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Jürgen Bajorath
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- affiliation: University of Bonn, Germany
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2020 – today
- 2024
- [j196]Hengwei Chen, Jürgen Bajorath:
Generative design of compounds with desired potency from target protein sequences using a multimodal biochemical language model. J. Cheminformatics 16(1): 55 (2024) - 2023
- [j195]Kohei Umedera, Atsushi Yoshimori, Hengwei Chen, Hiroyuki Kouji, Hiroyuki Nakamura, Jürgen Bajorath:
DeepCubist: Molecular Generator for Designing Peptidomimetics based on Complex three-dimensional scaffolds. J. Comput. Aided Mol. Des. 37(2): 107-115 (2023) - [j194]Shunsuke Tamura, Tomoyuki Miyao, Jürgen Bajorath:
Large-scale prediction of activity cliffs using machine and deep learning methods of increasing complexity. J. Cheminformatics 15(1): 4 (2023) - [j193]Nicola Gambacorta, Fulvio Ciriaco
, Nicola Amoroso, Cosimo Damiano Altomare, Jürgen Bajorath
, Orazio Nicolotti
:
CIRCE: Web-Based Platform for the Prediction of Cannabinoid Receptor Ligands Using Explainable Machine Learning. J. Chem. Inf. Model. 63(18): 5916-5926 (2023) - [j192]Tiago Janela, Jürgen Bajorath
:
Anatomy of Potency Predictions Focusing on Structural Analogues with Increasing Potency Differences Including Activity Cliffs. J. Chem. Inf. Model. 63(22): 7032-7044 (2023) - [j191]Andrea Mastropietro
, Giuseppe Pasculli
, Jürgen Bajorath
:
Learning characteristics of graph neural networks predicting protein-ligand affinities. Nat. Mac. Intell. 5(12): 1427-1436 (2023) - 2022
- [j190]Raquel Rodríguez-Pérez, Jürgen Bajorath
:
Evolution of Support Vector Machine and Regression Modeling in Chemoinformatics and Drug Discovery. J. Comput. Aided Mol. Des. 36(5): 355-362 (2022) - [j189]Thomas Blaschke, Jürgen Bajorath
:
Fine-tuning of a generative neural network for designing multi-target compounds. J. Comput. Aided Mol. Des. 36(5): 363-371 (2022) - [j188]Veerabahu Shanmugasundaram
, Jürgen Bajorath
, Ralph E. Christoffersen, James D. Petke, W. Jeffrey Howe, Mark A. Johnson, Dimitris K. Agrafiotis
, Pil Lee
, Leslie A. Kuhn
, Jay T. Goodwin
, M. Katharine Holloway, Thompson N. Doman, W. Patrick Walters
, Suzanne K. Schreyer, José L. Medina-Franco
, Karina Martínez-Mayorga
, Linda L. Restifo
:
Epilogue to the Gerald Maggiora Festschrift: a tribute to an exemplary mentor, colleague, collaborator, and innovator. J. Comput. Aided Mol. Des. 36(9): 623-638 (2022) - [j187]Jürgen Bajorath, Ana L. Chávez-Hernández
, Miquel Duran-Frigola
, Eli Fernández-de Gortari, Johann Gasteiger, Edgar López-López, Gerald M. Maggiora, José L. Medina-Franco, Oscar Méndez-Lucio, Jordi Mestres, Ramón Alain Miranda-Quintana, Tudor I. Oprea, Fabien Plisson
, Fernando D. Prieto-Martínez, Raquel Rodríguez-Pérez, Paola Rondón-Villarreal, Fernanda I. Saldívar-González, Norberto Sánchez-Cruz, Marilia Valli:
Chemoinformatics and artificial intelligence colloquium: progress and challenges in developing bioactive compounds. J. Cheminformatics 14(1): 82 (2022) - [j186]Tiago Janela, Jürgen Bajorath
:
Simple nearest-neighbour analysis meets the accuracy of compound potency predictions using complex machine learning models. Nat. Mac. Intell. 4(12): 1246-1255 (2022) - 2021
- [j185]Raquel Rodríguez-Pérez, Jürgen Bajorath
:
Evaluation of multi-target deep neural network models for compound potency prediction under increasingly challenging test conditions. J. Comput. Aided Mol. Des. 35(3): 285-295 (2021) - [j184]Atsushi Yoshimori, Huabin Hu, Jürgen Bajorath
:
Adapting the DeepSARM approach for dual-target ligand design. J. Comput. Aided Mol. Des. 35(5): 587-600 (2021) - [j183]Javed Iqbal, Martin Vogt, Jürgen Bajorath
:
Prediction of activity cliffs on the basis of images using convolutional neural networks. J. Comput. Aided Mol. Des. 35(12): 1157-1164 (2021) - [j182]Edgar López-López
, Jürgen Bajorath
, José L. Medina-Franco
:
Informatics for Chemistry, Biology, and Biomedical Sciences. J. Chem. Inf. Model. 61(1): 26-35 (2021) - [i14]José L. Medina-Franco
, Karina Martínez-Mayorga, Eli Fernández-de Gortari, Johannes Kirchmair
, Jürgen Bajorath
:
Rationality over fashion and hype in drug design. F1000Research 10: 397 (2021) - 2020
- [j181]Filip Miljkovic
, Jürgen Bajorath
:
Data structures for computational compound promiscuity analysis and exemplary applications to inhibitors of the human kinome. J. Comput. Aided Mol. Des. 34(1): 1-10 (2020) - [j180]Dagmar Stumpfe, Huabin Hu, Jürgen Bajorath
:
Advances in exploring activity cliffs. J. Comput. Aided Mol. Des. 34(9): 929-942 (2020) - [j179]Huabin Hu, Jürgen Bajorath
:
Simplified activity cliff network representations with high interpretability and immediate access to SAR information. J. Comput. Aided Mol. Des. 34(9): 943-952 (2020) - [j178]Raquel Rodríguez-Pérez
, Jürgen Bajorath
:
Interpretation of machine learning models using shapley values: application to compound potency and multi-target activity predictions. J. Comput. Aided Mol. Des. 34(10): 1013-1026 (2020) - [j177]Dimitar G. Yonchev
, Jürgen Bajorath
:
DeepCOMO: from structure-activity relationship diagnostics to generative molecular design using the compound optimization monitor methodology. J. Comput. Aided Mol. Des. 34(12): 1207-1218 (2020) - [j176]Javed Iqbal, Martin Vogt, Jürgen Bajorath
:
Activity landscape image analysis using convolutional neural networks. J. Cheminformatics 12(1): 34 (2020) - [j175]Raquel Rodríguez-Pérez
, Filip Miljkovic
, Jürgen Bajorath
:
