On the public citation graph

Prediction of the Normal Boiling Points of Organic Compounds from Molecular Structures with a Computational Neural Network Model

0 signed · 78 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 See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.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/aic.690040325openalex-snapshot
Critical temperatures and pressures of hydrocarbons
inferredcites →https://doi.org/10.1002/aic.690060209openalex-snapshot
Critical temperatures and pressures of organic compounds
inferredcites →https://doi.org/10.1002/jps.2600641215openalex-snapshot
Molecular Connectivity II: Relationship to Water Solubility and Boiling Point
inferredcites →https://doi.org/10.1002/jps.2600690652openalex-snapshot
Computer assisted studies of chemical structure and biological function
inferredcites →https://doi.org/10.1002/jps.2600760325openalex-snapshot
Molecular Connectivity in Structure–activity Analysis
inferredcites →https://doi.org/10.1002/qsar.19850040304openalex-snapshot
A Method for Determining the Theoretical Carcinogenicity of Polycyclic Aromatic Hydrocarbons
inferredcites →https://doi.org/10.1002/qsar.19860050103openalex-snapshot
Distinguishing Atom Differences in a Molecular Graph Shape Index
inferredcites →https://doi.org/10.1002/qsar.19860050104openalex-snapshot
Physical Factors Contributing to Hydrophobic Constant π
inferredcites →https://doi.org/10.1002/ss.331openalex-snapshot
The Pennsylvania State University
inferredcites →https://doi.org/10.1016/0009-2614(82)80009-2openalex-snapshot
Highly discriminating distance-based topological index
inferredcites →https://doi.org/10.1016/0097-8485(79)80002-9openalex-snapshot
Search for all self-avoiding paths for molecular graphs
inferredcites →https://doi.org/10.1016/0169-7439(87)80104-1openalex-snapshot
Quantum chemistry program exchange
inferredcites →https://doi.org/10.1016/s0003-2670(96)00578-8openalex-snapshot
Prediction of gas chromatographic retention indices of alkylbenzenes
inferredcites →https://doi.org/10.1021/ac00083a005openalex-snapshot
Prediction of Gas Chromatographic Retention Times and Response Factors Using a General Qualitative Structure-Property Relationships Treatment
inferredcites →https://doi.org/10.1021/ac00134a025openalex-snapshot
Molecular shape and the prediction of high-performance liquid chromatographic retention indexes of polycyclic aromatic hydrocarbons
inferredcites →https://doi.org/10.1021/ac00220a013openalex-snapshot
Development and use of charged partial surface area structural descriptors in computer-assisted quantitative structure-property relationship studies
inferredcites →https://doi.org/10.1021/bk-1979-0112.ch004openalex-snapshot
Studies of Chemical Structure-Biological Activity Relations Using Pattern Recognition
inferredcites →https://doi.org/10.1021/ci00001a013openalex-snapshot
A comment on nomenclature and the unsaturated bond
inferredcites →https://doi.org/10.1021/ci00020a032openalex-snapshot
Prediction of boiling points and critical temperatures of industrially important organic compounds from molecular structure
inferredcites →https://doi.org/10.1021/ci00023a011openalex-snapshot
Automated Descriptor Selection for Quantitative Structure-Activity Relationships Using Generalized Simulated Annealing
inferredcites →https://doi.org/10.1021/ci00043a009openalex-snapshot
On molecular identification numbers
inferredcites →https://doi.org/10.1021/ci00049a002openalex-snapshot
A simple method for the representation, quantification, and comparison of the volumes and shapes of chemical compounds
inferredcites →https://doi.org/10.1021/ci9501507openalex-snapshot
Prediction of Aqueous Solubility for a Diverse Set of Heteroatom-Containing Organic Compounds Using a Quantitative Structure−Property Relationship
inferredcites →https://doi.org/10.1021/ci960085gopenalex-snapshot
Prediction of Supercritical Carbon Dioxide Solubility of Organic Compounds from Molecular Structure
inferredcites →https://doi.org/10.1021/ie50364a026openalex-snapshot
Calculation of Boiling Points of Aliphatic Hydrocarbons
inferredcites →https://doi.org/10.1021/ie51392a038openalex-snapshot
Linear Boiling Point Relationships
inferredcites →https://doi.org/10.1021/ja01193a006openalex-snapshot
Raman Spectra of Aqueous Solutions of Potassium Thiocyanate
inferredcites →https://doi.org/10.1021/ja01279a060openalex-snapshot
A System Correlating Molecular Structure of Organic Compounds with their Boiling Points. I. Aliphatic Boiling Point Numbers
inferredcites →https://doi.org/10.1021/ja01279a061openalex-snapshot
The Viscosities of Solutions of the Proteins of Horse Serum1
inferredcites →https://doi.org/10.1021/ja01567a049openalex-snapshot
Confirmation of the Intramolecular Nature of the Hofmann “Haloamide” Reaction by Double Labeling
inferredcites →https://doi.org/10.1021/jm00196a017openalex-snapshot
Chance factors in studies of quantitative structure-activity relationships
inferredcites →https://doi.org/10.1021/jp953224qopenalex-snapshot
Correlation of Boiling Points with Molecular Structure. 1. A Training Set of 298 Diverse Organics and a Test Set of 9 Simple Inorganics

