QSAR Modeling: Where have you been? Where are you going to?

Cited by (1,001)

Items 701–800 of 1,001

1. QSAR analysis on a large and diverse set of potent phosphoinositide 3-kinase gamma (PI3Kγ) inhibitors using MLR and ANN methods
   Fereydoun Sadeghi, Abbas Afkhami, Tayyebeh Madrakian, Raouf Ghavami · 2022 · Scientific Reports
2. Analysis of the benefits of imputation models over traditional QSAR models for toxicity prediction
   Moritz Walter, Luke N. Allen, Antonio de la Vega de León, Samuel J. Webb, Valerie J. Gillet · 2022 · Journal of Cheminformatics
3. Extending the limitations in the prediction of PAMPA permeability with machine learning algorithms
   Anita Rácz, Anna Vincze, Balázs Volk, György Tibor Balogh · 2023 · European Journal of Pharmaceutical Sciences
4. Mechanistic Task Groupings Enhance Multitask Deep Learning of Strain-Specific Ames Mutagenicity
   Raymond Lui, Davy Guan, Slade T. Matthews · 2023 · Chemical Research in Toxicology
5. Machine Learning-Based Prediction of Drug-Induced Hepatotoxicity: An OvA-QSTR Approach
   Feyza Kelleci̇ Çeli̇k, Gül Karaduman · 2023 · Journal of Chemical Information and Modeling
6. Artificial Intelligence and Machine Learning Methods to Evaluate Cardiotoxicity following the Adverse Outcome Pathway Frameworks
   Edoardo Luca Viganò, Davide Ballabio, Alessandra Roncaglioni · 2024 · Toxics
7. Development and Evaluation of Conformal Prediction Methods for Quantitative Structure–Activity Relationship
   Yuting Xu, Andy I. Liaw, Robert P. Sheridan, Vladimir Svetnik · 2024 · ACS Omega
8. In silicotools used for compound selection during target-based drug discovery and development
   Gary W. Caldwell · 2015 · Expert Opinion on Drug Discovery
9. Prediction of CO 2 loading of amines in carbon capture process using membrane contactors: A molecular modeling
   Bijan Rezaei, Siavash Riahi · 2016 · Journal of Natural Gas Science and Engineering
10. Using Molecular Initiating Events To Generate 2D Structure–Activity Relationships for Toxicity Screening
    Timothy E. H. Allen, Sonia Liggi, Jonathan M. Goodman, Steve Gutsell, Paul J Russell · 2016 · Chemical Research in Toxicology
11. Chemical reaction vector embeddings: towards predicting drug metabolism in the human gut microbiome
    Emily K. Mallory, Ambika Acharya, Stefano Rensi, Peter James Turnbaugh, Roselie A. Bright, Russ Biagio Altman · 2017 · Pacific Symposium on Biocomputing (PSB)
12. Quantitative Structure–Activity Relationship Modeling and Docking of Monoterpenes with Insecticidal Activity Against Reticulitermes chinensis Snyder and Drosophila melanogaster
    Gabriela Cristina Soares Rodrigues, Mayara dos Santos Maia, Eugene N. Muratov, Luciana Scotti, Marcus Tullius Scotti · 2020 · Journal of Agricultural and Food Chemistry
13. Predictive modeling of aryl hydrocarbon receptor (AhR) agonism
    Elizabeth Goya‐Jorge, Rosa María Giner, Maité Sylla‐Iyarreta Veitía, Rafael Gozalbes, Stephen J. Barigye · 2020 · Chemosphere
14. InterPred: a webtool to predict chemical autofluorescence and luminescence interference