Assessing the information content of structural and protein-ligand interaction representations for the classification of kinase inhibitor binding modes via machine learning and active learning. J. Cheminformatics 12(1): 36 (2020) - [j174]Dagmar Stumpfe, Jürgen Bajorath
:
Current Trends, Overlooked Issues, and Unmet Challenges in Virtual Screening. J. Chem. Inf. Model. 60(9): 4112-4115 (2020) - [j173]Gerald M. Maggiora, José L. Medina-Franco
, Javed Iqbal, Martin Vogt
, Jürgen Bajorath
:
From Qualitative to Quantitative Analysis of Activity and Property Landscapes. J. Chem. Inf. Model. 60(12): 5873-5880 (2020) - [i13]Martin Vogt
, Jürgen Bajorath
:
ccbmlib - a Python package for modeling Tanimoto similarity value distributions. F1000Research 9: 100 (2020)
2010 – 2019
- 2019
- [j172]Filip Miljkovic
, Martin Vogt, Jürgen Bajorath
:
Systematic computational identification of promiscuity cliff pathways formed by inhibitors of the human kinome. J. Comput. Aided Mol. Des. 33(6): 559-572 (2019) - [j171]Tomoyuki Miyao
, Swarit Jasial
, Jürgen Bajorath
, Kimito Funatsu
:
Evaluation of different virtual screening strategies on the basis of compound sets with characteristic core distributions and dissimilarity relationships. J. Comput. Aided Mol. Des. 33(8): 729-743 (2019) - [j170]Oliver Laufkötter
, Noé Sturm, Jürgen Bajorath, Hongming Chen, Ola Engkvist
:
Combining structural and bioactivity-based fingerprints improves prediction performance and scaffold hopping capability. J. Cheminformatics 11(1): 54:1-54:14 (2019) - [j169]J. Jesús Naveja
, B. Angélica Pilón-Jiménez
, Jürgen Bajorath
, José L. Medina-Franco
:
A general approach for retrosynthetic molecular core analysis. J. Cheminformatics 11(1): 61:1-61:9 (2019) - [j168]Iuri Casciuc, Yuliana Zabolotna
, Dragos Horvath
, Gilles Marcou
, Jürgen Bajorath
, Alexandre Varnek
:
Virtual Screening with Generative Topographic Maps: How Many Maps Are Required? J. Chem. Inf. Model. 59(1): 564-572 (2019) - [j167]Tomoyuki Miyao, Kimito Funatsu
, Jürgen Bajorath
:
Exploring Alternative Strategies for the Identification of Potent Compounds Using Support Vector Machine and Regression Modeling. J. Chem. Inf. Model. 59(3): 983-992 (2019) - [j166]Tomoyuki Miyao, Kimito Funatsu
, Jürgen Bajorath
:
Three-Dimensional Activity Landscape Models of Different Design and Their Application to Compound Mapping and Potency Prediction. J. Chem. Inf. Model. 59(3): 993-1004 (2019) - [j165]J. Jesús Naveja
, Dagmar Stumpfe, José L. Medina-Franco
, Jürgen Bajorath
:
Exploration of Target Synergy in Cancer Treatment by Cell-Based Screening Assay and Network Propagation Analysis. J. Chem. Inf. Model. 59(6): 3072-3079 (2019) - [j164]Atsushi Yoshimori, Yuichi Horita, Toru Tanoue, Jürgen Bajorath
:
Method for Systematic Analogue Search Using the Mega SAR Matrix Database. J. Chem. Inf. Model. 59(9): 3727-3734 (2019) - [i12]Jürgen Bajorath
:
Repositioning the Chemical Information Science Gateway. F1000Research 8: 976 (2019) - 2018
- [j163]Ryo Kunimoto
, Jürgen Bajorath
:
Design of a tripartite network for the prediction of drug targets. J. Comput. Aided Mol. Des. 32(2): 321-330 (2018) - [j162]Tomoyuki Miyao, Jürgen Bajorath
:
Exploring ensembles of bioactive or virtual analogs of X-ray ligands for shape similarity searching. J. Comput. Aided Mol. Des. 32(7): 759-767 (2018) - 2017
- [j161]Dilyana Dimova, Jürgen Bajorath
:
Is scaffold hopping a reliable indicator for the ability of computational methods to identify structurally diverse active compounds? J. Comput. Aided Mol. Des. 31(7): 603-608 (2017) - [j160]Ryo Kunimoto
, Jürgen Bajorath
:
Exploring sets of molecules from patents and relationships to other active compounds in chemical space networks. J. Comput. Aided Mol. Des. 31(9): 779-788 (2017) - [j159]Shilva Kayastha, Ryo Kunimoto
, Dragos Horvath, Alexandre Varnek, Jürgen Bajorath
:
From bird's eye views to molecular communities: two-layered visualization of structure-activity relationships in large compound data sets. J. Comput. Aided Mol. Des. 31(11): 961-977 (2017) - [j158]Raquel Rodríguez-Pérez
, Martin Vogt, Jürgen Bajorath
:
Influence of Varying Training Set Composition and Size on Support Vector Machine-Based Prediction of Active Compounds. J. Chem. Inf. Model. 57(4): 710-716 (2017) - [j157]Shilva Kayastha, Dragos Horvath
, Erik Gilberg, Michael Gütschow, Jürgen Bajorath
, Alexandre Varnek
:
Privileged Structural Motif Detection and Analysis Using Generative Topographic Maps. J. Chem. Inf. Model. 57(5): 1218-1232 (2017) - [i11]Thomas Blaschke, Marcus Olivecrona, Ola Engkvist
, Jürgen Bajorath, Hongming Chen:
Application of generative autoencoder in de novo molecular design. CoRR abs/1711.07839 (2017) - [i10]Tomoyuki Miyao, Kimito Funatsu, Jürgen Bajorath
:
Exploring differential evolution for inverse QSAR analysis. F1000Research 6: 1285- (2017) - [i9]Jürgen Bajorath
:
Expanding the chemical information science gateway. F1000Research 6: 1764- (2017) - 2016
- [j156]Mengjun Wu, Martin Vogt, Gerald M. Maggiora
, Jürgen Bajorath:
Design of chemical space networks on the basis of Tversky similarity. J. Comput. Aided Mol. Des. 30(1): 1-12 (2016) - [j155]Martin Vogt, Dagmar Stumpfe, Gerald M. Maggiora
, Jürgen Bajorath:
Lessons learned from the design of chemical space networks and opportunities for new applications. J. Comput. Aided Mol. Des. 30(3): 191-208 (2016) - [j154]Andrew Anighoro, Jürgen Bajorath:
Binding mode similarity measures for ranking of docking poses: a case study on the adenosine A2A receptor. J. Comput. Aided Mol. Des. 30(6): 447-456 (2016) - [j153]Ryo Kunimoto
, Martin Vogt, Jürgen Bajorath:
Maximum common substructure-based Tversky index: an asymmetric hybrid similarity measure. J. Comput. Aided Mol. Des. 30(7): 523-531 (2016) - [j152]Andrew Anighoro, Antonio de la Vega de León
