A. Golbraikh

发表

A. Tropsha, A. Golbraikh, 2002, Journal of molecular graphics & modelling.

A. Tropsha, A. Golbraikh, 2002 .

Development and validation of k-nearest-neighbor QSPR models of metabolic stability of drug candidates.

A. Tropsha, A. Golbraikh, V. Gombar, 2003, Journal of medicinal chemistry.

Application of predictive QSAR models to database mining: identification and experimental validation of novel anticonvulsant compounds.

Alexander Golbraikh, Alexander Tropsha, Cécile Béguin, 2004, Journal of medicinal chemistry.

Value of p‐Value

A. Golbraikh, 2019, Molecular informatics.

QSAR Modeling of Datasets with Enantioselective Compounds using Chirality Sensitive Molecular Descriptors

A Tropsha, A. Tropsha, S. Oloff, 2005, SAR and QSAR in environmental research.

Development of quantitative structure-binding affinity relationship models based on novel geometrical chemical descriptors of the protein-ligand interfaces.

A. Tropsha, A. Golbraikh, Shuxing Zhang, 2006, Journal of medicinal chemistry.

Simple yet accurate prediction method for sublimation enthalpies of organic contaminants using their molecular structure

A. Gandomi, A. Golbraikh, M. Bagheri, 2012 .

Rank-based ant system method for non-linear QSPR analysis: QSPR studies of the solubility parameter

A. Golbraikh, M. Bagheri, Mehdi Bagheri, 2012, SAR and QSAR in environmental research.

Validation of protein-based alignment in 3D quantitative structure-activity relationships with CoMFA models.

A. Golbraikh, J. Chrétien, P. Bernard, 2000, European journal of medicinal chemistry.

Quantitative Structure−Activity Relationship Analysis of Functionalized Amino Acid Anticonvulsant Agents Using k Nearest Neighbor and Simulated Annealing PLS Methods

Alexander Golbraikh, Alexander Tropsha, Yunde Xiao, 2002 .

QSAR Modeling of the Blood–Brain Barrier Permeability for Diverse Organic Compounds

Alexander Golbraikh, Tudor I. Oprea, Alexander Tropsha, 2008, Pharmaceutical Research.

Integrative chemical-biological read-across approach for chemical hazard classification.

Alexander Golbraikh, Ivan Rusyn, Alexander Tropsha, 2013, Chemical research in toxicology.

Development of kNN QSAR Models for 3-Arylisoquinoline Antitumor Agents

Alexander Golbraikh, Alexander Tropsha, A. Tropsha, 2011 .

QSAR/QSPR Revisited

Alexander Golbraikh, Alexander Tropsha, A. Tropsha, 2018, Chemoinformatics.

Purine Nucleoside Analogues; 9: Benzylation of N 2-Acetyl-8-bromoguanine

A. Golbraikh, G. Koomen, R. Zhuk, 1999 .

Multi-Descriptor Read Across (MuDRA): a simple and transparent approach for developing accurate QSAR models

Wai In Lam, Vinicius M. Alves, Stephen J. Capuzzi, 2021 .

Application of Quantitative Structure–Activity Relationship Models of 5-HT1A Receptor Binding to Virtual Screening Identifies Novel and Potent 5-HT1A Ligands

Alexander Golbraikh, Bryan L. Roth, Alexander Tropsha, 2014, J. Chem. Inf. Model..

Differentiation of AmpC beta-lactamase binders vs. decoys using classification kNN QSAR modeling and application of the QSAR classifier to virtual screening

Alexander Golbraikh, Alexander Tropsha, Denise G. Teotico, 2008, J. Comput. Aided Mol. Des..

Does Rational Selection of Training and Test Sets Improve the Outcome of QSAR Modeling?

Alexander Golbraikh, Hao Zhu, Douglas M. Young, 2012, J. Chem. Inf. Model..

Predictive QSAR modeling based on diversity sampling of experimental datasets for the training and test set selection

Alexander Golbraikh, Alexander Tropsha, A. Tropsha, 2004, Molecular Diversity.

