| scholarly article | Q13442814 |
| P8978 | DBLP publication ID | journals/jcisd/ZhengT00 |
| P356 | DOI | 10.1021/CI980033M |
| P698 | PubMed publication ID | 10661566 |
| P5875 | ResearchGate publication ID | 220523245 |
| P50 | author | Alexander Tropsha | Q4720252 |
| P2093 | author name string | Zheng W | |
| P2860 | cites work | Equation of State Calculations by Fast Computing Machines | Q5384234 |
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| Genetic algorithms: principles of natural selection applied to computation | Q51652724 | ||
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| Quantitative Structure-Activity Relationships in Carboquinones and Benzodiazepines Using Counter-Propagation Neural Networks | Q52331766 | ||
| A 3D-QSAR Study of Anticoccidial Triazines Using Molecular Shape Analysis | Q52336961 | ||
| Taboo search: an approach to the multiple minima problem | Q52350711 | ||
| Quantitative structure-activity relationships by neural networks and inductive logic programming. II. The inhibition of dihydrofolate reductase by triazines | Q52373580 | ||
| Quantitative structure-activity relationships by neural networks and inductive logic programming. I. The inhibition of dihydrofolate reductase by pyrimidines. | Q52373584 | ||
| Application of neural networks: quantitative structure-activity relationships of the derivatives of 2,4-diamino-5-(substituted-benzyl)pyrimidines as DHFR inhibitors | Q52415934 | ||
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| The Collinearity Problem in Linear Regression. The Partial Least Squares (PLS) Approach to Generalized Inverses | Q56454402 | ||
| The Correlation of Biological Activity of Plant Growth Regulators and Chloromycetin Derivatives with Hammett Constants and Partition Coefficients | Q63987734 | ||
| A molecular shape analysis and quantitative structure-activity relationship investigation of some triazine-antifolate inhibitors of Leishmania dihydrofolate reductase | Q67946139 | ||
| Applications of neural networks in quantitative structure-activity relationships of dihydrofolate reductase inhibitors | Q67977559 | ||
| Direct prediction of dissociation constants (pKa's) of clonidine-like imidazolines, 2-substituted imidazoles, and 1-methyl-2-substituted-imidazoles from 3D structures using a comparative molecular field analysis (CoMFA) approach | Q70223325 | ||
| Three-dimensional quantitative structure--activity relationships for androgen receptor ligands | Q71140126 | ||
| Predicting mutagenicity of chemicals using topological and quantum chemical parameters: A similarity based study | Q72049100 | ||
| Voronoi modeling: the binding of triazines and pyrimidines to L. casei dihydrofolate reductase | Q72579297 | ||
| A generalized formalism of three-dimensional quantitative structure-property relationship analysis for flexible molecules using tensor representation | Q72819387 | ||
| Construction of a molecular shape analysis-three-dimensional quantitative structure-analysis relationship for an analog series of pyridobenzodiazepinone inhibitors of muscarinic 2 and 3 receptors | Q72819390 | ||
| Three-dimensional quantitative structure-activity relationship of angiotesin-converting enzyme and thermolysin inhibitors. II. A comparison of CoMFA models incorporating molecular orbital fields and desolvation free energies based on active-analog a | Q72901983 | ||
| P433 | issue | 1 | |
| P921 | main subject | nearest neighbour algorithm | Q1374523 |
| P304 | page(s) | 185-194 | |
| P577 | publication date | 2000-01-01 | |
| P1433 | published in | Journal of Chemical Information and Computer Sciences | Q104614957 |
| P1476 | title | Novel variable selection quantitative structure--property relationship approach based on the k-nearest-neighbor principle | |
| P478 | volume | 40 |
| Q52004654 | 2D QSAR consensus prediction for high-throughput virtual screening. An application to COX-2 inhibition modeling and screening of the NCI database |
| Q59289468 | 2D, 3D-QSAR and docking studies of 1,2,3-thiadiazole thioacetanilides analogues as potent HIV-1 non-nucleoside reverse transcriptase inhibitors |
| Q91239968 | 2D- and 3D-QSAR modelling, molecular docking and in vitro evaluation studies on 18β-glycyrrhetinic acid derivatives against triple-negative breast cancer cell line |
| Q35939582 | 3D-QSAR studies on fluroquinolones derivatives as inhibitors for tuberculosis |