, Jürgen Bajorath:
Predicting bioactive conformations and binding modes of macrocycles. J. Comput. Aided Mol. Des. 30(10): 841-849 (2016) - [j151]Swarit Jasial
, Ye Hu, Jürgen Bajorath:
Assessing the Growth of Bioactive Compounds and Scaffolds over Time: Implications for Lead Discovery and Scaffold Hopping. J. Chem. Inf. Model. 56(2): 300-307 (2016) - [j150]Andrew Anighoro, Jürgen Bajorath:
Three-Dimensional Similarity in Molecular Docking: Prioritizing Ligand Poses on the Basis of Experimental Binding Modes. J. Chem. Inf. Model. 56(3): 580-587 (2016) - [j149]Dragos Horvath, Gilles Marcou
, Alexandre Varnek, Shilva Kayastha, Antonio de la Vega de León
, Jürgen Bajorath:
Prediction of Activity Cliffs Using Condensed Graphs of Reaction Representations, Descriptor Recombination, Support Vector Machine Classification, and Support Vector Regression. J. Chem. Inf. Model. 56(9): 1631-1640 (2016) - [i8]Swarit Jasial
, Ye Hu, Martin Vogt
, Jürgen Bajorath
:
Activity-relevant similarity values for fingerprints and implications for similarity searching. F1000Research 5: 591 (2016) - [i7]Ye Hu, Jürgen Bajorath
:
Analyzing compound activity records and promiscuity degrees in light of publication statistics. F1000Research 5: 1227 (2016) - [i6]Antonio de la Vega de León
, Jürgen Bajorath
:
Design of chemical space networks incorporating compound distance relationships. F1000Research 5: 2634 (2016) - 2015
- [j148]Magdalena Zwierzyna
, Martin Vogt, Gerald M. Maggiora
, Jürgen Bajorath:
Design and characterization of chemical space networks for different compound data sets. J. Comput. Aided Mol. Des. 29(2): 113-125 (2015) - [j147]Roman Garnett, Thomas Gärtner
, Martin Vogt, Jürgen Bajorath:
Introducing the 'active search' method for iterative virtual screening. J. Comput. Aided Mol. Des. 29(4): 305-314 (2015) - [j146]Bijun Zhang, Martin Vogt, Gerald M. Maggiora
, Jürgen Bajorath:
Comparison of bioactive chemical space networks generated using substructure- and fingerprint-based measures of molecular similarity. J. Comput. Aided Mol. Des. 29(7): 595-608 (2015) - [j145]Antonio de la Vega de León, Shilva Kayastha, Dilyana Dimova, Thomas Schultz, Jürgen Bajorath:
Visualization of multi-property landscapes for compound selection and optimization. J. Comput. Aided Mol. Des. 29(8): 695-705 (2015) - [j144]Bijun Zhang, Martin Vogt, Gerald M. Maggiora
, Jürgen Bajorath:
Design of chemical space networks using a Tanimoto similarity variant based upon maximum common substructures. J. Comput. Aided Mol. Des. 29(10): 937-950 (2015) - [j143]Bijun Zhang, Martin Vogt, Gerald M. Maggiora
, Jürgen Bajorath:
Erratum to: Design of chemical space networks using a Tanimoto similarity variant based upon maximum common substructures. J. Comput. Aided Mol. Des. 29(11): 1071-1072 (2015) - [j142]Andrew Anighoro, Dagmar Stumpfe, Kathrin Heikamp, Kristin Beebe, Leonard M. Neckers, Jürgen Bajorath, Giulio Rastelli
:
Computational Polypharmacology Analysis of the Heat Shock Protein 90 Interactome. J. Chem. Inf. Model. 55(3): 676-686 (2015) - [j141]Jenny Balfer, Jürgen Bajorath:
Visualization and Interpretation of Support Vector Machine Activity Predictions. J. Chem. Inf. Model. 55(6): 1136-1147 (2015) - [i5]Disha Gupta-Ostermann, Yoichiro Hirose, Takenao Odagami, Hiroyuki Kouji, Jürgen Bajorath
:
Follow-up: Prospective compound design using the 'SAR Matrix' method and matrix-derived conditional probabilities of activity. F1000Research 4: 75 (2015) - [i4]Ye Hu, Norbert Furtmann, Dagmar Stumpfe, Jürgen Bajorath
:
Comprehensive knowledge base of two- and three-dimensional activity cliffs for medicinal and computational chemistry. F1000Research 4: 168 (2015) - [i3]Ye Hu, Bijun Zhang, Martin Vogt
, Jürgen Bajorath
:
AnalogExplorer2 - Stereochemistry sensitive graphical analysis of large analog series. F1000Research 4: 1031 (2015) - 2014
- [j140]Gerald M. Maggiora
, Jürgen Bajorath:
Chemical space networks: a powerful new paradigm for the description of chemical space. J. Comput. Aided Mol. Des. 28(8): 795-802 (2014) - [j139]Bijun Zhang, Martin Vogt, Jürgen Bajorath:
Design of an activity landscape view taking compound-based feature probabilities into account. J. Comput. Aided Mol. Des. 28(9): 919-926 (2014) - [j138]Antonio de la Vega de León, Jürgen Bajorath:
Compound optimization through data set-dependent chemical transformations. J. Cheminformatics 6(S-1): 5 (2014) - [j137]Norbert Furtmann, Jürgen Bajorath:
Evaluation of molecular model-based discovery of ecto-5'-nucleotidase inhibitors on the basis of X-ray structures. J. Cheminformatics 6(S-1): 13 (2014) - [j136]Shilva Kayastha, Dilyana Dimova, Preeti Iyer, Martin Vogt, Jürgen Bajorath:
Large-Scale Assessment of Activity Landscape Feature Probabilities of Bioactive Compounds. J. Chem. Inf. Model. 54(2): 442-450 (2014) - [j135]Dagmar Stumpfe, Dilyana Dimova, Jürgen Bajorath:
Composition and Topology of Activity Cliff Clusters Formed by Bioactive Compounds. J. Chem. Inf. Model. 54(2): 451-461 (2014) - [j134]Disha Gupta-Ostermann, Veerabahu Shanmugasundaram
, Jürgen Bajorath:
Neighborhood-Based Prediction of Novel Active Compounds from SAR Matrices. J. Chem. Inf. Model. 54(3): 801-809 (2014) - [j133]Vigneshwaran Namasivayam
, Disha Gupta-Ostermann, Jenny Balfer, Kathrin Heikamp, Jürgen Bajorath:
Prediction of Compounds in Different Local Structure-Activity Relationship Environments Using Emerging Chemical Patterns. J. Chem. Inf. Model. 54(5): 1301-1310 (2014) - [j132]Jenny Balfer, Jürgen Bajorath:
Introduction of a Methodology for Visualization and Graphical Interpretation of Bayesian Classification Models. J. Chem. Inf. Model. 54(9): 2451-2468 (2014) - [j131]Antonio de la Vega de León
, Jürgen Bajorath:
Prediction of Compound Potency Changes in Matched Molecular Pairs Using Support Vector Regression. J. Chem. Inf. Model. 54(10): 2654-2663 (2014) - [j130]Ye Hu, Jürgen Bajorath:
Influence of Search Parameters and Criteria on Compound Selection, Promiscuity, and Pan Assay Interference Characteristics. J. Chem. Inf. Model. 54(11): 3056-3066 (2014) - [i2]Ye Hu, Jürgen Bajorath
:
Compound data sets and software tools for chemoinformatics and medicinal chemistry applications: update and data transfer. F1000Research 3: 69 (2014) - 2013
- [j129]Ye Hu, Gerald M. Maggiora
, Jürgen Bajorath:
Activity cliffs in PubChem confirmatory bioassays taking inactive compounds into account. J. Comput. Aided Mol. Des. 27(2): 115-124 (2013) - [j128]Disha Gupta-Ostermann, Ye Hu, Jürgen Bajorath:
Systematic mining of analog series with related core structures in multi-target activity space. J. Comput. Aided Mol. Des. 27(8): 665-674 (2013) - [j127]Martin Vogt, Jürgen Bajorath:
Statistical modeling of value distributions of similarity coefficients in virtual screening and its application to predicting fingerprint search performance. J. Cheminformatics 5(S-1): 5 (2013) - [j126]Ye Hu, Jürgen Bajorath:
Systematic Identification of Scaffolds Representing Compounds Active against Individual Targets and Single or Multiple Target Families. J. Chem. Inf. Model. 53(2): 312-326 (2013) - [j125]Ye Hu, Jürgen Bajorath:
Introduction of Target Cliffs as a Concept To Identify and Describe Complex Molecular Selectivity Patterns. J. Chem. Inf. Model. 53(3): 545-552 (2013) - [j124]Mohsen Ahmadi, Martin Vogt, Preeti Iyer, Jürgen Bajorath, Holger Fröhlich
:
Predicting Potent Compounds via Model-Based Global Optimization. J. Chem. Inf. Model. 53(3): 553-559 (2013) - [j123]Kathrin Heikamp, Jürgen Bajorath:
Prediction of Compounds with Closely Related Activity Profiles Using Weighted Support Vector Machine Linear Combinations. J. Chem. Inf. Model. 53(4): 791-801 (2013) - [j122]Dagmar Stumpfe, Dilyana Dimova, Kathrin Heikamp, Jürgen Bajorath:
Compound Pathway Model To Capture SAR Progression: Comparison of Activity Cliff-Dependent and -Independent Pathways. J. Chem. Inf. Model. 53(5): 1067-1072 (2013) - [j121]Antonio de la Vega de León
, Jürgen Bajorath:
Compound Optimization through Data Set-Dependent Chemical Transformations. J. Chem. Inf. Model. 53(6): 1263-1271 (2013) - [j120]Vigneshwaran Namasivayam
, Ye Hu, Jenny Balfer, Jürgen Bajorath:
Classification of Compounds with Distinct or Overlapping Multi-Target Activities and Diverse Molecular Mechanisms Using Emerging Chemical Patterns. J. Chem. Inf. Model. 53(6): 1272-1281 (2013) - [j119]Bijun Zhang, Ye Hu, Jürgen Bajorath:
SAR Transfer across Different Targets. J. Chem. Inf. Model. 53(7): 1589-1594 (2013) - [j118]Kathrin Heikamp, Jürgen Bajorath:
Comparison of Confirmed Inactive and Randomly Selected Compounds as Negative Training Examples in Support Vector Machine-Based Virtual Screening. J. Chem. Inf. Model. 53(7): 1595-1601 (2013) - [j117]Martin Vogt, Preeti Iyer, Gerald M. Maggiora
, Jürgen Bajorath:
Conditional Probabilities of Activity Landscape Features for Individual Compounds. J. Chem. Inf. Model. 53(7): 1602-1612 (2013) - [j116]Martin Vogt, Jürgen Bajorath:
Similarity Searching for Potent Compounds Using Feature Selection. J. Chem. Inf. Model. 53(7): 1613-1619 (2013) - [j115]Jenny Balfer, Martin Vogt, Jürgen Bajorath:
Searching for Closely Related Ligands with Different Mechanisms of Action Using Machine Learning and Mapping Algorithms. J. Chem. Inf. Model. 53(9): 2252-2274 (2013) - [j114]Dilyana Dimova, Dagmar Stumpfe, Jürgen Bajorath:
Quantifying the Fingerprint Descriptor Dependence of Structure-Activity Relationship Information on a Large Scale. J. Chem. Inf. Model. 53(9): 2275-2281 (2013) - [j113]Vigneshwaran Namasivayam
, Preeti Iyer, Jürgen Bajorath:
Prediction of Individual Compounds Forming Activity Cliffs Using Emerging Chemical Patterns. J. Chem. Inf. Model. 53(12): 3131-3139 (2013) - [p1]Jens Auer, Martin Vogt, Jürgen Bajorath:
Emerging Chemical Patterns - Theory and Applications. Contrast Data Mining 2013: 253-268 - 2012
- [j112]Jürgen Bajorath:
Computational chemistry in pharmaceutical research: at the crossroads. J. Comput. Aided Mol. Des. 26(1): 11-12 (2012) - [j111]Ruifang Li
, Jürgen Bajorath:
Systematic assessment of scaffold distances in ChEMBL: prioritization of compound data sets for scaffold hopping analysis in virtual screening. J. Comput. Aided Mol. Des. 26(10): 1101-1109 (2012) - [j110]Anne Mai Wassermann, Jürgen Bajorath:
A computational method to facilitate structure-activity relationship transfer. J. Cheminformatics 4(S-1): 3 (2012) - [j109]Dilyana Dimova, Jürgen Bajorath:
Design of multi-target activity landscapes that capture hierarchical activity cliff distributions. J. Cheminformatics 4(S-1): 4 (2012) - [j108]Kathrin Heikamp, Anne Mai Wassermann, Jürgen Bajorath:
Potency-directed similarity searching using support vector machines. J. Cheminformatics 4(S-1): 12 (2012) - [j107]Ye Hu, Jürgen Bajorath:
Exploration of 3D Activity Cliffs on the Basis of Compound Binding Modes and Comparison of 2D and 3D Cliffs. J. Chem. Inf. Model. 52(3): 670-677 (2012) - [j106]Vigneshwaran Namasivayam
, Jürgen Bajorath:
Searching for Coordinated Activity Cliffs Using Particle Swarm Optimization. J. Chem. Inf. Model. 52(4): 927-934 (2012) - [j105]Disha Gupta-Ostermann, Mathias Wawer, Anne Mai Wassermann, Jürgen Bajorath:
Graph Mining for SAR Transfer Series. J. Chem. Inf. Model. 52(4): 935-942 (2012) - [j104]Xiaoying Hu, Ye Hu, Martin Vogt, Dagmar Stumpfe, Jürgen Bajorath:
MMP-Cliffs: Systematic Identification of Activity Cliffs on the Basis of Matched Molecular Pairs. J. Chem. Inf. Model. 52(5): 1138-1145 (2012) - [j103]Ye Hu, Norbert Furtmann, Michael Gütschow, Jürgen Bajorath:
Systematic Identification and Classification of Three-Dimensional Activity Cliffs. J. Chem. Inf. Model. 52(6): 1490-1498 (2012) - [j102]Anne Mai Wassermann, Peter Haebel, Nils Weskamp
, Jürgen Bajorath:
SAR Matrices: Automated Extraction of Information-Rich SAR Tables from Large Compound Data Sets. J. Chem. Inf. Model. 52(7): 1769-1776 (2012) - [j101]Ye Hu, Jürgen Bajorath:
Extending the Activity Cliff Concept: Structural Categorization of Activity Cliffs and Systematic Identification of Different Types of Cliffs in the ChEMBL Database. J. Chem. Inf. Model. 52(7): 1806-1811 (2012) - [j100]Preeti Iyer, Dilyana Dimova, Martin Vogt, Jürgen Bajorath:
Navigating High-Dimensional Activity Landscapes: Design and Application of the Ligand-Target Differentiation Map. J. Chem. Inf. Model. 52(8): 1962-1969 (2012) - [j99]Dagmar Stumpfe, Jürgen Bajorath:
Frequency of Occurrence and Potency Range Distribution of Activity Cliffs in Bioactive Compounds. J. Chem. Inf. Model. 52(9): 2348-2353 (2012) - [j98]Kathrin Heikamp, Xiaoying Hu, Aixia Yan
, Jürgen Bajorath:
Prediction of Activity Cliffs Using Support Vector Machines. J. Chem. Inf. Model. 52(9): 2354-2365 (2012) - [j97]Ye Hu, Jürgen Bajorath:
Growth of Ligand-Target Interaction Data in ChEMBL Is Associated with Increasing and Activity Measurement-Dependent Compound Promiscuity. J. Chem. Inf. Model. 52(10): 2550-2558 (2012) - [j96]Disha Gupta-Ostermann, Jürgen Bajorath:
Identification of Multitarget Activity Ridges in High-Dimensional Bioactivity Spaces. J. Chem. Inf. Model. 52(10): 2579-2586 (2012) - [j95]Vigneshwaran Namasivayam
, Jürgen Bajorath:
Multiobjective Particle Swarm Optimization: Automated Identification of Structure-Activity Relationship-Informative Compounds with Favorable Physicochemical Property Distributions. J. Chem. Inf. Model. 52(11): 2848-2855 (2012) - [j94]Antonio de la Vega de León
, Jürgen Bajorath:
Design of a Three-Dimensional Multitarget Activity Landscape. J. Chem. Inf. Model. 52(11): 2876-2883 (2012) - [j93]Bijun Zhang, Anne Mai Wassermann, Martin Vogt, Jürgen Bajorath:
Systematic Assessment of Compound Series with SAR Transfer Potential. J. Chem. Inf. Model. 52(12): 3138-3143 (2012) - [i1]Ye Hu, Jürgen Bajorath
:
Freely available compound data sets and software tools for chemoinformatics and computational medicinal chemistry applications. F1000Research 1: 11 (2012) - 2011
- [j92]Ye Hu, Jürgen Bajorath:
Combining Horizontal and Vertical Substructure Relationships in Scaffold Hierarchies for Activity Prediction. J. Chem. Inf. Model. 51(2): 248-257 (2011) - [j91]Dilyana Dimova, Mathias Wawer, Anne Mai Wassermann, Jürgen Bajorath:
Design of Multitarget Activity Landscapes That Capture Hierarchical Activity Cliff Distributions. J. Chem. Inf. Model. 51(2): 258-266 (2011) - [j90]Anne Mai Wassermann, Britta Nisius, Martin Vogt, Jürgen Bajorath:
Correction to Identification of Descriptors Capturing Compound Class-Specific Features by Mutual Information Analysis. J. Chem. Inf. Model. 51(2): 508-509 (2011) - [j89]Preeti Iyer, Ye Hu, Jürgen Bajorath:
SAR Monitoring of Evolving Compound Data Sets Using Activity Landscapes. J. Chem. Inf. Model. 51(3): 532-540 (2011) - [j88]Peter Ripphausen, Britta Nisius, Mathias Wawer, Jürgen Bajorath:
Rationalizing the Role of SAR Tolerance for Ligand-Based Virtual Screening. J. Chem. Inf. Model. 51(4): 837-842 (2011) - [j87]Preeti Iyer, Dagmar Stumpfe, Jürgen Bajorath:
Molecular Mechanism-Based Network-like Similarity Graphs Reveal Relationships between Different Types of Receptor Ligands and Structural Changes that Determine Agonistic, Inverse-Agonistic, and Antagonistic Effects. J. Chem. Inf. Model. 51(6): 1281-1286 (2011) - [j86]Vigneshwaran Namasivayam
, Preeti Iyer, Jürgen Bajorath:
Extraction of Discontinuous Structure-Activity Relationships from Compound Data Sets through Particle Swarm Optimization. J. Chem. Inf. Model. 51(7): 1545-1551 (2011) - [j85]Ye Hu, Dagmar Stumpfe, Jürgen Bajorath:
Lessons Learned from Molecular Scaffold Analysis. J. Chem. Inf. Model. 51(8): 1742-1753 (2011) - [j84]Kathrin Heikamp, Jürgen Bajorath:
Large-Scale Similarity Search Profiling of ChEMBL Compound Data Sets. J. Chem. Inf. Model. 51(8): 1831-1839 (2011) - [j83]Martin Vogt, Yun Huang, Jürgen Bajorath:
From Activity Cliffs to Activity Ridges: Informative Data Structures for SAR Analysis. J. Chem. Inf. Model. 51(8): 1848-1856 (2011) - [j82]Anne Mai Wassermann, Jürgen Bajorath:
A Data Mining Method To Facilitate SAR Transfer. J. Chem. Inf. Model. 51(8): 1857-1866 (2011) - [j81]Kathrin Heikamp, Jürgen Bajorath:
How Do 2D Fingerprints Detect Structurally Diverse Active Compounds? Revealing Compound Subset-Specific Fingerprint Features through Systematic Selection. J. Chem. Inf. Model. 51(9): 2254-2265 (2011) - [j80]Peter Ripphausen, Anne Mai Wassermann, Jürgen Bajorath:
REPROVIS-DB: A Benchmark System for Ligand-Based Virtual Screening Derived from Reproducible Prospective Applications. J. Chem. Inf. Model. 51(10): 2467-2473 (2011) - [j79]Martin Vogt, Jürgen Bajorath:
Introduction of the Conditional Correlated Bernoulli Model of Similarity Value Distributions and its Application to the Prospective Prediction of Fingerprint Search Performance. J. Chem. Inf. Model. 51(10): 2496-2506 (2011) - [j78]Ruifang Li
, Dagmar Stumpfe, Martin Vogt, Hanna Geppert, Jürgen Bajorath:
Development of a Method To Consistently Quantify the Structural Distance between Scaffolds and To Assess Scaffold Hopping Potential. J. Chem. Inf. Model. 51(10): 2507-2514 (2011) - [j77]Preeti Iyer, Ye Hu, Jürgen Bajorath:
SAR Monitoring of Evolving Compound Data Sets Using Activity Landscapes. J. Chem. Inf. Model. 51(11): 3026 (2011) - [j76]Dagmar Stumpfe, Jürgen Bajorath:
Assessing the Confidence Level of Public Domain Compound Activity Data and the Impact of Alternative Potency Measurements on SAR Analysis. J. Chem. Inf. Model. 51(12): 3131-3137 (2011) - [j75]Ye Hu, Jürgen Bajorath:
Target Family-Directed Exploration of Scaffolds with Different SAR Profiles. J. Chem. Inf. Model. 51(12): 3138-3148 (2011) - 2010
- [j74]Martin Vogt, Anne Mai Wassermann, Jürgen Bajorath:
Application of Information - Theoretic Concepts in Chemoinformatics. Inf. 1(2): 60-73 (2010) - [j73]Eugen Lounkine, Jürgen Bajorath:
Adaptation of formal concept analysis for the systematic exploration of structure-activity and structure-selectivity relationships. J. Cheminformatics 2(S-1): 21 (2010) - [j72]Mathias Wawer, Lisa Peltason, Jürgen Bajorath:
Systematic extraction of structure-activity relationship information from biological screening data. J. Cheminformatics 2(S-1): 22 (2010) - [j71]Eugen Lounkine, Mathias Wawer, Anne Mai Wassermann, Jürgen Bajorath:
SARANEA: A Freely Available Program To Mine Structure-Activity and Structure-Selectivity Relationship Information in Compound Data Sets. J. Chem. Inf. Model. 50(1): 68-78 (2010) - [j70]José Batista
, Lu Tan, Jürgen Bajorath:
Atom-Centered Interacting Fragments and Similarity Search Applications. J. Chem. Inf. Model. 50(1): 79-86 (2010) - [j69]Hanna Geppert, Martin Vogt, Jürgen Bajorath:
Current Trends in Ligand-Based Virtual Screening: Molecular Representations, Data Mining Methods, New Application Areas, and Performance Evaluation. J. Chem. Inf. Model. 50(2): 205-216 (2010) - [j68]Hany E. A. Ahmed, Martin Vogt, Jürgen Bajorath:
Design and Evaluation of Bonded Atom Pair Descriptors. J. Chem. Inf. Model. 50(4): 487-499 (2010) - [j67]Ye Hu, Jürgen Bajorath:
Molecular Scaffolds with High Propensity to Form Multi-Target Activity Cliffs. J. Chem. Inf. Model. 50(4): 500-510 (2010) - [j66]Lisa Peltason, Preeti Iyer, Jürgen Bajorath:
Rationalizing Three-Dimensional Activity Landscapes and the Influence of Molecular Representations on Landscape Topology and the Formation of Activity Cliffs. J. Chem. Inf. Model. 50(6): 1021-1033 (2010) - [j65]Lu Tan, José Batista
, Jürgen Bajorath:
Rationalization of the Performance and Target Dependence of Similarity Searching Incorporating Protein-Ligand Interaction Information. J. Chem. Inf. Model. 50(6): 1042-1052 (2010) - [j64]Anne Mai Wassermann, Jürgen Bajorath:
Chemical Substitutions That Introduce Activity Cliffs Across Different Compound Classes and Biological Targets. J. Chem. Inf. Model. 50(7): 1248-1256 (2010) - [j63]Mathias Wawer, Jürgen Bajorath:
Similarity-Potency Trees: A Method to Search for SAR Information in Compound Data Sets and Derive SAR Rules. J. Chem. Inf. Model. 50(8): 1395-1409 (2010) - [j62]Anne Mai Wassermann, Britta Nisius, Martin Vogt, Jürgen Bajorath:
Identification of Descriptors Capturing Compound Class-Specific Features by Mutual Information Analysis. J. Chem. Inf. Model. 50(11): 1935-1940 (2010) - [j61]Ye Hu, Jürgen Bajorath:
Polypharmacology Directed Compound Data Mining: Identification of Promiscuous Chemotypes with Different Activity Profiles and Comparison to Approved Drugs. J. Chem. Inf. Model. 50(12): 2112-2118 (2010)
2000 – 2009
- 2009
- [j60]Eugen Lounkine, Jürgen Bajorath:
Topological Fragment Index for the Analysis of Molecular Substructures and Their Topological Environment in Active Compounds. J. Chem. Inf. Model. 49(2): 162-168 (2009) - [j59]Eugen Lounkine, Ye Hu, José Batista
, Jürgen Bajorath:
Relevance of Feature Combinations for Similarity Searching Using General or Activity Class-Directed Molecular Fingerprints. J. Chem. Inf. Model. 49(3): 561-570 (2009) - [j58]Anne Mai Wassermann, Hanna Geppert, Jürgen Bajorath:
Searching for Target-Selective Compounds Using Different Combinations of Multiclass Support Vector Machine Ranking Methods, Kernel Functions, and Fingerprint Descriptors. J. Chem. Inf. Model. 49(3): 582-592 (2009) - [j57]Hanna Geppert, Jens Humrich, Dagmar Stumpfe, Thomas Gärtner
, Jürgen Bajorath:
Ligand Prediction from Protein Sequence and Small Molecule Information Using Support Vector Machines and Fingerprint Descriptors. J. Chem. Inf. Model. 49(4): 767-779 (2009) - [j56]Britta Nisius, Martin Vogt, Jürgen Bajorath:
Development of a Fingerprint Reduction Approach for Bayesian Similarity Searching Based on Kullback-Leibler Divergence Analysis. J. Chem. Inf. Model. 49(6): 1347-1358 (2009) - [j55]Eugen Lounkine, Dagmar Stumpfe, Jürgen Bajorath:
Molecular Formal Concept Analysis for Compound Selectivity Profiling in Biologically Annotated Databases. J. Chem. Inf. Model. 49(6): 1359-1368 (2009) - [j54]Yuan Wang, Jürgen Bajorath:
Development of a Compound Class-Directed Similarity Coefficient That Accounts for Molecular Complexity Effects in Fingerprint Searching. J. Chem. Inf. Model. 49(6): 1369-1376 (2009) - [j53]Yuan Wang, Hanna Geppert, Jürgen Bajorath:
Shannon Entropy-Based Fingerprint Similarity Search Strategy. J. Chem. Inf. Model. 49(7): 1687-1691 (2009) - [j52]Anne Mai Wassermann, Hanna Geppert, Jürgen Bajorath:
Ligand Prediction for Orphan Targets Using Support Vector Machines and Various Target-Ligand Kernels Is Dominated by Nearest Neighbor Effects. J. Chem. Inf. Model. 49(10): 2155-2167 (2009) - [j51]Mihiret Tekeste Sisay, Lisa Peltason, Jürgen Bajorath:
Structural Interpretation of Activity Cliffs Revealed by Systematic Analysis of Structure-Activity Relationships in Analog Series. J. Chem. Inf. Model. 49(10): 2179-2189 (2009) - [j50]Martin Vogt, Britta Nisius, Jürgen Bajorath:
Predicting the similarity search performance of fingerprints and their combination with molecular property descriptors using probabilistic and information theoretic modeling. Stat. Anal. Data Min. 2(2): 123-134 (2009) - 2008
- [j49]Yuan Wang, Jürgen Bajorath:
Balancing the Influence of Molecular Complexity on Fingerprint Similarity Searching. J. Chem. Inf. Model. 48(1): 75-84 (2008) - [j48]Martin Vogt, Jürgen Bajorath:
Bayesian Similarity Searching in High-Dimensional Descriptor Spaces Combined with Kullback-Leibler Descriptor Divergence Analysis. J. Chem. Inf. Model. 48(2): 247-255 (2008) - [j47]Hanna Geppert, Tamás Horváth, Thomas Gärtner
, Stefan Wrobel, Jürgen Bajorath:
Support-Vector-Machine-Based Ranking Significantly Improves the Effectiveness of Similarity Searching Using 2D Fingerprints and Multiple Reference Compounds. J. Chem. Inf. Model. 48(4): 742-746 (2008) - [j46]Eugen Lounkine, Jürgen Bajorath:
Core Trees and Consensus Fragment Sequences for Molecular Representation and Similarity Analysis. J. Chem. Inf. Model. 48(6): 1161-1166 (2008) - [j45]Ingo Vogt, Jürgen Bajorath:
Design and Exploration of Target-Selective Chemical Space Representations. J. Chem. Inf. Model. 48(7): 1389-1395 (2008) - [j44]Jens Auer, Jürgen Bajorath:
Distinguishing between Bioactive and Modeled Compound Conformations through Mining of Emerging Chemical Patterns. J. Chem. Inf. Model. 48(9): 1747-1753 (2008) - [j43]Yuan Wang, Jürgen Bajorath:
Bit Silencing in Fingerprints Enables the Derivation of Compound Class-Directed Similarity Metrics. J. Chem. Inf. Model. 48(9): 1754-1759 (2008) - [j42]Thomas J. Crisman
, Mihiret Tekeste Sisay, Jürgen Bajorath:
Ligand-Target Interaction-Based Weighting of Substructures for Virtual Screening. J. Chem. Inf. Model. 48(10): 1955-1964 (2008) - [j41]Lu Tan, Eugen Lounkine, Jürgen Bajorath:
Similarity Searching Using Fingerprints of Molecular Fragments Involved in Protein-Ligand Interactions. J. Chem. Inf. Model. 48(12): 2308-2312 (2008) - 2007
- [j40]Martin Vogt, Jeffrey W. Godden, Jürgen Bajorath:
Bayesian Interpretation of a Distance Function for Navigating High-Dimensional Descriptor Spaces. J. Chem. Inf. Model. 47(1): 39-46 (2007) - [j39]José Batista
, Jürgen Bajorath:
Chemical Database Mining through Entropy-Based Molecular Similarity Assessment of Randomly Generated Structural Fragment Populations. J. Chem. Inf. Model. 47(1): 59-68 (2007) - [j38]Martin Vogt, Jürgen Bajorath:
Introduction of an Information-Theoretic Method to Predict Recovery Rates of Active Compounds for Bayesian in Silico Screening: Theory and Screening Trials. J. Chem. Inf. Model. 47(2): 337-341 (2007) - [j37]Ingo Vogt, Jürgen Bajorath:
Analysis of a High-Throughput Screening Data Set Using Potency-Scaled Molecular Similarity Algorithms. J. Chem. Inf. Model. 47(2): 367-375 (2007) - [j36]Hanna Eckert
, Jürgen Bajorath:
Exploring Peptide-likeness of Active Molecules Using 2D Fingerprint Methods. J. Chem. Inf. Model. 47(4): 1366-1378 (2007) - [j35]José Batista
, Jürgen Bajorath:
Mining of Randomly Generated Molecular Fragment Populations Uncovers Activity-Specific Fragment Hierarchies. J. Chem. Inf. Model. 47(4): 1405-1413 (2007) - [j34]Eugen Lounkine, José Batista
, Jürgen Bajorath:
Mapping of Activity-Specific Fragment Pathways Isolated from Random Fragment Populations Reveals the Formation of Coherent Molecular Cores. J. Chem. Inf. Model. 47(6): 2133-2139 (2007) - 2006
- [j33]Jeffrey W. Godden, Jürgen Bajorath:
A Distance Function for Retrieval of Active Molecules from Complex Chemical Space Representations. J. Chem. Inf. Model. 46(3): 1094-1097 (2006) - [j32]Hanna Eckert
, Ingo Vogt, Jürgen Bajorath:
Mapping Algorithms for Molecular Similarity Analysis and Ligand-Based Virtual Screening: Design of DynaMAD and Comparison with MAD and DMC. J. Chem. Inf. Model. 46(4): 1623-1634 (2006) - [j31]José Batista
, Jeffrey W. Godden, Jürgen Bajorath:
Assessment of Molecular Similarity from the Analysis of Randomly Generated Structural Fragment Populations. J. Chem. Inf. Model. 46(5): 1937-1944 (2006) - [j30]Jens Auer, Jürgen Bajorath:
Emerging Chemical Patterns: A New Methodology for Molecular Classification and Compound Selection. J. Chem. Inf. Model. 46(6): 2502-2514 (2006) - [j29]Hanna Eckert
, Jürgen Bajorath:
Design and Evaluation of a Novel Class-Directed 2D Fingerprint to Search for Structurally Diverse Active Compounds. J. Chem. Inf. Model. 46(6): 2515-2526 (2006) - 2005
- [j28]Jeffrey W. Godden, Florence L. Stahura, Jürgen Bajorath:
Anatomy of Fingerprint Search Calculations on Structurally Diverse Sets of Active Compounds. J. Chem. Inf. Model. 45(6): 1812-1819 (2005) - 2004
- [j27]Jeffrey W. Godden, John R. Furr, Ling Xue, Florence L. Stahura, Jürgen Bajorath:
Molecular Similarity Analysis and Virtual Screening by Mapping of Consensus Positions in Binary-Transformed Chemical Descriptor Spaces with Variable Dimensionality. J. Chem. Inf. Model. 44(1): 21-29 (2004) - [j26]Ling Xue, Jeffrey W. Godden, Florence L. Stahura, Jürgen Bajorath:
Similarity Search Profiles as a Diagnostic Tool for the Analysis of Virtual Screening Calculations. J. Chem. Inf. Model. 44(4): 1275-1281 (2004) - [j25]Ling Xue, Florence L. Stahura, Jürgen Bajorath:
Similarity Search Profiling Reveals Effects of Fingerprint Scaling in Virtual Screening. J. Chem. Inf. Model. 44(6): 2032-2039 (2004) - 2003
- [j24]Jeffrey W. Godden, John R. Furr, Jürgen Bajorath:
Recursive Median Partitioning for Virtual Screening of Large Databases. J. Chem. Inf. Comput. Sci. 43(1): 182-188 (2003) - [j23]Ling Xue, Jeffrey W. Godden, Florence L. Stahura, Jürgen Bajorath:
Design and Evaluation of a Molecular Fingerprint Involving the Transformation of Property Descriptor Values into a Binary Classification Scheme. J. Chem. Inf. Comput. Sci. 43(4): 1151-1157 (2003) - [j22]Ling Xue, Jeffrey W. Godden, Florence L. Stahura, Jürgen Bajorath:
Profile Scaling Increases the Similarity Search Performance of Molecular Fingerprints Containing Numerical Descriptors and Structural Keys. J. Chem. Inf. Comput. Sci. 43(4): 1218-1225 (2003) - 2002
- [j21]Jürgen Bajorath:
Chemoinformatics methods for systematic comparison of molecules from natural and synthetic sources and design of hybrid libraries. J. Comput. Aided Mol. Des. 16(5-6): 431-439 (2002) - [j20]Jeffrey W. Godden, Jürgen Bajorath:
Chemical Descriptors with Distinct Levels of Information Content and Varying Sensitivity to Differences between Selected Compound Databases Identified by SE-DSE Analysis. J. Chem. Inf. Comput. Sci. 42(1): 87-93 (2002) - [j19]Florence L. Stahura, Jeffrey W. Godden, Jürgen Bajorath:
Differential Shannon Entropy Analysis Identifies Molecular Property Descriptors that Predict Aqueous Solubility of Synthetic Compounds with High Accuracy in Binary QSAR Calculations. J. Chem. Inf. Comput. Sci. 42(3): 550-558 (2002) - [j18]Ling Xue, Jürgen Bajorath:
Accurate Partitioning of Compounds Belonging to Diverse Activity Classes. J. Chem. Inf. Comput. Sci. 42(3): 757-764 (2002) - [j17]Jeffrey W. Godden, Ling Xue, Douglas B. Kitchen
, Florence L. Stahura, E. James Schermerhorn, Jürgen Bajorath:
Median Partitioning: A Novel Method for the Selection of Representative Subsets from Large Compound Pools. J. Chem. Inf. Comput. Sci. 42(4): 885-893 (2002) - [j16]Jeffrey W. Godden, Ling Xue, Jürgen Bajorath:
Classification of Biologically Active Compounds by Median Partitioning. J. Chem. Inf. Comput. Sci. 42(5): 1263-1269 (2002) - 2001
- [j15]Jürgen Bajorath:
Selected Concepts and Investigations in Compound Classification, Molecular Descriptor Analysis, and Virtual Screening. J. Chem. Inf. Comput. Sci. 41(2): 233-245 (2001) - [j14]Ling Xue, Florence L. Stahura, Jeffrey W. Godden, Jürgen Bajorath:
Mini-fingerprints Detect Similar Activity of Receptor Ligands Previously Recognized Only by Three-Dimensional Pharmacophore-Based Methods. J. Chem. Inf. Comput. Sci. 41(2): 394-401 (2001) - [j13]Ling Xue, Florence L. Stahura, Jeffrey W. Godden, Jürgen Bajorath:
Fingerprint Scaling Increases the Probability of Identifying Molecules with Similar Activity in Virtual Screening Calculations. J. Chem. Inf. Comput. Sci. 41(3): 746-753 (2001) - [j12]Jeffrey W. Godden, Jürgen Bajorath:
Differential Shannon Entropy as a Sensitive Measure of Differences in Database Variability of Molecular Descriptors. J. Chem. Inf. Comput. Sci. 41(4): 1060-1066 (2001) - 2000
- [j11]Jeffrey W. Godden, Ling Xue, Jürgen Bajorath:
Combinatorial Preferences Affect Molecular Similarity/Diversity Calculations Using Binary Fingerprints and Tanimoto Coefficients. J. Chem. Inf. Comput. Sci. 40(1): 163-166 (2000) - [j10]Jeffrey W. Godden, Florence L. Stahura, Jürgen Bajorath:
Variability of Molecular Descriptors in Compound Databases Revealed by Shannon Entropy Calculations. J. Chem. Inf. Comput. Sci. 40(3): 796-800 (2000) - [j9]Ling Xue, Jürgen Bajorath:
Molecular Descriptors for Effective Classification of Biologically Active Compounds Based on Principal Component Analysis Identified by a Genetic Algorithm. J. Chem. Inf. Comput. Sci. 40(3): 801-809 (2000) - [j8]Ling Xue, Jeffrey W. Godden, Jürgen Bajorath:
Evaluation of Descriptors and Mini-Fingerprints for the Identification of Molecules with Similar Activity. J. Chem. Inf. Comput. Sci. 40(5): 1227-1234 (2000) - [j7]Florence L. Stahura, Jeffrey W. Godden, Ling Xue, Jürgen Bajorath:
Distinguishing between Natural Products and Synthetic Molecules by Descriptor Shannon Entropy Analysis and Binary QSAR Calculations. J. Chem. Inf. Comput. Sci. 40(5): 1245-1252 (2000)
1990 – 1999
- 1999
- [j6]Jürgen Bajorath:
Analysis of Fas-ligand interactions using a molecular model of the receptor-ligand interface. J. Comput. Aided Mol. Des. 13(4): 409-418 (1999) - [j5]Jeffrey W. Godden, Florence L. Stahura, Jürgen Bajorath:
Statistical analysis of computational docking of large compound data bases to distinct protein binding sites. J. Comput. Chem. 20(15): 1634-1643 (1999) - [j4]Hua Gao, Christopher I. Williams, Paul Labute, Jürgen Bajorath:
Binary Quantitative Structure-Activity Relationship (QSAR) Analysis of Estrogen Receptor Ligands. J. Chem. Inf. Comput. Sci. 39(1): 164-168 (1999) - [j3]Ling Xue, Jeffrey W. Godden, Hua Gao, Jürgen Bajorath:
Identification of a Preferred Set of Molecular Descriptors for Compound Classification Based on Principal Component Analysis. J. Chem. Inf. Comput. Sci. 39(4): 699-704 (1999) - [j2]Ling Xue, Jeffrey W. Godden, Jürgen Bajorath:
Database Searching for Compounds with Similar Biological Activity Using Short Binary Bit String Representations of Molecules. J. Chem. Inf. Comput. Sci. 39(5): 881-886 (1999) - [c1]Jürgen Bajorath, Teri E. Klein, Terry P. Lybrand, Jiri Novotny:
Computer-Aided Drug Design - Session Introduction. Pacific Symposium on Biocomputing 1999: 413-414 - 1997
- [j1]Jürgen Bajorath, Alejandro Aruffo:
Prediction of the three-dimensional structure of the human Fas receptor by comparative molecular modeling. J. Comput. Aided Mol. Des. 11(1): 3-8 (1997)
Coauthor Index
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