What points at this work

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

inferred← citeshttps://doi.org/10.1002/0470845015.cqa007mopenalex-snapshot
Quantitative Structure–Property Relationships (QSPR)
inferred← citeshttps://doi.org/10.1002/9783527613106.biblioopenalex-snapshot
Bibliography
inferred← citeshttps://doi.org/10.1002/9783527618279.ch41copenalex-snapshot
Quantitative Structure‐Property Relationships
inferred← citeshttps://doi.org/10.1002/9783527628766.biblioopenalex-snapshot
Bibliography
inferred← citeshttps://doi.org/10.1002/chin.200005279openalex-snapshot
ChemInform Abstract: Prediction of the Normal Boiling Points of Organic Compounds from Molecular Structures with a Computational Neural Network Model.
inferred← citeshttps://doi.org/10.1002/qsar.200810101openalex-snapshot
Artificial Neural Network‐Based Quantitative Structural Property Relationship for Predicting Boiling Points of Refrigerants
inferred← citeshttps://doi.org/10.1007/978-3-031-37196-7_1openalex-snapshot
An Introduction to Machine Learning in Molecular Sciences
inferred← citeshttps://doi.org/10.1007/s00894-017-3552-0openalex-snapshot
Modeling molecular boiling points using computed interaction energies
inferred← citeshttps://doi.org/10.1007/s10822-006-9098-3openalex-snapshot
Caco-2 cell permeability modelling: a neural network coupled genetic algorithm approach
inferred← citeshttps://doi.org/10.1007/s10822-008-9209-4openalex-snapshot
Size-intensive descriptors
inferred← citeshttps://doi.org/10.1007/s11705-026-2675-1openalex-snapshot
ACGC plus: a general group contribution framework for diverse properties prediction
inferred← citeshttps://doi.org/10.1016/j.aichem.2024.100050openalex-snapshot
Applying graph neural network models to molecular property prediction using high-quality experimental data
inferred← citeshttps://doi.org/10.1016/j.fpc.2021.11.001openalex-snapshot
On prediction of melting points without computer simulation: A focus on energetic molecular crystals
inferred← citeshttps://doi.org/10.1016/j.jmgm.2011.06.010openalex-snapshot
Estimation of boiling points using density functional theory with polarized continuum model solvent corrections
inferred← citeshttps://doi.org/10.1016/j.jmgm.2013.04.007openalex-snapshot
Prediction of boiling points of organic compounds by QSPR tools
inferred← citeshttps://doi.org/10.1016/j.jmgm.2022.108149openalex-snapshot
Graph convolutional neural network applied to the prediction of normal boiling point
inferred← citeshttps://doi.org/10.1016/j.molliq.2017.06.039openalex-snapshot
Development of robust generalized models for estimating the normal boiling points of pure chemical compounds
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/10.1021/acsearthspacechem.3c00009openalex-snapshot
Machine Learning for Ionization Potentials and Photoionization Cross Sections of Volatile Organic Compounds
inferred← citeshttps://doi.org/10.1021/ci034129eopenalex-snapshot
Using Ensembles to Classify Compounds for Drug Discovery
inferred← citeshttps://doi.org/10.1021/ci050022aopenalex-snapshot
Interpreting Computational Neural Network QSAR Models: A Measure of Descriptor Importance
inferred← citeshttps://doi.org/10.1021/ci050282sopenalex-snapshot
On the Use of 1H and 13C 1D NMR Spectra as QSPR Descriptors
inferred← citeshttps://doi.org/10.1021/ci600541fopenalex-snapshot
Counting Clusters Using R-NN Curves
inferred← citeshttps://doi.org/10.1021/cr3004339openalex-snapshot
Descriptor Selection Methods in Quantitative Structure–Activity Relationship Studies: A Review Study
