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Molecular Distance−Edge Vector (μ): An Extension from Alkanes to Alcohols

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What this work says

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

inferredcites →https://doi.org/10.1007/bf01164639openalex-snapshot
Molecular topological index: An extension to heterosystems
inferredcites →https://doi.org/10.1007/bf01200821openalex-snapshot
Generalized molecular descriptors
inferredcites →https://doi.org/10.1021/ja00856a001openalex-snapshot
Characterization of molecular branching
inferredcites →https://doi.org/10.1021/ja00856a002openalex-snapshot
Importance of nonbonded attraction in the stereochemistry of the SN2' reaction
inferredcites →https://doi.org/10.1021/ja01193a006openalex-snapshot
Raman Spectra of Aqueous Solutions of Potassium Thiocyanate
inferredcites →https://doi.org/10.1351/pac198855020199openalex-snapshot
Topological indices based on topological distances in molecular graphs

What points at this work

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

inferred← citeshttps://doi.org/10.1002/9781118906842.ch13openalex-snapshot
Gas Separation by Polymer Membranes
inferred← citeshttps://doi.org/10.1002/9783527613106.biblioopenalex-snapshot
Bibliography
inferred← citeshttps://doi.org/10.1002/9783527628766.biblioopenalex-snapshot
Bibliography
inferred← citeshttps://doi.org/10.1002/chin.200005276openalex-snapshot
ChemInform Abstract: Molecular Distance—Edge Vector (μ): An Extension from Alkanes to Alcohols.
inferred← citeshttps://doi.org/10.1002/cjoc.20010190808openalex-snapshot
MEDV‐13 for QSAR Studies on the COX‐2 Inhibition by Indomethacin Amides and Esters
inferred← citeshttps://doi.org/10.1002/jccs.200100041openalex-snapshot
A Novel MHDV Descriptor for Dipeptide QSAR Studies
inferred← citeshttps://doi.org/10.1002/jccs.200100106openalex-snapshot
Application of Wavelet Neural Network to the Prediction of Gas Chromatographic Retention Indices of Alkanes
inferred← citeshttps://doi.org/10.1002/jccs.200100137openalex-snapshot
On Structural Parameterization and Molecular Modeling of Peptide Analogues by Molecular Electronegativity Edge Vector (VMEE): Estimation and Prediction for Biological Activity of Dipeptides
inferred← citeshttps://doi.org/10.1002/qsar.200430894openalex-snapshot
Highly Correlating Distance‐Connectivity‐Based Topological Indices. 2: Prediction of 15 Properties of a Large Set of Alkanes Using a Stepwise Factor Selection‐Based PCR Analysis
inferred← citeshttps://doi.org/10.1007/s11458-007-0012-xopenalex-snapshot
A new two-dimensional approach to quantitative prediction for collision cross-section of more than 110 singly protonated peptides by a novel moecular electronegativity-interaction vector through quantitative structure-spectrometry relationship studies
inferred← citeshttps://doi.org/10.1016/j.chemolab.2004.03.002openalex-snapshot
Quantitative structure–property relationship studies for estimating boiling points of alcohols using calculated molecular descriptors with radial basis function neural networks
inferred← citeshttps://doi.org/10.1016/j.chemolab.2014.06.015openalex-snapshot
QSPR study on the relative retention time of polybrominated diphenyl ethers (PBDEs) by using molecular distance-edge vector index
inferred← citeshttps://doi.org/10.1016/j.theochem.2004.04.010openalex-snapshot
Molecular electronegativity-distance vector (MEDV-4): a two-dimensional QSAR method for the estimation and prediction of biological activities of estradiol derivatives
inferred← citeshttps://doi.org/10.1016/j.theochem.2007.10.008openalex-snapshot
Estimation and prediction on retention times of components from essential oil of Paulownia tomentosa flowers by molecular electronegativity-distance vector (MEDV)
inferred← citeshttps://doi.org/10.1016/s0169-7439(01)00146-0openalex-snapshot
Molecular structural vector description and retention index of polycyclic aromatic hydrocarbons
inferred← citeshttps://doi.org/10.1039/c4ra14178dopenalex-snapshot
QSPR study on the photolysis half-life of PCDD/Fs adsorbed on spruce (Picea abies (L.) Karst.) needle surfaces under sunlight irradiation by using a molecular distance-edge vector index
inferred← citeshttps://doi.org/10.1080/10406638.2015.1028588openalex-snapshot
Predicting the Aqueous Solubility of PCDD/Fs by using QSPR Method Based on the Molecular Distance-Edge Vector Index
inferred← citeshttps://doi.org/10.1139/v09-109openalex-snapshot
QSPR studies on normal boiling points and molar refractivities of organic compounds by correlation-ranking-based PCR and PC–ANN analyses of new topological indices
inferred← citeshttps://doi.org/10.1186/1752-153x-8-36openalex-snapshot
QSPR study on the octanol/air partition coefficient of polybrominated diphenyl ethers by using molecular distance-edge vector index
inferred← citeshttps://doi.org/10.1360/982004-252openalex-snapshot
A novel molecular distance edge vector as applied to chemical modeling of quantitative structure-retention relationships: Various gas chromatographic retention behaviors of polychlorinated dibenzofurans on different polarity-varying stationary phases
inferred← citeshttps://doi.org/10.1360/csb2005-50-9-875openalex-snapshot
新分子距边矢量用于环境毒物多氯代二苯并呋喃的定量结构保留相关建模
inferred← citeshttps://doi.org/10.1365/s10337-006-0054-0openalex-snapshot
Estimation and Prediction of Relative Retention Indices of Polychlorinated Naphthalenes in GC with Molecular Electronegativity Distance Vector
inferred← citeshttps://doi.org/10.1365/s10337-007-0382-8openalex-snapshot
QSRR Study for Gas and Liquid Chromatographic Retention Indices of Polyhalogenated Biphenyls Using Two 2D Descriptors
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/10.4028/scientific5/amr.455-456.925openalex-snapshot
QSPR Studies on n-Octanol/Water Partition Coefficient of Polychlorinated Biphenyls by Using Artificial Neural Network
inferred← citeshttps://doi.org/10.4028/scientific5/amr.455-456.930openalex-snapshot
QSPR Study on the Soil-Water Partition Coefficient of Polychlorinated Biphenyls by Using Artificial Neural Network
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