1,865 results on '"A. Varnek"'
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52. Evolution of commercially available compounds for HTS
53. Multi-task generative topographic mapping in virtual screening.
54. Conjugated Quantitative Structure-Property Relationship Models: Application to Simultaneous Prediction of Tautomeric Equilibrium Constants and Acidity of Molecules.
55. CGRtools: Python Library for Molecule, Reaction, and Condensed Graph of Reaction Processing.
56. CovaDOTS: In Silico Chemistry-Driven Tool to Design Covalent Inhibitors Using a Linking Strategy.
57. De Novo Molecular Design by Combining Deep Autoencoder Recurrent Neural Networks with Generative Topographic Mapping.
58. Virtual Screening with Generative Topographic Maps: How Many Maps Are Required?
59. Predicting S. aureus antimicrobial resistance with interpretable genomic space maps.
60. Kinetic solubility: experimental and machine‐learning modeling perspectives
61. Integrating QSAR modelling and deep learning in drug discovery: the emergence of deep QSAR
62. Chemical complexity challenge: Is multi‐instance machine learning a solution?
63. Multi-Instance Learning Approach to the Modeling of Enantioselectivity of Conformationally Flexible Organic Catalysts
64. A community effort in SARS‐CoV‐2 drug discovery
65. In Vitro Evaluation of In Silico Screening Approaches in Search for Selective ACE2 Binding Chemical Probes
66. Generative Topographic Mapping Approach to Chemical Space Analysis
67. Assessment of tautomer distribution using the condensed reaction graph approach.
68. Rescoring of docking poses under Occam's Razor: are there simpler solutions?
69. Multi-task generative topographic mapping in virtual screening
70. Meta-GTM: Visualization and Analysis of the Chemical Library Space
71. GENERA: A Combined Genetic/Deep-Learning Algorithm for Multiobjective Target-Oriented De Novo Design
72. Conjugated Quantitative Structure‐Property Relationship Models: Prediction of Kinetic Characteristics Linked by the Arrhenius Equation
73. Kinetic solubility: Experimental and machine‐learning modeling perspectives.
74. Chemical complexity challenge: Is multi‐instance machine learning a solution?
75. Predictive cartography of metal binders using generative topographic mapping.
76. Structure-reactivity modeling using mixture-based representation of chemical reactions.
77. QSAR modeling and chemical space analysis of antimalarial compounds.
78. From bird's eye views to molecular communities: two-layered visualization of structure-activity relationships in large compound data sets.
79. Privileged Structural Motif Detection and Analysis Using Generative Topographic Maps.
80. Rescoring of docking poses under Occam’s Razor: are there simpler solutions?
81. Prediction of Aromatic Hydroxylation Sites for Human CYP1A2 Substrates Using Condensed Graph of Reactions
82. Assessment of tautomer distribution using the condensed reaction graph approach
83. SPIN CROSSOVER IN IRON(II) COMPLEXES WITH TRIS(PYRAZOL-1-YL)METHANE AND [Ag(CN)2]– AND [Au(CN)2]– ANIONS
84. MetaGTM: VISUALIZATION AND ANALYSIS OF THE CHEMICAL LIBRARY SPACE
85. A community effort to discover small molecule SARS-CoV-2 inhibitors
86. Predicting Highly Enantioselective Catalysts Using Tunable Fragment Descriptors
87. Challenges for Kinetics Predictions via Neural Network Potentials: A Wilkinson’s Catalyst Case
88. MetaGTM: VISUALIZATION AND ANALYSIS OF THE CHEMICAL LIBRARY SPACE
89. Construction of order-independent molecular fragments space with vector quantised graph autoencoder
90. A community effort to discover small molecule SARS-CoV-2 inhibitors
91. DMSO Solubility Assessment for Fragment-Based Screening
92. Automatized Assessment of Protective Group Reactivity: A Step Toward Big Reaction Data Analysis.
93. Kernel Target Alignment Parameter: A New Modelability Measure for Regression Tasks.
94. Structural and Physico-Chemical Interpretation (SPCI) of QSAR Models and Its Comparison with Matched Molecular Pair Analysis.
95. Chemical Space Mapping and Structure-Activity Analysis of the ChEMBL Antiviral Compound Set.
96. Prediction of Activity Cliffs Using Condensed Graphs of Reaction Representations, Descriptor Recombination, Support Vector Machine Classification, and Support Vector Regression.
97. Conjugated quantitative structure‐property relationship models: Prediction of kinetic characteristics linked by the Arrhenius equation.
98. Predicting S. aureus antimicrobial resistance with interpretable genomic space maps
99. The chemical library space and its application to DNA-Encoded Libraries
100. Predicting Highly Enantioselective Catalysts Using Tunable Fragment Descriptors**
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