Comparing Multiple Machine Learning Algorithms and Metrics for Estrogen Receptor Binding Prediction

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Items 101–152 of 152

1. Mycobacterium abscessus drug discovery using machine learning
   Alan A. Schmalstig, Kimberley M. Zorn, Sebastian Murcia, Andrew Robinson, Svetlana Savina, Elena Kazakova, Vadim Makarov, Miriam Braunstein, Sean Ekins · 2022 · Tuberculosis
2. Machine learning methods for endocrine disrupting potential identification based on single-cell data
   Zahir Aghayev, Adam T. Szafran, Anh Tuan Tran, Hari S. Ganesh, Fabio Stossi, Lan Feng Zhou, Michael A. Mancini, Efstratios N. Pistikopoulos, Burcu Beykal · 2023 · Chemical Engineering Science
3. Automatic Quantitative Structure–Activity Relationship Modeling to Fill Data Gaps in High-Throughput Screening
   Heather L. Ciallella, Elena Chung, Daniel P. Russo, Hao Zhu · 2022 · Methods in molecular biology
4. Bridging the Gap Between Nanotoxicological Data and the Critical Structure–Activity Relationships
   Xiliang Yan, Tongtao Yue, Hao Zhu, Bing Yan · 2022 · Springer eBooks
5. AI-Assisted Forecasting of a Mitigated Multiple Steam Generator Tube Rupture Scenario in a Typical Nuclear Power Plant
   Sonia Justyna Spisak, Aya Diab · 2025 · Energies
6. Machine Learning and Large Language Models for Modeling Complex Toxicity Pathways and Predicting Steroidogenesis
   Thomas R. Lane, Patricia A. Vignaux, Joshua S. Harris, Scott H. Snyder, Fabio Urbina, Sean Ekins · 2025 · Environmental Science & Technology
7. Joint Decision-Making Model Based on Consensus Modeling Technology for the Prediction of Drug-Induced Liver Injury
   Yukun Wang, Xuebo Chen · 2021 · Journal of Chemistry
8. Predicting firm creation in rural Texas: A multi-model machine learning approach to a complex policy problem
   Mark C. Hand, Vivek Shastry, Varun Rai · 2023 · PLoS ONE
9. Advances in In Silico Toxicity Assessment of Nanomaterials and Emerging Contaminants
   Xuehua Li, Yang Huang, Jingwen Chen · 2022 · Springer eBooks
10. Feasibility and application of machine learning enabled fast screening of poly-beta-amino-esters for cartilage therapies
    Stefano Perni, Polina Prokopovich · 2022 · Scientific Reports
11. Machine Learning Modeling for ABC Transporter Efflux and Inhibition: Data Curation, Model Development, and New Compound Interaction Predictions
    Nada J. Daood, Sean R. Carey, Elena Chung, Tong Wang, Anna Kreutz, Mounika Girireddy, Suman Chakravarti, Nicole Kleinstreuer, Jacqueline B. Tiley, Lauren M. Aleksunes et al. · 2025 · Molecular Pharmaceutics
12. Identification of New Modulators and Inhibitors of Palmitoyl-Protein Thioesterase 1 for CLN1 Batten Disease and Cancer
    Ana C. Puhl, Renuka Raman, Tammy M. Havener, Eni Minerali, Anthony James Hickey, Sean Ekins · 2024 · ACS Omega
13. Machine learning approaches for image classification in developmental biology and clinical embryology
    Camilla Mapstone, Berenika Płusa · 2025 · Development
14. Classification of some chemical drugs by genetic algorithm and deep neural network hybrid method
    Mustafa Karakaplan, Fatih Mehmet Avcu · 2021 · Concurrency and Computation Practice and Experience
15. AZ VERİ SETLİ ÇALIŞMALARINDA DERİN ÖĞRENME VE DİĞER SINIFLANDIRMA ALGORİTMALARININ KARŞILAŞTIRILMASI: AGONİST VE ANTAGONİST LİGAND ÖRNEĞİ
    Fatih Mehmet Avcu · 2022 · İnönü Üniversitesi Sağlık Hizmetleri Meslek Yüksek Okulu Dergisi
16. Visual analysis of drug research and development based on artificial intelligence
    Wei Wei, Chao Song, Changxing Qi, Xin Zhang, Xiaoyi Zhang, Run Pu, Yi Ao · 2024 · Journal of Holistic Integrative Pharmacy
17. Computational Approaches for Predicting Drug Interactions with Human Organic Anion Transporter 4 (OAT4)
    Lucy Martinez-Guerrero, Patricia A. Vignaux, Joshua S. Harris, Thomas R. Lane, Fabio Urbina, Stephen H. Wright, Sean Ekins, Nathan J. Cherrington · 2025 · Molecular Pharmaceutics
18. Shortcuts to schistosomiasis drug discovery: The state-of-the-art
    José Teófilo Moreira‐Filho, Rafael Ferreira Dantas, Mário Roberto Senger, Arthur C. Silva, Dulcinéa Maria Barbosa Campos, Eugene N. Muratov, Floriano Paes Silva, Carolina Horta Andrade, Bruno J. Neves · 2019 · Annual reports in medicinal chemistry
