On the public citation graph

Classification of Cytochrome P450 Activities Using Machine Learning Methods

https://doi.org/10.1021/mp900217x
0 signed · 73 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 See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.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/jps.2600721016openalex-snapshot
General Definition of Valence Delta-Values for Molecular Connectivity
inferredcites →https://doi.org/10.1007/bf02478259openalex-snapshot
A logical calculus of the ideas immanent in nervous activity
inferredcites →https://doi.org/10.1007/s11095-008-9807-9openalex-snapshot
Development of a New Predictive Model for Interactions with Human Cytochrome P450 2A6 Using Pharmacophore Ensemble/Support Vector Machine (PhE/SVM) Approach
inferredcites →https://doi.org/10.1016/0004-3702(96)00007-0openalex-snapshot
Artificial intelligence: A modern approach
inferredcites →https://doi.org/10.1016/0377-2217(85)90321-2openalex-snapshot
Classification and regression trees
inferredcites →https://doi.org/10.1016/c2009-0-19715-5openalex-snapshot
Data Mining: Practical Machine Learning Tools and Techniques
inferredcites →https://doi.org/10.1016/j.drudis.2006.10.005openalex-snapshot
Similarity-based virtual screening using 2D fingerprints
inferredcites →https://doi.org/10.1016/s0169-409x(02)00011-xopenalex-snapshot
Computer systems for the prediction of xenobiotic metabolism
inferredcites →https://doi.org/10.1016/s0300-483x(99)00207-3openalex-snapshot
Structural characteristics of human P450s involved in drug metabolism: QSARs and lipophilicity profiles
inferredcites →https://doi.org/10.1016/s1359-6446(97)01081-7openalex-snapshot
Properties of cytochrome P450 isoenzymes and their substrates Part 1: active site characteristics
inferredcites →https://doi.org/10.1016/s1359-6446(97)01085-4openalex-snapshot
Properties of cytochrome P450 isoenzymes and their substrates part 2: properties of cytochrome P450 substrates
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/ci00025a024openalex-snapshot
The Szeged Index and an Analogy with the Wiener Index
inferredcites →https://doi.org/10.1021/ci025584yopenalex-snapshot
The Chemistry Development Kit (CDK): An Open-Source Java Library for Chemo- and Bioinformatics
inferredcites →https://doi.org/10.1021/ci0500536openalex-snapshot
Prediction of Cytochrome P450 3A4, 2D6, and 2C9 Inhibitors and Substrates by Using Support Vector Machines
inferredcites →https://doi.org/10.1021/ci0600915openalex-snapshot
QSAR Modeling of in Vitro Inhibition of Cytochrome P450 3A4*
inferredcites →https://doi.org/10.1021/ci980137xopenalex-snapshot
Metric Validation and the Receptor-Relevant Subspace Concept
inferredcites →https://doi.org/10.1021/j100389a010openalex-snapshot
DREIDING: a generic force field for molecular simulations
inferredcites →https://doi.org/10.1021/ja00856a001openalex-snapshot
Characterization of molecular branching
inferredcites →https://doi.org/10.1021/ja01193a005openalex-snapshot
Structural Determination of Paraffin Boiling Points
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
inferredcites →https://doi.org/10.1023/a:1010933404324openalex-snapshot
Random Forests
inferredcites →https://doi.org/10.1042/bst0330796openalex-snapshot
Biodiversity of cytochrome P450 redox systems
inferredcites →https://doi.org/10.1063/1.1746554openalex-snapshot
Influence of Neighbor Bonds on Additive Bond Properties in Paraffins
inferredcites →https://doi.org/10.1093/nar/gkj067openalex-snapshot
DrugBank: a comprehensive resource for in silico drug discovery and exploration
inferredcites →https://doi.org/10.1111/j.1742-7843.2006.pto_471.xopenalex-snapshot
The Challenge of Predicting Drug Toxicityin silico
inferredcites →https://doi.org/10.1124/dmd.108.023507openalex-snapshot
Classification of Cytochrome P450 1A2 Inhibitors and Noninhibitors by Machine Learning Techniques
inferredcites →https://doi.org/10.1517/17425255.4.5.513openalex-snapshot
Computational prediction of drug binding and rationalisation of selectivity towards cytochromes P450
inferredcites →https://doi.org/10.2174/138920008784220664openalex-snapshot
Drugs Behave as Substrates, Inhibitors and Inducers of Human Cytochrome P450 3A4
inferredcites →https://doi.org/10.2174/138920009788499021openalex-snapshot
Development of Decision Tree Models for Substrates, Inhibitors, and Inducers of P-Glycoprotein
inferredcites →https://doi.org/10.2174/156802606778108942openalex-snapshot
Application of Support Vector Machines to In Silico Prediction of Cytochrome P450 Enzyme Substrates and Inhibitors
inferredcites →https://doi.org/10.2174/157340608784872226openalex-snapshot
Prediction of Cytochrome P450 2B6-Substrate Interactions Using Pharmacophore Ensemble/Support Vector Machine (PhE/SVM) Approach