    Alexandre Borrel, Kamel Mansouri, Sue Nolte, Trey O Saddler, Mike Conway, Charles Schmitt, Nicole Kleinstreuer · 2020 · Nucleic Acids Research
15. In Silico Prediction of Intestinal Permeability by Hierarchical Support Vector Regression
    Ming-Han Lee, Giang Huong Ta, Ching‐Feng Weng, Max K. Leong · 2020 · International Journal of Molecular Sciences
16. Data Science in Chemical Engineering: Applications to Molecular Science
    Chowdhury M. Ashraf, Nisarg Joshi, David A. C. Beck, Jim Pfaendtner · 2021 · Annual Review of Chemical and Biomolecular Engineering
17. Development of blood brain barrier permeation prediction models for organic and inorganic biocidal active substances
    Hyun Kil Shin, Sangwoo Lee, Ha‐Na Oh, Donggon Yoo, Seungmin Park, Woo‐Keun Kim, Myung-Gyun Kang · 2021 · Chemosphere
18. Identification of Kaurane-Type Diterpenes as Inhibitors of Leishmania Pteridine Reductase I
    Chonny Herrera‐Acevedo, Areli Flores‐Gaspar, Luciana Scotti, Francisco Jaime Bezerra Mendonça, Marcus Tullius Scotti, Ericsson David Coy-Barrera · 2021 · Molecules
19. Computer Aided Drug Design Methodologies with Natural Products in the Drug Research Against Alzheimer’s Disease
    Natália Ferreira de Sousa, Luciana Scotti, Érika Paiva de Moura, Mayara dos Santos Maia, Gabriela Cristina Soares Rodrigues, Herbert Igor Rodrigues de Medeiros, Simone Mendes Lopes, Marcus Tullius Scotti · 2021 · Current Neuropharmacology
20. Toward the Rational Design of Sustainable Hair Dyes Using Cheminformatics Approaches: Step 1. Database Development and Analysis
    Tova N. Williams, Mélaine A. Kuenemann, George A. Van Den Driessche, Antony John Williams, Denis Fourches, Harold Stanley Freeman · 2017 · ACS Sustainable Chemistry & Engineering
21. Development of Prediction Models for Drug-Induced Cholestasis, Cirrhosis, Hepatitis, and Steatosis Based on Drug and Drug Metabolite Structures
    Hyun Kil Shin, Myung-Gyun Kang, Daeui Park, Tamina Park, Seokjoo Yoon · 2020 · Frontiers in Pharmacology
22. 4-Fluoro-3′,4′,5′-trimethoxychalcone as a new anti-invasive agent. From discovery to initial validation in an in vivo metastasis model
    Bart I. Roman, Tine De Ryck, Atanas Patronov, Svetoslav H. Slavov, Barbara W.A. Vanhoecke, ALAN ROY KATRITZKY, Marc Bracke, Christian V. Stevens · 2015 · European Journal of Medicinal Chemistry
23. Data-driven toxicity prediction in drug discovery: Current status and future directions
    Ningning Wang, Xinliang David Li, Jing Xiao, Shao Liu, Dongsheng Cao · 2024 · Drug Discovery Today
24. Combinatorial Effect of Ligand and Ligand-Binding Site Hydrophobicities on Binding Affinity
    Dinesh Kumar Sriramulu, Sun‐Gu Lee · 2020 · Journal of Chemical Information and Modeling
25. Navigating bioactivity space in anti-tubercular drug discovery through the deployment of advanced machine learning models and cheminformatics tools: a molecular modeling based retrospective study
    Ratul Bhowmik, Ravi Kant, Ajay Manaithiya, Daman Saluja, Bharti Vyas, Ranajit Nath, Kamal A. Qureshi, Seppo Parkkila, Ashok Aspatwar · 2023 · Frontiers in Pharmacology
26. Similarity-based pairing improves efficiency of siamese neural networks for regression tasks and uncertainty quantification