Novel ligands for the human histamine H1 receptor: synthesis, pharmacology, and comparative molecular field analysis studies of 2-dimethylamino-5-(6)-phenyl-1,2,3,4-tetrahydronaphthalenes.

Alexander Golbraikh, Alexander Tropsha, A. Tropsha, 2006, Bioorganic & medicinal chemistry.

Purine nucleoside analogues. 11. An alternative synthesis of N- and O-alkyl derivatives of 9- and 7-[(2-acetoxyethoxy)methyl]-N2-acetylguanine

A. Golbraikh, R. Zhuk, J. Geenevasen, 1999 .

Conformational aspects of antiviral activity of deoxyguanosine acyclic analogues.

A. Golbraikh, G. Nikiforovich, R. Zhuk, 1989, Nucleic acids research.

Combinatorial QSAR Modeling of Specificity and Subtype Selectivity of Ligands Binding to Serotonin Receptors 5HT1E and 5HT1F

Alexander Golbraikh, Alexander Tropsha, Hao Tang, 2008, J. Chem. Inf. Model..

Antitumor agents. 213. Modeling of epipodophyllotoxin derivatives using variable selection k nearest neighbor QSAR method.

Alexander Golbraikh, Alexander Tropsha, Zhiyan Xiao, 2002, Journal of medicinal chemistry.

Multi-Descriptor Read Across (MuDRA): A Simple and Transparent Approach for Developing Accurate Quantitative Structure-Activity Relationship Models

Alexander Golbraikh, Alexander Tropsha, Diane Pozefsky, 2018, J. Chem. Inf. Model..

Predictive QSAR modeling workflow, model applicability domains, and virtual screening.

Alexander Golbraikh, Alexander Tropsha, A. Tropsha, 2007, Current pharmaceutical design.

Comparison of chemical databases : Analysis of molecular diversity with self Organising maps (SOM)

Alexander Golbraikh, Philippe Bernard, Jacques R. Chrétien, 1998 .

Probing of the receptor-binding sites of the H1 and H3 influenza A and influenza B virus hemagglutinins by synthetic and natural sialosides.

A. Golbraikh, N. Bovin, M. Matrosovich, 1993, Virology.

Quantitative Structure–activity Relationship Analysis of Pyridinone HIV-1 Reverse Transcriptase Inhibitors using the k Nearest Neighbor Method and QSAR-based Database Mining

Alexander Golbraikh, Alexander Tropsha, José L. Medina-Franco, 2005, J. Comput. Aided Mol. Des..

Discovery of Novel Antimalarial Compounds Enabled by QSAR-Based Virtual Screening

Julie Clark, Alexander Golbraikh, Hao Zhu, 2013, J. Chem. Inf. Model..

Combinatorial QSAR of Ambergris Fragrance Compounds

Alexander Golbraikh, Alexander Tropsha, Weifan Zheng, 2004, J. Chem. Inf. Model..

Rational selection of training and test sets for the development of validated QSAR models

Alexander Golbraikh, Min Shen, Alexander Tropsha, 2003, J. Comput. Aided Mol. Des..

Data Set Modelability by QSAR

Alexander Golbraikh, Alexander Tropsha, Denis Fourches, 2014, J. Chem. Inf. Model..

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.

Alexander Golbraikh, Alexander Tropsha, Christopher M Grulke, 2010, Journal of medicinal chemistry.

A Novel Automated Lazy Learning QSAR (ALL-QSAR) Approach: Method Development, Applications, and Virtual Screening of Chemical Databases Using Validated ALL-QSAR Models

Alexander Golbraikh, Alexander Tropsha, Scott Oloff, 2006, J. Chem. Inf. Model..

Predictive QSAR modeling based on diversity sampling of experimental datasets for the training and test set selection

Alexander Golbraikh, Alexander Tropsha, A. Tropsha, 2002, J. Comput. Aided Mol. Des..

QSAR Modeling of alpha-Campholenic Derivatives with Sandalwood Odor

Alexander Golbraikh, Peter Wolschann, Gerhard Buchbauer, 2003, J. Chem. Inf. Comput. Sci..

