Method with the SFED Model

inferred← citeshttps://doi.org/10.1021/ci050025nopenalex-snapshot

Surface-Integral QSPR Models: Local Energy Properties

inferred← citeshttps://doi.org/10.1021/ci0503210openalex-snapshot

In Silico Prediction of Buffer Solubility Based on Quantum-Mechanical and HQSAR- and Topology-Based Descriptors

inferred← citeshttps://doi.org/10.1021/ci200276vopenalex-snapshot

Conformation-Dependent QSPR Models: logPOW

inferred← citeshttps://doi.org/10.1021/ci300095xopenalex-snapshot

Predicting the Sites and Energies of Noncovalent Intermolecular Interactions Using Local Properties

inferred← citeshttps://doi.org/10.1021/ci400482eopenalex-snapshot

Using Random Forest To Model the Domain Applicability of Another Random Forest Model

inferred← citeshttps://doi.org/10.1021/ci800151mopenalex-snapshot

Critical Assessment of QSAR Models of Environmental Toxicity against Tetrahymena pyriformis: Focusing on Applicability Domain and Overfitting by Variable Selection

inferred← citeshttps://doi.org/10.1021/ie0205290openalex-snapshot

Group-Contribution-Based Estimation of Octanol/Water Partition Coefficient and Aqueous Solubility

inferred← citeshttps://doi.org/10.1021/je049732nopenalex-snapshot

Prediction of Subcooled Vapor Pressures of Nonpolar Organic Compounds Using a One-Parameter QSPR

inferred← citeshttps://doi.org/10.1021/jm011027bopenalex-snapshot

Descriptors, Physical Properties, and Drug-Likeness

inferred← citeshttps://doi.org/10.1039/b418834aopenalex-snapshot

Prediction of vapour pressure using descriptors derived from molecular dynamics

inferred← citeshttps://doi.org/10.1039/c1cp20110gopenalex-snapshot

Using molecular simulation to predict solute solvation and partition coefficients in solvents of different polarity

inferred← citeshttps://doi.org/10.1039/c3cp44284eopenalex-snapshot

Prediction of 1-octanol–water and air–water partition coefficients for nitro-aromatic compounds from molecular dynamics simulations

inferred← citeshttps://doi.org/10.1061/(asce)cf.1943-5509.0001471openalex-snapshot

Evaluation of the Deterioration of Ceramic Claddings by Application of Artificial Neural Networks

inferred← citeshttps://doi.org/10.1063/1.4730040openalex-snapshot

Direct calculation of 1-octanol–water partition coefficients from adaptive biasing force molecular dynamics simulations

inferred← citeshttps://doi.org/10.1063/1.4992111openalex-snapshot

Dissipative particle dynamics: Systematic parametrization using water-octanol partition coefficients

inferred← citeshttps://doi.org/10.1080/00268970902994293openalex-snapshot

Prediction of the vapor pressure of some halogenated methyl-phenyl ether (anisole) compounds using linear and nonlinear QSPR methods

inferred← citeshttps://doi.org/10.1080/1062936031000073135openalex-snapshot

Quantitative structure-property relationships for vapor pressures of polybrominated diphenyl ethers

inferred← citeshttps://doi.org/10.1080/10629360410001665857openalex-snapshot

Data evaluations and quantitative predictive models for vapor pressures of polycyclic aromatic hydrocarbons at different temperatures

inferred← citeshttps://doi.org/10.1080/17460441.2017.1344210openalex-snapshot

Lipophilicity and biomimetic properties to support drug discovery

inferred← citeshttps://doi.org/10.1186/1752-153x-3-s1-o7openalex-snapshot

Calculation of molecular lipophilicity: state of the art and comparison of methods on more than 96000 compounds

inferred← citeshttps://doi.org/10.1186/1758-2946-6-34openalex-snapshot

Using beta binomials to estimate classification uncertainty for ensemble models

inferred← citeshttps://doi.org/10.1385/mb:27:2:139openalex-snapshot

Neural Networks as Robust Tools in Drug Lead Discovery and Development

inferred← citeshttps://doi.org/10.1897/01-363openalex-snapshot

Quantitative structure-property relationships for prediction of boiling point, vapor pressure, and melting point

inferred← citeshttps://doi.org/10.2741/3788openalex-snapshot

Theoretical and computational approaches to ligand-based drug discovery

inferred← citeshttps://doi.org/10.4155/fmc-2018-0435openalex-snapshot

Lipophilicity in Drug Design: An Overview of Lipophilicity Descriptors in 3D-QSAR Studies

inferred← citeshttps://doi.org/10.48550/arxiv.1908.03569openalex-snapshot

Concepts and Applications of Conformal Prediction in Computational Drug Discovery

inferred← citeshttps://doi.org/10.6023/a22010017openalex-snapshot

Accurate Prediction of the Boiling Point of Organic Molecules by Multi-Component Heterogeneous Learning Model

Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.