    Yumeng Zhang, Janosch Menke, Jiazhen He, Eva Nittinger, Christian Tyrchan, Oliver Koch, Hongtao Zhao · 2023 · Journal of Cheminformatics
27. Data-driven discovery of innate immunomodulators via machine learning-guided high throughput screening
    Yifeng Tang, Jeremiah Y. Kim, Carman KM IP, Azadeh Bahmani, Qing Chen, Matthew Glenn Rosenberger, Aaron Palmer Esser-Kahn, Andrew L. Ferguson · 2023 · Chemical Science
28. Are we fitting data or noise? Analysing the predictive power of commonly used datasets in drug-, materials-, and molecular-discovery
    Daniel Crusius, Flaviu S. Cipcigan, Philip Charles Biggin · 2024 · Faraday Discussions
29. Computational Methodologies in Synthesis, Preparation and Application of Antimicrobial Polymers, Biomolecules, and Nanocomposites
    Iva Rezić, Maja Somogyi Škoc · 2024 · Polymers
30. Bitter peptide prediction using graph neural networks
    Prashant Srivastava, Alexandra Steuer, Francesco Ferri, Alessandro Nicoli, Kristian Schultz, Saptarshi Bej, Antonella Di Pizio, Olaf Wolkenhauer · 2024 · Journal of Cheminformatics
31. The utilisation of structural descriptors to predict metabolic constants of xenobiotics in mammals
    Alessandra Pirovano, Stefan Brandmaier, Mark A. J. Huijbregts, Ad M.J. Ragas, Karin Veltman, A. Jan Hendriks · 2014 · Environmental Toxicology and Pharmacology
32. Comprehensive QSRR modeling as a starting point in characterization and further development of anticancer drugs based on 17α-picolyl and 17(E)-picolinylidene androstane structures
    Strahinja Z. Kovačević, Sanja O. Podunavac-Kuzmanović, Lidija R. Jevrić, Pavle T. Jovanov, Evgenija A. Djurendić, Jovana J. Ajduković · 2016 · European Journal of Pharmaceutical Sciences
33. Aqueous Drug Solubility: What Do We Measure, Calculate and QSPR Predict?
    Oleg A. Raevsky, Veniamin Y. Grigorev, Daniel E. Polianczyk, Olga E. Raevskaja, John C. Dearden · 2019 · Mini-Reviews in Medicinal Chemistry
34. Exploring the chemical space for freeze-drying excipients
    Helena Meng-Lund, Tobias Palle Holm, Antti Poso, Lene Jørgensen, Jukka Rantanen, Holger Grohganz · 2019 · International Journal of Pharmaceutics
35. Towards a reliable prediction of the aquatic toxicity of dyes
    Gisela de Aragão Umbuzeiro, Anjaína Fernandes de Albuquerque, Francine Inforçato Vacchi, Małgorzata Szymczyk, Xinyi Sui, Reza Aalizadeh, Peter C. von der Ohe, Νikolaos S. Τhomaidis, Nelson R. Vinueza, Harold Stanley Freeman · 2019 · Environmental Sciences Europe
36. A comparison of molecular representations for lipophilicity quantitative structure–property relationships with results from the SAMPL6 logP Prediction Challenge
    Raymond Lui, Davy Guan, Slade T. Matthews · 2020 · Journal of Computer-Aided Molecular Design
37. New Pharmacological Findings Linked to Biphenyl DHPMs, Kinesin Eg5 Ligands: Anticancer and Antioxidant Effects
    Itamar Luís Gonçalves, Liliana Rockenbach, Gabriela Göethel, Elisa Saüer, Luciano Porto Kagami, Gustavo Machado das Neves, Thaís Munhoz, Fabrício Figueiró, Solange Cristina García, Ana Maria Oliveira Battastini et al. · 2020 · Future Medicinal Chemistry