| Q104473715 | A Combined approach of Pharmacophore Modeling, QSAR Study, Molecular Docking and in silico ADME/Tox prediction of 4-Arylthio & 4- Aryloxy-3- Iodopyridine-2(1H)-one analogs to identify potential Reverse Transcriptase inhibitor: Anti-HIV agents |
| Q51365324 | A QSAR Study of Environmental Estrogens Based on a Novel Variable Selection Method |
| Q50885432 | A Structure-Activity Relationship Study of Naphthoquinone Derivatives as Antitubercular Agents Using Molecular Modeling Techniques. |
| Q48017744 | A chemical class-based approach to predictive model generation |
| Q39708002 | A comprehensive identification-evidence based alternative for HIV/AIDS treatment with HAART in the healthcare industries |
| Q54692862 | A comprehensive structure-activity analysis of protein kinase B-alpha (Akt1) inhibitors. |
| Q41870587 | A critical assessment of combined ligand- and structure-based approaches to HERG channel blocker modeling |
| Q51897669 | A hierarchical clustering methodology for the estimation of toxicity. |
| Q40106954 | A modeling study of aldehyde inhibitors of human cathepsin K using partial least squares method. |
| Q43703970 | A novel PI index and its applications to QSPR/QSAR studies |
| Q36876902 | A novel automated lazy learning QSAR (ALL-QSAR) approach: method development, applications, and virtual screening of chemical databases using validated ALL-QSAR models |
| Q45005255 | A novel two-step QSAR modeling work flow to predict selectivity and activity of HDAC inhibitors |
| Q37291866 | A novel two-step hierarchical quantitative structure-activity relationship modeling work flow for predicting acute toxicity of chemicals in rodents |
| Q129289231 | A review of extractive distillation from an azeotropic phenomenon for dynamic control |
| Q31106864 | A review of the applications of data mining and machine learning for the prediction of biomedical properties of nanoparticles |
| Q64168640 | A systematic evaluation of the benefits and hazards of variable selection in latent variable regression. Part I. Search algorithm, theory and simulations |
| Q51548690 | Activity prediction of some nontested anticancer compounds using GA-based PLS regression models |
| Q57008772 | Addressing a bottle neck for regulation of nanomaterials: quantitative read-across (Nano-QRA) algorithm for cases when only limited data is available |
| Q34289760 | Advances in computational methods to predict the biological activity of compounds. |
| Q43930525 | An integrated SOM-fuzzy ARTMAP neural system for the evaluation of toxicity |
| Q33879724 | Analysis and Study of Molecule Data Sets Using Snowflake Diagrams of Weighted Maximum Common Subgraph Trees |
| Q92877845 | Analysis of model PM2.5-induced inflammation and cytotoxicity by the combination of a virtual carbon nanoparticle library and computational modeling |
| Q33193139 | Anti-HIV activity of HEPT, TIBO, and cyclic urea derivatives: structure-property studies, focused combinatorial library generation, and hits selection using substructural molecular fragments method. |
| Q30352841 | Antiprotozoal Nitazoxanide Derivatives: Synthesis, Bioassays and QSAR Study Combined with Docking for Mechanistic Insight. |
| Q37368872 | Antitumor agents 252. Application of validated QSAR models to database mining: discovery of novel tylophorine derivatives as potential anticancer agents |
| Q40640009 | Antitumor agents. 213. Modeling of epipodophyllotoxin derivatives using variable selection k nearest neighbor QSAR method |
| Q36091289 | Application of GQSAR for Scaffold Hopping and Lead Optimization in Multitarget Inhibitors |
| Q33730312 | Application of QSAR and Shape Pharmacophore Modeling Approaches for Targeted Chemical Library Design |
| Q57363395 | Application of QSPR to Mixtures |
| Q46741550 | Application of predictive QSAR models to database mining: identification and experimental validation of novel anticonvulsant compounds |
| Q37700998 | Application of quantitative structure-activity relationship models of 5-HT1A receptor binding to virtual screening identifies novel and potent 5-HT1A ligands |
| Q46798122 | Application of validated QSAR models of D1 dopaminergic antagonists for database mining |
| Q30832351 | Applying data mining techniques to library design, lead generation and lead optimization |
| Q24813419 | Assessment of prediction confidence and domain extrapolation of two structure-activity relationship models for predicting estrogen receptor binding activity |
| Q59066121 | Autoregressive Prediction with Rolling Mechanism for Time Series Forecasting with Small Sample Size |