inferred← citeshttps://doi.org/10.1021/cr900238dopenalex-snapshot
Quantitative Correlation of Physical and Chemical Properties with Chemical Structure: Utility for Prediction
inferred← citeshttps://doi.org/10.1021/jp064332nopenalex-snapshot
Quantitative Structure−Activity (Affinity) Relationship (QSAR) Study on Protonation and Cationization of α-Amino Acids
inferred← citeshttps://doi.org/10.1023/a:1015505612789openalex-snapshot
Construction of Neural-Network Structure–Condition–Property Relationships: Modeling of Physicochemical Properties of Hydrocarbons
inferred← citeshttps://doi.org/10.1023/a:1021647507148openalex-snapshot
The use of saturated vapor pressure at standard temperature in correlations of physicochemical properties
inferred← citeshttps://doi.org/10.1023/a:1026084514236openalex-snapshot
QSAR Modeling of Genotoxicity on Non-congeneric Sets of Organic Compounds
inferred← citeshttps://doi.org/10.1039/b105183kopenalex-snapshot
Efficient estimation of second virial coefficients of fused hard-sphere molecules by an artificial neural networkElectronic Supplementary Information available. See http://www.rsc.org/suppdata/cp/b1/b105183k/
inferred← citeshttps://doi.org/10.1039/b408967gopenalex-snapshot
Estimation of melting points of pyridinium bromide ionic liquids with decision trees and neural networks
inferred← citeshttps://doi.org/10.1039/d3py00395gopenalex-snapshot
A review on the application of molecular descriptors and machine learning in polymer design
inferred← citeshttps://doi.org/10.1051/ro/2021134openalex-snapshot
Determining the best set of molecular descriptors for a Toxicity classification problem
inferred← citeshttps://doi.org/10.1080/00319100500061233openalex-snapshot
Prediction of normalized polarity parameter in binary mixed solvent systems using artificial neural networks
inferred← citeshttps://doi.org/10.1080/00319100601089679openalex-snapshot
Prediction dielectric constant of different ternary liquid mixtures at various temperatures and compositions using artificial neural networks
inferred← citeshttps://doi.org/10.1080/00319101003646561openalex-snapshot
Normal boiling points of pure molecular liquids: contributions of universal and specific interactions
inferred← citeshttps://doi.org/10.1186/s13321-018-0309-4openalex-snapshot
chemmodlab: a cheminformatics modeling laboratory R package for fitting and assessing machine learning models
inferred← citeshttps://doi.org/10.1205/cherd.03144openalex-snapshot
Regression Models Using Pattern Search Assisted Least Square Support Vector Machines
inferred← citeshttps://doi.org/10.12921/cmst.2015.21.04.004openalex-snapshot
Prediction the Normal Boiling Points of Primary, Secondary and Tertiary Liquid Amines from their Molecular Structure Descriptors
inferred← citeshttps://doi.org/10.1385/1-59259-285-6:325openalex-snapshot
Application of Neural Networks to Large Dataset QSAR, Virtual Screening, and Library Design
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/10.15771/0949-8214_2000_2_5openalex-snapshot
Modellierung des Wärmeübergangs beim Blasensieden in freier Konvektion mit künstlichen neuronalen Netzen : Teil I ; Literaturübersicht
inferred← citeshttps://doi.org/10.18637/jss.v018.i05openalex-snapshot
Chemical Informatics Functionality in R
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/10.35537/10915/63703openalex-snapshot
Una exploración a las relaciones cuantitativas entre datos espectrométricos y actividad a través de descriptores mecano-cuánticos
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.