38. Benchmarking 2D/3D/MD-QSAR Models for Imatinib Derivatives: How Far Can We Predict?
    Phyo Phyo Kyaw Zin, Alexandre Borrel, Denis Fourches · 2020 · Journal of Chemical Information and Modeling
39. Development of classification models for predicting inhibition of mitochondrial fusion and fission using machine learning methods
    Weihao Tang, Jingwen Chen, Huixiao Hong · 2020 · Chemosphere
40. Parsing Sage and Rosemary in Time: The Machine Learning Race to Crack Olfactory Perception
    Richard C. Gerkin · 2021 · Chemical Senses
41. Web-Based Quantitative Structure–Activity Relationship Resources Facilitate Effective Drug Discovery
    Yuliang Wang, Jingyi Li, Xing-Xing Shi, Zheng Wang, Ge‐Fei Hao, Guang‐Fu Yang · 2021 · Topics in Current Chemistry
42. Unsupervised Representation Learning for Proteochemometric Modeling
    Paul T. Kim, Robin Winter, Djork-Arné Clevert · 2021 · International Journal of Molecular Sciences
43. Quantitative structure–activity relationship(QSAR) models for color and COD removal for some dyes subjected to electrochemical oxidation
    Katha S. Hirpara, Upendra D. Patel · 2022 · Environmental Technology
44. Transforming the evaluation of agrochemicals
    Douglas C. Wolf, Yadvinder Bhuller, Rhian B. Cope, Marco Corvaro, Richard A. Currie, John E. Doe, Adriana M. Doi, Gina M. Hilton, Jyotigna M. Mehta, David A. Saltmiras et al. · 2022 · Pest Management Science
45. Topological pattern for the search of new active drugs against methicillin resistant Staphylococcus aureus
    José Ignacio Bueso-Bordils, María Teresa Pérez‐Gracia, Beatriz Suay‐García, María J. Duart, Rafael V. Martín-Algarra, Luis Lahuerta Zamora, Gerardo M. Antón-Fos, P. Aleman · 2017 · European Journal of Medicinal Chemistry
46. Renewable Hydride Donors for the Catalytic Reduction of CO2: A Thermodynamic and Kinetic Study
    Abdulaziz W. Alherz, Chern‐Hooi Lim, Yu-Ching Kuo, Philip Lehman, Jennifer N. Cha, James T. Hynes, Charles B. Musgrave · 2018 · The Journal of Physical Chemistry B
47. An in vitro and machine learning framework for quantifying serum albumin binding of per- and polyfluoroalkyl substances
    Hannah M. Starnes, Adrian J. Green, David M. Reif, Scott M. Belcher · 2024 · Toxicological Sciences
48. Computational Landscape in Drug Discovery: From AI/ML Models to Translational Application
    Deepak Sharma, Madhu Anabala, V. Vanitha Jain, Mukul Shyam, Sabina Evan Prince, Rajiniraja Muniyan · 2025 · Scientifica
49. On the use of chemical bonding descriptors in machine learning
    Michele Tomasini, Lucia Caporaso, Martí Gimferrer, Albert Poater · 2025 · Coordination Chemistry Reviews
50. Monte Carlo based QSGFEAR: prediction of Gibb's free energy of activation at different temperatures using SMILES based descriptors
    Rahul Prasad Singh, Prof Parvin Kumar, Meena Devi, Sohan Lal, Ashwani Kumar, Jayant Sindhu, Alla P. Toropova, Andrey Andreevich Toropov, Devender Singh · 2022 · New Journal of Chemistry
51. Supramolecular assembly in designing co-crystals of fumaric acid and pyrimidine/picolinate derivatives
    Sevgi Kansız, Mohammad Azam, Necmi Dege, Nihal Ermiş, Saud Ibrahim Al-Resayes, Mahboob Alam · 2022 · Green Chemistry Letters and Reviews
52. Prediction of KRASG12C inhibitors using conjoint fingerprint and machine learning-based QSAR models
    Tarapong Srisongkram, Patcharapa Khamtang, Natthida Weerapreeyakul · 2023 · Journal of Molecular Graphics and Modelling
53. “Freedom of design” in chemical compound space: towards rational in silico design of molecules with targeted quantum-mechanical properties