| Q28649930 | Best Practices for QSAR Model Development, Validation, and Exploitation |
| Q28842863 | Beware of q2! |
| Q108527454 | Bibliography |
| Q90096114 | Big Data and Artificial Intelligence Modeling for Drug Discovery |
| Q96291702 | Big-Data Science in Porous Materials: Materials Genomics and Machine Learning |
| Q56916101 | Chapter 9 Molecular Similarity: Advances in Methods, Applications and Validations in Virtual Screening and QSAR |
| Q88009893 | Characterization of Mixtures. Part 2: QSPR Models for Prediction of Excess Molar Volume and Liquid Density Using Neural Networks |
| Q30490614 | Chembench: A Publicly Accessible, Integrated Cheminformatics Portal |
| Q42574841 | Chemometric analysis of ligand receptor complementarity: identifying Complementary Ligands Based on Receptor Information (CoLiBRI). |
| Q57819339 | Chemometrics in QSAR |
| Q56432344 | Chemometrics tools in QSAR/QSPR studies: A historical perspective |
| Q33859712 | Classification NanoSAR development for cytotoxicity of metal oxide nanoparticles |
| Q51703283 | Classification and virtual screening of androgen receptor antagonists |
| Q45964216 | Classification of cytochrome P450 1A2 inhibitors and noninhibitors by machine learning techniques. |
| Q33755029 | CoMFA analysis of tgDHFR and rlDHFR based on antifolates with 6-5 fused ring system using the all-orientation search (AOS) routine and a modified cross-validated r(2)-guided region selection (q(2)-GRS) routine and its initial application |
| Q45294403 | CoMFA and CoMSIA analyses of Pneumocystis carinii dihydrofolate reductase, Toxoplasma gondii dihydrofolate reductase, and rat liver dihydrofolate reductase |
| Q83372806 | Combinatorial QSAR modeling of P-glycoprotein substrates |
| Q42646937 | Combinatorial QSAR modeling of chemical toxicants tested against Tetrahymena pyriformis |
| Q33333590 | Combinatorial QSAR modeling of specificity and subtype selectivity of ligands binding to serotonin receptors 5HT1E and 5HT1F. |
| Q52001092 | Combinatorial QSAR of ambergris fragrance compounds |
| Q40959163 | Combining docking-based comparative intermolecular contacts analysis and k-nearest neighbor correlation for the discovery of new check point kinase 1 inhibitors |
| Q39524100 | Comparative Analysis of QSAR-based vs. Chemical Similarity Based Predictors of GPCRs Binding Affinity |
| Q85643224 | Comparative Pharmacophore Modeling and QSAR Studies for Structural Requirements of some Substituted 2-Aminopyridine Derivatives as Inhibitors of Nitric Oxide Synthases |
| Q85240577 | Comparative pharmacophore modeling and QSAR studies for structural requirements of some substituted 2-aminopyridines derivatives as inhibitors nitric oxide synthases |
| Q31169170 | Comparative study of machine-learning and chemometric tools for analysis of in-vivo high-throughput screening data |
| Q51366809 | Comparison of global and mode of action-based models for aquatic toxicity. |
| Q41140196 | Comprehensive Modeling and Discovery of Mebendazole as a Novel TRAF2- and NCK-interacting Kinase Inhibitor |
| Q108527458 | Computational Approaches for Target Inference |
| Q26997089 | Computational methods in drug discovery |
| Q41983319 | Computational modeling of novel inhibitors targeting the Akt pleckstrin homology domain |
| Q28829021 | Computer-aided design of carbon nanotubes with the desired bioactivity and safety profiles |
| Q38819860 | Computer-aided discovery of new FGFR-1 inhibitors followed by in vitro validation. |
| Q37841340 | Computer-aided drug discovery and development |
| Q57808771 | Computing similarity between structural environments of mutagenicity alerts |
| Q40451590 | Consensus kNN QSAR: a versatile method for predicting the estrogenic activity of organic compounds in silico. A comparative study with five estrogen receptors and a large, diverse set of ligands. |
| Q37198661 | Considerations and recent advances in QSAR models for cytochrome P450-mediated drug metabolism prediction |
| Q51706593 | Counter propagation artificial neural network categorical models for prediction of carcinogenicity for non-congeneric chemicals |
| Q37639371 | Critical evaluation of human oral bioavailability for pharmaceutical drugs by using various cheminformatics approaches |
| Q58103008 | Current Approaches for Choosing Feature Selection and Learning Algorithms in Quantitative Structure-Activity Relationships (QSAR) |
| Q31119563 | Data Mining and Machine Learning Tools for Combinatorial Material Science of All-Oxide Photovoltaic Cells |