Conformational features responsible for binding of cyclic analogues of enkephalin to opioid receptors. I. Low-energy peptide backbone conformers of analogues containing Phe4.

A. Golbraikh, G. Nikiforovich, M. Shenderovich, 2009, International journal of peptide and protein research.

QSAR Modeling Using Chirality Descriptors Derived from Molecular Topology

Alexander Golbraikh, Alexander Tropsha, A. Tropsha, 2003, J. Chem. Inf. Comput. Sci..

Novel ZE-Isomerism Descriptors Derived from Molecular Topology and Their Application to QSAR Analysis

Alexander Golbraikh, Danail Bonchev, Alexander Tropsha, 2002, J. Chem. Inf. Comput. Sci..

Novel Chirality Descriptors Derived from Molecular Topology

Alexander Golbraikh, Danail Bonchev, Alexander Tropsha, 2001, J. Chem. Inf. Comput. Sci..

Novel Chirality Descriptors Derived from Molecular Topology.

Alexander Golbraikh, Alexander Tropsha, Danail Bonchev, 2001 .

Quantitative structure-property relationship modeling of remote liposome loading of drugs.

Alexander Golbraikh, Amiram Goldblum, Alexander Tropsha, 2012, Journal of controlled release : official journal of the Controlled Release Society.

Predictive QSAR modeling: Methods and applications in drug discovery and chemical risk assessment

Alexander Golbraikh, Hao Zhu, Alexander Tropsha, 2012 .

QSAR Modeling of α-Campholenic Derivatives with Sandalwood Odor.

Alexander Golbraikh, Peter Wolschann, Gerhard Buchbauer, 2003 .

A Novel Two-Step Hierarchical Quantitative Structure–Activity Relationship Modeling Work Flow for Predicting Acute Toxicity of Chemicals in Rodents

Alexander Golbraikh, Fred A. Wright, Ivan Rusyn, 2009, Environmental health perspectives.

A molecular mechanism for the cleavage of a disulfide bond as the primary function of agonist binding to G-protein-coupled receptors based on theoretical calculations supported by experiments.

A. Golbraikh, U. Lendeckel, W. Brandt, 1999, European journal of biochemistry.

Conformational features responsible for the binding of cyclic analogues of enkephalin to opioid receptors. III. Probable binding conformations of mu-agonists with phenylalanine in position 3.

A. Golbraikh, G. Nikiforovich, G V Nikiforovich, 2009, International journal of peptide and protein research.

Molecular Dataset Diversity Indices and Their Applications to Comparison of Chemical Databases and QSAR Analysis

Alexander Golbraikh, A. Golbraikh, 2000, J. Chem. Inf. Comput. Sci..

Does Rational Selection of Training and Test Sets Improve the Outcome of QSAR Modeling?

A. Tropsha, D. Young, T. Martin, 2012, J. Chem. Inf. Model..

Data Set Modelability by QSAR

A. Tropsha, D. Fourches, E. Muratov, 2014, J. Chem. Inf. Model..

Dataset Modelability by QSAR: Continuous Response Variable

Vinicius M. Alves, A. Tropsha, E. Muratov, 2021, Practical Aspects of Computational Chemistry V.

Modelability Criteria: Statistical Characteristics Estimating Feasibility to Build Predictive QSAR Models for a Dataset

Inta Liepina, Alexander Golbraikh, Alexander Tropsha, 2014 .

Integrative chemical-biological read-across approach for chemical hazard classification.

I. Rusyn, A. Tropsha, Alexander Sedykh, 2013, Chemical research in toxicology.

Discovery of Novel Antimalarial Compounds Enabled by QSAR-Based Virtual Screening

A. Tropsha, S. Ekins, Alexander Sedykh, 2013, J. Chem. Inf. Model..

Combinatorial QSAR Modeling of P-Glycoprotein Substrates

Alexander Golbraikh, Alexander Tropsha, Yunde Xiao, 2006, J. Chem. Inf. Model..