    Leonardo Medrano Sandonas, Johannes Hoja, Brian G. Ernst, Álvaro Vázquez‐Mayagoitia, Robert A. DiStasio, Alexandre Tkatchenko · 2023 · Chemical Science
54. Alternative methods go green! Green toxicology as a sustainable approach for assessing chemical safety and designing safer chemicals
    Alexandra Maertens, Thomas H. Luechtefeld, Jean Knight, Thomas Härtung · 2024 · ALTEX
55. Virtual screening: hope, hype, and the fine line in between
    Hossam Nada, Nicholas A. Meanwell, Moustafa Tarek Gabr · 2025 · Expert Opinion on Drug Discovery
56. Cheminformatics Modeling of Adverse Drug Responses by Clinically Relevant Mutants of Human Androgen Receptor
    Naman Paul, Lavinia A. Carabet, Nada Lallous, Takeshi Yamazaki, Martin Edwin Gleave, Paul S. Rennie, Artem R Cherkasov · 2016 · Journal of Chemical Information and Modeling
57. QSAR analysis for 6-arylpyrazine-2-carboxamides as Trypanosoma brucei inhibitors
    Vijay Hariram Masand, Nahed N. E. El-Sayed, Devidas T. Mahajan, Vesna Rastija · 2017 · SAR and QSAR in environmental research
58. Classical and 3D QSAR studies of larvicidal monoterpenes against Aedes aegypti: new molecular insights for the rational design of more active compounds
    Iêda Maria dos Santos, João Pedro Agra Gomes, Thiego Gustavo Cavalcante de Carvalho, Gabriela Lemos de Azevedo Maia, Edilson Beserra de Alencar Filho · 2018 · Structural Chemistry
59. Regression Modelability Index: A New Index for Prediction of the Modelability of Data Sets in the Development of QSAR Regression Models
    Irene Luque Ruiz, Miguel Ángel Gómez‐Nieto · 2018 · Journal of Chemical Information and Modeling
60. In silico model for mutagenicity (Ames test), taking into account metabolism
    Matteo Vian, Giuseppa Raitano, Alessandra Roncaglioni, Emilio Benfenati · 2018 · Mutagenesis
61. Evaluation of multi-target deep neural network models for compound potency prediction under increasingly challenging test conditions
    Raquel Rodríguez-Pérez, Jürgen Bajorath · 2021 · Journal of Computer-Aided Molecular Design
62. QSAR and Pharmacophore Modeling of Nitrogen Heterocycles as Potent Human N-Myristoyltransferase (Hs-NMT) Inhibitors
    Magdi E. A. Zaki, Sami A. Al‐Hussain, Vijay Hariram Masand, Siddhartha Akasapu, Israa Lewaa · 2021 · Molecules
63. Machine learning analysis of microwave dielectric properties for seven structure types: The role of the processing and composition
    Natalia V. Kireeva, Vitaly P. Solov’ev · 2021 · Journal of Physics and Chemistry of Solids
64. Prediction of degradability of micropollutants by sonolysis in water with QSPR - a case study on phenol derivates
    Judith Glienke, Willy Schillberg, Michael Stelter, Patrick Braeutigam · 2021 · Ultrasonics Sonochemistry
65. Improving VAE based molecular representations for compound property prediction
    Ani Tevosyan, Lusine Khondkaryan, Hrant Khachatrian, Gohar Tadevosyan, Lilit Apresyan, Nelly Babayan, Helga Stopper, Zaven E. Navoyan · 2022 · Journal of Cheminformatics
66. In silico QSAR modeling to predict the safe use of antibiotics during pregnancy
    Feyza Kelleci̇ Çeli̇k, Gül Karaduman · 2022 · Drug and Chemical Toxicology
67. Industrial applications of in silico ADMET
    Bernd Beck, Tim Geppert · 2014 · Journal of Molecular Modeling
68. Animal Ethics in Animal Research
    Helena Röcklinsberg, Mickey Gjerris, I. Anna S. Olsson · 2017 · Cambridge University Press eBooks
69. Nanobiotechnology: 1D nanomaterial building blocks for cellular interfaces and hybrid tissues
    Haitao Liu, Bilal Haider, Holden R. Fried, Jie Ju, Olurotimi A. Bolonduro, Vineeth Raghuram, Brian P. Timko · 2018 · Nano Research