| Q90275704 | Deep Convolutional Neural Networks for the Prediction of Molecular Properties: Challenges and Opportunities Connected to the Data |
| Q47572187 | Descriptor Selection via Log-Sum Regularization for the Biological Activities of Chemical Structure |
| Q38119005 | Descriptor selection methods in quantitative structure-activity relationship studies: a review study |
| Q30929535 | Developing Enhanced Blood-Brain Barrier Permeability Models: Integrating External Bio-Assay Data in QSAR Modeling |
| Q47805354 | Development and validation of k-nearest-neighbor QSPR models of metabolic stability of drug candidates |
| Q37412416 | Development of quantitative structure-binding affinity relationship models based on novel geometrical chemical descriptors of the protein-ligand interfaces |
| Q36223175 | Development, validation, and use of quantitative structure-activity relationship models of 5-hydroxytryptamine (2B) receptor ligands to identify novel receptor binders and putative valvulopathic compounds among common drugs |
| Q33323614 | Differentiation of AmpC beta-lactamase binders vs. decoys using classification kNN QSAR modeling and application of the QSAR classifier to virtual screening |
| Q108527517 | Directionally sensitive homogeneously weighted moving average control charts |
| Q35681838 | Discovery of Natural Product-Derived 5-HT1A Receptor Binders by Cheminfomatics Modeling of Known Binders, High Throughput Screening and Experimental Validation |
| Q37304601 | Discovery of geranylgeranyltransferase-I inhibitors with novel scaffolds by the means of quantitative structure-activity relationship modeling, virtual screening, and experimental validation |
| Q92490554 | Discovery of new JNK3 inhibitory chemotypes via QSAR-Guided selection of docking-based pharmacophores and comparison with other structure-based pharmacophore modeling methods |
| Q35949404 | Discovery of new selective cytotoxic agents against Bcl-2 expressing cancer cells using ligand-based modeling. |
| Q91292299 | Discovery of novel Flt3 inhibitory chemotypes through extensive ligand-based and new structure-based pharmacophore modelling methods |
| Q40399170 | Discovery of novel antimalarial compounds enabled by QSAR-based virtual screening |
| Q47789923 | Discovery of potent adenosine A2a antagonists as potential anti-Parkinson disease agents. Non-linear QSAR analyses integrated with pharmacophore modeling |
| Q44024312 | Diverse models for the prediction of HIV integrase inhibitory activity of substituted quinolone carboxylic acids |
| Q104464870 | Do we need different machine learning algorithms for QSAR modeling? A comprehensive assessment of 16 machine learning algorithms on 14 QSAR data sets |
| Q50771542 | Elaborate ligand-based modeling coupled with multiple linear regression and k nearest neighbor QSAR analyses unveiled new nanomolar mTOR inhibitors. |
| Q88332474 | Erratum to: Does being an Olympic city help improve recreational resources? Examining the quality of physical activity resources in a low-income neighborhood of Rio de Janeiro |
| Q57948354 | Evaluation of Mutual Information and Genetic Programming for Feature Selection in QSAR |
| Q47311102 | GA(M)E-QSAR: a novel, fully automatic genetic-algorithm-(meta)-ensembles approach for binary classification in ligand-based drug design. |
| Q56982807 | Generative Topographic Mapping Approach to Chemical Space Analysis |
| Q52036280 | Genetic Algorithm guided Selection: variable selection and subset selection |
| Q100989757 | Guiding Conventional Protein-Ligand Docking Software with Convolutional Neural Networks |
| Q51865853 | Highly correlating distance/connectivity-based topological indices 5. Accurate prediction of liquid density of organic molecules using PCR and PC-ANN. |
| Q40657601 | Identification of 3-Nitro-2,4,6-trihydroxybenzamide Derivatives as Photosynthetic Electron Transport Inhibitors by QSAR and Pharmacophore Studies |
| Q46169885 | Identification of 3-nitro-2, 4, 6-trihydroxybenzamide derivatives as photosynthetic electron transport inhibitors by QSAR and pharmacophore studies |
| Q41035643 | Identification of novel inhibitors for Pim-1 kinase using pharmacophore modeling based on a novel method for selecting pharmacophore generation subsets. |
| Q34740499 | Identification of putative estrogen receptor-mediated endocrine disrupting chemicals using QSAR- and structure-based virtual screening approaches |