What points at this work

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

inferred← citeshttps://doi.org/10.1002/9783527645121.ch1openalex-snapshot
Current Modeling Methods Used in QSAR/QSPR
inferred← citeshttps://doi.org/10.1002/minf.201100069openalex-snapshot
Selecting Relevant Descriptors for Classification by Bayesian Estimates: A Comparison with Decision Trees and Support Vector Machines Approaches for Disparate Data Sets
inferred← citeshttps://doi.org/10.1007/978-1-62703-059-5_5openalex-snapshot
Classification Models for Safe Drug Molecules
inferred← citeshttps://doi.org/10.1007/s11030-012-9364-3openalex-snapshot
QSAR classification of metabolic activation of chemicals into covalently reactive species
inferred← citeshttps://doi.org/10.1016/j.bmc.2012.01.049openalex-snapshot
Identification of cytochrome P450 2D6 and 2C9 substrates and inhibitors by QSAR analysis
inferred← citeshttps://doi.org/10.1016/j.chemolab.2013.08.003openalex-snapshot
A multidimensional analysis of machine learning methods performance in the classification of bioactive compounds
inferred← citeshttps://doi.org/10.1016/j.dmpk.2019.11.006openalex-snapshot
Computational prediction of cytochrome P450 inhibition and induction
inferred← citeshttps://doi.org/10.1016/j.eswa.2015.03.007openalex-snapshot
Multithreshold Entropy Linear Classifier: Theory and applications
inferred← citeshttps://doi.org/10.1016/j.pscia.2026.100110openalex-snapshot
Breaking through the radiation dilemma: development and clinical translation of anti-radiation drugs
inferred← citeshttps://doi.org/10.1016/j.ygeno.2018.12.007openalex-snapshot
Predicting drug-target interactions using Lasso with random forest based on evolutionary information and chemical structure
inferred← citeshttps://doi.org/10.1021/acs.jcim.5b00130openalex-snapshot
Rule-Based Prediction Models of Cytochrome P450 Inhibition
inferred← citeshttps://doi.org/10.1021/acs.jcim.5b00295openalex-snapshot
Ligand-Based Virtual Screening in a Search for Novel Anti-HIV-1 Chemotypes
inferred← citeshttps://doi.org/10.1021/acs.jcim.6b00426openalex-snapshot
Creating the New from the Old: Combinatorial Libraries Generation with Machine-Learning-Based Compound Structure Optimization
inferred← citeshttps://doi.org/10.1021/acsomega.9b02344openalex-snapshot
Lipophilic Metabolic Efficiency (LipMetE) and Drug Efficiency Indices to Explore the Metabolic Properties of the Substrates of Selected Cytochrome P450 Isoforms
inferred← citeshttps://doi.org/10.1021/bk-2016-1222.ch014openalex-snapshot
Steps Toward a Virtual Rat: Predictive Absorption, Distribution, Metabolism, and Toxicity Models
inferred← citeshttps://doi.org/10.1021/ci100072zopenalex-snapshot
Pharmaceutical Perspectives of Nonlinear QSAR Strategies
inferred← citeshttps://doi.org/10.1021/ci200028nopenalex-snapshot
Classification of Cytochrome P450 Inhibitors and Noninhibitors Using Combined Classifiers
inferred← citeshttps://doi.org/10.1021/ci200542mopenalex-snapshot
Computational Prediction of Metabolism: Sites, Products, SAR, P450 Enzyme Dynamics, and Mechanisms
inferred← citeshttps://doi.org/10.1021/ci400480sopenalex-snapshot
Fusing Dual-Event Data Sets for Mycobacterium tuberculosis Machine Learning Models and Their Evaluation
inferred← citeshttps://doi.org/10.1021/ci500694copenalex-snapshot
Combinatorial Consensus Scoring for Ligand-Based Virtual Fragment Screening: A Comparative Case Study for Serotonin 5-HT3A, Histamine H1, and Histamine H4Receptors
inferred← citeshttps://doi.org/10.1021/mp100279dopenalex-snapshot