70. Acneiform eruptions induced by epidermal growth factor receptor inhibitors: treatment with oral isotretinoin.
    Celia Requena, B. Llombart, Onofre Sanmartín · 2012 · PubMed
71. Bioinformatics and Cheminformatics Tools in Early Drug Discovery
    Palak K. Parikh, Jignasa Savjani, Anuradha Ketan Gajjar, Mahesh T. Chhabria · 2023 · Wiley eBooks
72. Machine learning and deep learning in clinical practice: Advancing neurodegenerative disease diagnosis with multimodal markers
    Omid Zarei, Maryam Talebi moghaddam, Sadegh Moradi Vastegani · 2025 · Brain Research Bulletin
73. First Novel Workflow for Semiquantification of Emerging Contaminants in Environmental Samples Analyzed by Gas Chromatography–Atmospheric Pressure Chemical Ionization–Quadrupole Time of Flight–Mass Spectrometry
    Reza Aalizadeh, Varvara Nikolopoulou, ‪Nikiforos Alygizakis, Νikolaos S. Τhomaidis · 2022 · Analytical Chemistry
74. Toxicity prediction of 1,2,4-triazoles compounds by QSTR and interspecies QSTTR models
    Zhiyong Liu, Kai Dang, Jun-Hong Gao, Peng Fan, Cunzhi Li, Hong Wang, Huan Li, Xiaoni Deng, Yongchao Gao, Airong Qian · 2022 · Ecotoxicology and Environmental Safety
75. Applicability Domain Characterization for Machine Learning QSAR Models
    Zhongyu Wang, Jingwen Chen · 2023 · Computational methods in engineering & the sciences
76. Characterization of oxidative damage induced by nanoparticles via mechanism-driven machine learning approaches
    Xiaoqing Wang, Fei Li, Yuefa Teng, Chenglong Ji, Huifeng Wu · 2023 · The Science of The Total Environment
77. Physicochemical Significance of Topological Indices: Importance in Drug Discovery Research
    Karanpreet Singh Bhatia, Ankit Kumar Gupta, Anil Kumar Saxena · 2023 · Current Topics in Medicinal Chemistry
78. Stacked ensemble learning on HaCaT cytotoxicity for skin irritation prediction: A case study on dipterocarpol
    Tarapong Srisongkram, Nur Fadhilah Syahid, Dheerapat Tookkane, Natthida Weerapreeyakul, Ploenthip Puthongking · 2023 · Food and Chemical Toxicology
79. Identification of novel NLRP3 inhibitors: a comprehensive approach using 2D-QSAR, molecular docking, molecular dynamics simulation and drug-likeness evaluation
    Mouad Mouhsin, Oussama Abchır, Faiçal Sbai El Otmani, Ayoub Ait Oumghar, Mustapha Oubenali, Samir Chtita, Mohamed Mbarki, Ahmed Gamouh · 2023 · Chemical Papers
80. Development of a novel representation of drug 3D structures and enhancement of the TSR-based method for probing drug and target interactions
    Tarikul I. Milon, Yuhong Wang, Ryan L. Fontenot, Poorya Khajouie, Francois J. Villinger, Vijay V. Raghavan, Wu Xu · 2024 · Computational Biology and Chemistry
81. Endocrine-Disrupting Effects of Salicylate Preservatives on Neurosteroidogenesis: Targeting 5α-Reductase Type 1
    Wanyu Li, Rong Cui, Shufang Qi, Ke Zheng, Jin Yang, Ren‐Shan Ge, Yiyan Wang · 2024 · Journal of Agricultural and Food Chemistry
82. Machine learning & deep learning tools in pharmaceutical sciences: A comprehensive review
    Saleem Javid, Abdul Rahmanulla, Mohammed Gulzar Ahmed, Rokeya Sultana, B. R. Prashantha Kumar · 2025 · Intelligent Pharmacy
83. Azolium analogues as CDK4 inhibitors: Pharmacophore modeling, 3D QSAR study and new lead drug discovery
    Rohini Rondla, Lavanya Souda Padma Rao, Vishwanath Ramatenki, Rajender Vadija, Thirupathi Mukkera, Sarita Rajender Potlapally, Uma Vuruputuri · 2017 · Journal of Molecular Structure