| Q31020770 | Identifying biologically active compound classes using phenotypic screening data and sampling statistics |
| Q30489350 | If I tweet will you cite? The effect of social media exposure of articles on downloads and citations. |
| Q93362283 | Implicit-descriptor ligand-based virtual screening by means of collaborative filtering |
| Q35952879 | In silico approaches for predicting ADME properties of drugs |
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| Q93091403 | In silico profiling nanoparticles: predictive nanomodeling using universal nanodescriptors and various machine learning approaches |
| Q45018056 | In silico studies with human DNA topoisomerase-II alpha to unravel the mechanism of in vitro genotoxicity of benzene and its metabolites |
| Q37360048 | Influence relevance voting: an accurate and interpretable virtual high throughput screening method |
| Q39340009 | Informing the Human Plasma Protein Binding of Environmental Chemicals by Machine Learning in the Pharmaceutical Space: Applicability Domain and Limits of Predictability |
| Q51330280 | Integrated in silico approaches for the prediction of Ames test mutagenicity |
| Q35210032 | Integrative and personalized QSAR analysis in cancer by kernelized Bayesian matrix factorization |
| Q42921015 | Integrative chemical-biological read-across approach for chemical hazard classification |
| Q44631258 | Interpretation of honeybees contact toxicity associated to acetylcholinesterase inhibitors |
| Q128491891 | Investigating Structural Requirements of Some Pyrimidine-linked Benzimidazole Derivatives as Anticancer Agents Against MCF-7 Cancerous Cell Line Through the use of 2D and 3D QSARs |
| Q38850045 | Investigation of the influence of protein corona composition on gold nanoparticle bioactivity using machine learning approaches |
| Q33967814 | LigSeeSVM: ligand-based virtual screening using support vector machines and data fusion |
| Q47226715 | Ligand-based computational modelling of platelet-derived growth factor beta receptor leading to new angiogenesis inhibitory leads. |
| Q38797004 | Ligand-based modeling of diverse aryalkylamines yields new potent P-glycoprotein inhibitors |
| Q89208331 | Machine Learning Methods in Computational Toxicology |
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| Q34271118 | Machine learning methods in chemoinformatics |
| Q53807639 | Mapping drug-target interaction networks |
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| Q45372748 | Mixed learning algorithms and features ensemble in hepatotoxicity prediction. |
| Q37194304 | Modeling kinetics of subcellular disposition of chemicals. |
| Q33535332 | Modeling liver-related adverse effects of drugs using knearest neighbor quantitative structure-activity relationship method |
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| Q59007997 | Molecular Modeling Studies of Substituted 2,4,5-Trisubstituted Triazolinones Aryl and Nonaryl Derivatives as Angiotensin II AT1Receptor Antagonists |
| Q36365145 | Molecular similarity and diversity in chemoinformatics: from theory to applications. |
| Q115741790 | Multivariate statistical analysis methods in QSAR |
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| Q39535158 | New QSAR Models for Human Cytochromes P450, 1A2, 2D6 and 3A4 Implicated in the Metabolism of Drugs. Relevance of Dataset on Model Development |
| Q52036293 | Novel ZE-isomerism descriptors derived from molecular topology and their application to QSAR analysis |
| Q73508134 | Novel chirality descriptors derived from molecular topology |
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| Q51930825 | Novel semi-automated methodology for developing highly predictive QSAR models: application for development of QSAR models for insect repellent amides |
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| Q31949891 | Predicting the kinetics of peptide-antibody interactions using a multivariate experimental design of sequence and chemical space |
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| Q47329221 | Prediction of acute mammalian toxicity using QSAR methods: a case study of sulfur mustard and its breakdown products |
| Q44288159 | Prediction of dihydrofolate reductase inhibition and selectivity using computational neural networks and linear discriminant analysis |
| Q36056166 | Prediction of human population responses to toxic compounds by a collaborative competition |
| Q41470377 | Prediction of partition coefficient of some 3-hydroxy pyridine-4-one derivatives using combined partial least square regression and genetic algorithm |
