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MODEL—molecular descriptor lab: A web‐based server for computing structural and physicochemical features of compounds

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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 Structure-Pharmacokinetic Relationships for Drug Distribution Properties by Using General Regression Neural Network

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Molecular Topology and Quantum Chemical Descriptors in the Study of Reversed-Phase Liquid Chromatography. Hydrogen-Bonding Behavior of Chalcones and Flavanones

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Support Vector Machines for ADME Property Classification

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MOPAC: A semiempirical molecular orbital program

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QSAR and ADME

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Classification of dopamine antagonists using functional feature hypothesis and topological descriptors

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BCUT descriptors to predicting affinity toward A3 adenosine receptors

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Linear free energy relationships on rate constants for the gas-phase reactions of hydroxyl radicals with PAHs and PCDD/Fs

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Modelling blood–brain barrier partitioning using Bayesian neural nets

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Drug design by machine learning: support vector machines for pharmaceutical data analysis

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Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings 1PII of original article: S0169-409X(96)00423-1. The article was originally published in Advanced Drug Delivery Reviews 23 (1997) 3–25. 1

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Computational approaches to the prediction of the blood–brain distribution

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Neural networks in drug discovery: have they lived up to their promise?

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A simple model to predict blood–brain barrier permeation from 3D molecular fields

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VolSurf: a new tool for the pharmacokinetic optimization of lead compounds

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Present and future in vitro approaches for drug metabolism

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Modeling Blood-Brain Barrier Partitioning Using the Electrotopological State

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Predicting Protein−Ligand Binding Affinities Using Novel Geometrical Descriptors and Machine-Learning Methods

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Effect of Molecular Descriptor Feature Selection in Support Vector Machine Classification of Pharmacokinetic and Toxicological Properties of Chemical Agents

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Prediction of P-Glycoprotein Substrates by a Support Vector Machine Approach

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Prediction of Cytochrome P450 3A4, 2D6, and 2C9 Inhibitors and Substrates by Using Support Vector Machines

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Topological Descriptors in Modeling the Antimalarial Activity of 4-(3‘,5‘-Disubstituted anilino)quinolines

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Effect of Selection of Molecular Descriptors on the Prediction of Blood−Brain Barrier Penetrating and Nonpenetrating Agents by Statistical Learning Methods

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Quadratic Shape Descriptors. 1. Rapid Superposition of Dissimilar Molecules Using Geometrically Invariant Surface Descriptors

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Prediction of the Brain−Blood Distribution of a Large Set of Drugs from Structurally Derived Descriptors Using Partial Least-Squares (PLS) Modeling

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Quantum-Chemical Descriptors in QSAR/QSPR Studies

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QSAR and Molecular Modeling Studies of Baclofen Analogues as GABAB Agonists. Insights into the Role of the Aromatic Moiety in GABAB Binding and Activation

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Designing Libraries with CNS Activity

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Predicting Blood−Brain Barrier Permeation from Three-Dimensional Molecular Structure

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Prediction of Genotoxicity of Chemical Compounds by Statistical Learning Methods

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Structure−Toxicity Relationships for the Effects to Tetrahymena pyriformis of Aliphatic, Carbonyl-Containing, α,β-Unsaturated Chemicals

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Gene Selection for Cancer Classification using Support Vector Machines

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A new scheme for electronegativity equalization as a source of electronic descriptors: Application to chemical reactivity

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Prediction of the Deral Penetration of Polycyclic Aromatic Hydrocarbons (PAHs): A hierarchical Qsar Approach

inferredcites →https://doi.org/10.1089/10665270260518317openalex-snapshot

Predicting CNS Permeability of Drug Molecules: Comparison of Neural Network and Support Vector Machine Algorithms

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Support vector machine classification and validation of cancer tissue samples using microarray expression data

inferredcites →https://doi.org/10.1093/bioinformatics/17.5.455openalex-snapshot

Predicting protein–protein interactions from primary structure

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Feature subset selection for splice site prediction

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Prediction of Torsade-Causing Potential of Drugs by Support Vector Machine Approach No funding was used to assist in conducting the study and the authors do not have any conflicts of interest directly relevant to the contents of the manuscript.

inferredcites →https://doi.org/10.1109/csb.2003.1227321openalex-snapshot

Discovering compact and highly discriminative features or combinations of drug activities using support vector machines

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Drug Discovery: A Historical Perspective

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High-Throughput Screening in Drug Metabolism and Pharmacokinetic Support of Drug Discovery

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Support Vector Machines in Combinatorial Chemistry

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QSPR as a means of predicting and understanding chemical and physical properties in terms of structure

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Topological Descriptors in Modeling the HIV Inhibitory Activity of 2-Aryl-3- pyridyl-thiazolidin-4-ones

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Physicochemical Descriptors in Property-Based Drug Design

What points at this work

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

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SVEEVA Descriptor Application to Peptide QSAR

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PaDEL‐descriptor: An open source software to calculate molecular descriptors and fingerprints

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QuBiLS‐MIDAS: A parallel free‐software for molecular descriptors computation based on multilinear algebraic maps

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Predicting the Enzymatic Hydrolysis Half‐lives of New Chemicals Using Support Vector Regression Models Based on Stepwise Feature Elimination

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QSAR study for cytotoxicity of diterpenoid tanshinones

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Quantitative Structure–Activity Relationships

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