84. Using Delaunay triangulation and Voronoi tessellation to predict the toxicities of binary mixtures containing hormetic compound
    Rui Qu, Shu‐Shen Liu, Qiao-Feng Zheng, Tong Li · 2017 · Scientific Reports
85. Comprehensive 3D-QSAR Model Predicts Binding Affinity of Structurally Diverse Sigma 1 Receptor Ligands
    Youyi Peng, Hiep Dong, William Jeffrey Welsh · 2018 · Journal of Chemical Information and Modeling
86. Searching for the Optimized Luminescent Lanthanide Phosphor Using Heuristic Algorithms
    Ruichan Lv, Liyang Xiao, Yanxing Wang, Fan Yang, Jie Tian, Jun Lin · 2019 · Inorganic Chemistry
87. Investigation of Factors Affecting the Performance of in silico Volume Distribution QSAR Models for Human, Rat, Mouse, Dog & Monkey
    Saw Simeon, Dino Montanari, M. Paul Gleeson · 2019 · Molecular Informatics
88. An Analysis of Proteochemometric and Conformal Prediction Machine Learning Protein-Ligand Binding Affinity Models
    Conor D. Parks, Zied Gaieb, Rommie E. Amaro · 2020 · Frontiers in Molecular Biosciences
89. Evaluating High-Variance Leaves as Uncertainty Measure for Random Forest Regression
    Thomas‐Martin Dutschmann, Knut Baumann · 2021 · Molecules
90. Artificial Intelligence in Compound Design
    Christoph Grebner, Hans Matter, Gerhard Heßler · 2021 · Methods in molecular biology
91. Discovery of Novel Epidermal Growth Factor Receptor (EGFR) Inhibitors Using Computational Approaches
    Donghui Huo, Shiyu Wang, Yue Kong, Zijian Qin, Aixia Yan · 2021 · Journal of Chemical Information and Modeling
92. Machine Learning Prediction of Structure‐Performance Relationship in Organic Synthesis
    Li‐Cheng Yang, Lu‐Jing Zhu, Shuo‐Qing Zhang, Xin Hong · 2022 · Chinese Journal of Chemistry
93. Data driven toxicity assessment of organic chemicals against Gammarus species using QSAR approach
    Yang Lü, Tian Ruya, Zhoujing Li, Xiaomin Ma, Hongyan Wang, Wei Sun · 2023 · Chemosphere
94. Evaluating Scalable Supervised Learning for Synthesize-on-Demand Chemical Libraries
    Moayad Alnammi, Shengchao Liu, Spencer S. Ericksen, Gene E. Ananiev, Andrew F. Voter, Song Guo, James L. Keck, F. Michael Hoffmann, Scott A. Wildman, Anthony Gitter · 2023 · Journal of Chemical Information and Modeling
95. Materials Informatics: Statistical Modeling in Material Science
    Abraham Yosipof, Klimentiy Shimanovich, Hanoch Senderowitz · 2016 · Molecular Informatics
96. In Silico and in Vitro Assessment of OATP1B1 Inhibition in Drug Discovery
    Matthew L. Danielson, Geri A. Sawada, Thomas J. Raub, Prashant V. Desai · 2018 · Molecular Pharmaceutics
97. Novel 1,4-dihydropyridine induces apoptosis in human cancer cells through overexpression of Sirtuin1
    Debashri Manna, Rajabrata Bhuyan, Forid Saikh, Somnath Ghosh, Jayasri Basak, Rita Ghosh · 2018 · APOPTOSIS
98. Computer-Aided Discovery of New Solubility-Enhancing Drug Delivery System
    Mikołaj Mizera, Eugene N. Muratov, Vinícius M. Alves, Alexander Tropsha, Judyta Cielecka‐Piontek · 2020 · Biomolecules
99. In Silico Frontiers Shaping the Next Generation of Transformation Product Prediction and Toxicological Assessment
    Paul Löffler, Emma Schymanski, Henning Henschel, Foon Yin Lai · 2025 · Environmental Science & Technology
100. Conceptual density functional theory in drug discovery: an overview
     Hemangini Rohit, Hiteshi Tandon · 2025 · Journal of Molecular Modeling