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| Q78844325 | Predictive QSAR modeling based on diversity sampling of experimental datasets for the training and test set selection |
| Q35103940 | Predictive in silico off-target profiling in drug discovery |
| Q99355178 | Predictive modeling of angiotensin I-converting enzyme (ACE) inhibitory peptides using various machine learning approaches |
| Q50882338 | Prospective QSAR-Based Prediction Models with Pharmacophore Studies of Oxadiazole-Substituted α-Isopropoxy Phenylpropanoic Acids with Dual Activators of PPARα and PPARγ. |
| Q51044220 | Prospective QSAR-based prediction models with pharmacophore studies of oxadiazole-substituted α-isopropoxy phenylpropanoic acids on with dual activators of PPARα and PPARγ |
| Q43881504 | QNA-based 'Star Track' QSAR approach. |
| Q51629378 | QSAR analysis for some diaryl-substituted pyrazoles as CCR2 inhibitors by GA-stepwise MLR. |
| Q57019425 | QSAR and Molecular Modeling Approaches for Prediction of Drug Metabolism |
| Q46196365 | QSAR classification models for the screening of the endocrine-disrupting activity of perfluorinated compounds. |
| Q80805981 | QSAR modeling of GPCR ligands: methodologies and examples of applications |
| Q51928184 | QSAR modeling of human serum protein binding with several modeling techniques utilizing structure-information representation |
| Q43558205 | QSAR modeling of the blood-brain barrier permeability for diverse organic compounds |
| Q44290415 | QSAR modeling using chirality descriptors derived from molecular topology |
| Q32019897 | QSAR models using a large diverse set of estrogens |
| Q51928569 | QSAR prediction of estrogen activity for a large set of diverse chemicals under the guidance of OECD principles. |
| Q50957987 | QSAR prediction of the competitive interaction of emerging halogenated pollutants with human transthyretin |
| Q85657172 | QSAR studies on 3-(4-biphenylmethyl) 4, 5-dihydro-4-oxo-3H-imidazo [4, 5-c] Pyridine derivatives as angiotensin II (AT1) receptor antagonist |
| Q47670530 | QSAR, docking and in vivo studies for immunomodulatory activity of isolated triterpenoids from Eucalyptus tereticornis and Gentiana kurroo. |
| Q28385022 | Quantitative nanostructure-activity relationship modeling |
| Q42322486 | Quantitative structure - property relationship modeling of remote liposome loading of drugs |
| Q74291072 | Quantitative structure-activity relationship analysis of functionalized amino acid anticonvulsant agents using k nearest neighbor and simulated annealing PLS methods |
| Q46703800 | Quantitative structure-activity relationship analysis of pyridinone HIV-1 reverse transcriptase inhibitors using the k nearest neighbor method and QSAR-based database mining |
| Q35201801 | Quantitative structure-activity relationship methods: perspectives on drug discovery and toxicology |
| Q33551379 | Quantitative structure-activity relationship modeling of rat acute toxicity by oral exposure |
| Q46696141 | Quantitative structure-activity relationships of methotrexate and methotrexate analogues transported by the rat multispecific resistance-associated protein 2 (rMrp2). |
| Q80531189 | Quantitative structure-pharmacokinetic parameters relationships (QSPKR) analysis of antimicrobial agents in humans using simulated annealing k-nearest-neighbor and partial least-square analysis methods |
| Q37166328 | Quantum-SAR extension of the spectral-SAR algorithm: application to polyphenolic anticancer bioactivity |
| Q51507851 | Rank-based ant system method for non-linear QSPR analysis: QSPR studies of the solubility parameter |
| Q31165909 | Rational selection of training and test sets for the development of validated QSAR models |
| Q43262550 | Rationalizing protein-ligand interactions for PTP1B inhibitors using computational methods |
| Q99602518 | Reason Vectors: Abstract Representation of Chemistry-Biology Interaction Outcomes, for Reasoning and Prediction |
| Q108527442 | Recent Advances in Development, Validation, and Exploitation of QSAR Models |
| Q108527443 | Recent Advances in Development, Validation, and Exploitation of QSAR Models |
| Q47192466 | Recent Trends in Statistical QSAR Modeling of Environmental Chemical Toxicity |
| Q34288171 | Recent advances in ligand-based drug design: relevance and utility of the conformationally sampled pharmacophore approach. |
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