Combinatorial QSAR Modeling of Human Intestinal Absorption
inferred← citeshttps://doi.org/10.1039/9781837070206-00430openalex-snapshot
Machine Learning in the Optimization of Pharmacokinetic Parameters
inferred← citeshttps://doi.org/10.1039/c5ra17196bopenalex-snapshot
An improved large-scale prediction model of CYP1A2 inhibitors by using combined fragment descriptors
inferred← citeshttps://doi.org/10.1063/1674-0068/29/cjcp1603039openalex-snapshot
Combination Computing of Support Vector Machine, Support Vector Regression and Molecular Docking for Potential Cytochrome P450 1A2 Inhibitors
inferred← citeshttps://doi.org/10.1093/bioinformatics/btv043openalex-snapshot
CypRules: a rule-based P450 inhibition prediction server
inferred← citeshttps://doi.org/10.1109/mci.2015.2437312openalex-snapshot
Weighted Tanimoto Extreme Learning Machine with Case Study in Drug Discovery
inferred← citeshttps://doi.org/10.1111/cbdd.13494openalex-snapshot
A combined drug discovery strategy based on machine learning and molecular docking
inferred← citeshttps://doi.org/10.1142/s146902681750002xopenalex-snapshot
Classification of Cytochrome P450 1A2 Inhibitors and Noninhibitors Based on Deep Belief Network
inferred← citeshttps://doi.org/10.1155/2017/9861752openalex-snapshot
CryoProtect: A Web Server for Classifying Antifreeze Proteins from Nonantifreeze Proteins
inferred← citeshttps://doi.org/10.1186/1758-2946-5-17openalex-snapshot
The influence of the inactives subset generation on the performance of machine learning methods
inferred← citeshttps://doi.org/10.1186/2050-6511-14-46openalex-snapshot
Assessing the translatability of In vivo cardiotoxicity mechanisms to In vitro models using causal reasoning
inferred← citeshttps://doi.org/10.1186/s13321-015-0088-0openalex-snapshot
Robust optimization of SVM hyperparameters in the classification of bioactive compounds
inferred← citeshttps://doi.org/10.1517/17425255.2010.489550openalex-snapshot
Machine learning algorithms for the prediction of hERG and CYP450 binding in drug development
inferred← citeshttps://doi.org/10.1517/17460441.2012.668182openalex-snapshot
Decision tree models for data mining in hit discovery
inferred← citeshttps://doi.org/10.2147/dddt.s86529openalex-snapshot
Navigating the chemical space of dipeptidyl peptidase-4 inhibitors
inferred← citeshttps://doi.org/10.3390/computation7020026openalex-snapshot
Exploring the Chemical Space of Cytochrome P450 Inhibitors Using Integrated Physicochemical Parameters, Drug Efficiency Metrics and Decision Tree Models
inferred← citeshttps://doi.org/10.3390/molecules17089283openalex-snapshot
Insights on Cytochrome P450 Enzymes and Inhibitors Obtained Through QSAR Studies
inferred← citeshttps://doi.org/10.4103/ijehe.ijehe_39_23openalex-snapshot
Extracting Hidden Patterns of Iranian User Trust in Social Networks Regarding Coronavirus Disease 2019 Using Data Mining Techniques
inferred← citeshttps://doi.org/10.4155/fmc-2016-0188openalex-snapshot
Hemopred: A Web Server for Predicting the Hemolytic Activity of Peptides
inferred← citeshttps://doi.org/10.5599/admet.2772openalex-snapshot
Leveraging machine learning models in evaluating ADMET properties for drug discovery and development
inferred← citeshttps://doi.org/10.70675/de51bc89z33fez456fz9467z959329cc603bopenalex-snapshot
Optimisation de méthodes de criblage virtuel et synthèse de molécules à visée thérapeutique pour le traitement des maladies auto-immunes.
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.