19. Staying Ahead of the Game: How SARS-CoV-2 has Accelerated the Application of Machine Learning in Pandemic Management
    Alexander H. Williams, Chang‐Guo Zhan · 2023 · BioDrugs
20. A computationally supported designer benzodiazepine strategy for public toxicology laboratories
    Heather L. Ciallella, Danai T Taruvinga, Kimberly Yacoub, Szabolcs Sofalvi, Samantha M Delor, Claire K. Naso-Kaspar, Christie L Mitchell-Mata, Shelby Travaglianti, Eric S. Lavins, Luigino G. Apollonio · 2024 · Journal of Analytical Toxicology
21. Repurposing lapatinib as a triple antagonist of chemokine receptors 3, 4, and 5
    Thomas R. Lane, Ana C. Puhl, Patricia A. Vignaux, Keith R. Pennypacker, Sean Ekins · 2024 · Molecular Pharmacology
22. The Role of Simulation Science in Public Health at the Agency for Toxic Substances and Disease Registry: An Overview and Analysis of the Last Decade
    Siddhi Desai, Jewell Wilson, Chao Ji, Jason B. Sautner, Andrew J. Prussia, Eugene Demchuk, Moiz M. Mumtaz, Patricia Ruiz · 2024 · Toxics
23. Machine Learning Based Cybersecurity Defense at the Age of Industry 4.0
    Sourabh Kumar Vishavnath, Adnan Anwar, Mohiuddin Ahmed · 2021 · Studies in computational intelligence
24. On the ability of machine learning methods to discover novel scaffolds
    Rishi Jagdev, Thomas Bruun Madsen, Paul W. Finn · 2022 · Journal of Molecular Modeling
25. Custom Tokenization Dictionary, CUSTODI: A General, Fast, and Reversible Data-Driven Representation and Regressor
    Shachar Fite, Omri Nitecki, Zeev Gross · 2021 · Journal of Chemical Information and Modeling
26. Identification of Pharmacophore Groups with Antimalarial Potential in Flavonoids by QSAR-Based Virtual Screening
    Adriana de Oliveira Fernandes, Valéria Vieira Moura Paixão, Yria Jaine Andrade Santos, Eduardo Borba Alves, Ricardo Pereira Rodrigues, Daniela Aparecida Chagas‐Paula, Aurélia Santos Faraoni, Rosana Casoti, Marcus Vinícius de Aragão Batista, Marcel Bermúdez et al. · 2025 · Drugs and Drug Candidates
27. Automated machine learning approach for developing a quantitative structure–activity relationship model for cardiac steroid inhibition of Na+/K+-ATPase
    Yohei Takada, Kazuhiro Kaneko · 2023 · Pharmacological Reports
28. Deep learning quantitative structure–activity relationship methods for chemical toxicity prediction and risk assessment
    Shuheng Huang, Mei Ying Hu · 2023 · Elsevier eBooks
29. Biological Evaluation of Lysionotin: a Novel Inhibitor of 5-Lipoxygenase for Anti-glioma
    Xin-xin Shao, Cong Chen, Jie Liu, Qingjun Li, Shan He, Xiang-Hua Qi, Xianjun Fu, Zhenguo Wang · 2024 · Chinese Journal of Integrative Medicine
30. Boosting Methods Comparison : XGBoost, Adaboost and Gradient Boosting for Business Partner Performance Prediction
    Elly Warni, Dea Wahsa Saputri, Alimuddin Alimuddin, Muhammad Rizal H, Yunifa Miftachul Arif, Irfan Tanzilur Rahman · 2024 · International Conference on Information Technology, Information Systems and Electrical Engineering (ICITISEE)
31. Prediction of progesterone receptor binding potency, agonism and antagonism using machine learning models
    Nemanja Milošević, Nataša Sukur, Svetlana Fa, Bojana Stanić, Nebojsa L. Andric · 2025 · Computational Toxicology
32. Machine Learning-Enabled Network Biology Analysis for Biomarker Discovery: Uncovering Molecular Interactions between Endocrine-Disrupting Chemicals and Hormone-Sensitive Cancers
    Suvitha Anbarasu, Anand Anbarasu · 2025 · Journal of Computational Biophysics and Chemistry
33. Classification of hydroxylated polychlorinated biphenyls as agonists and nonagonists of estrogen receptors using linear discriminant analysis and decision tree models
    Lukman Kehinde Akinola, Adamu Uzairu, Gideon Adamu Shallangwa, Stephen Eyije Abechi, Abdullahi B Umar · 2025 · Environmental Toxicology and Chemistry
34. Perspective on applicability of data-driven machine learning computational new approach methodologies for hazard identification in chemicals risk assessment
    Geven Piir, Sulev Sild, Olga Tcheremenskaia, Emma Di Consiglio, Jörgen Henriksson, Agnieszka Gajewicz, Enrico Mombelli, Alessandra Roncaglioni, Uko Maran · 2026 · Journal of Cheminformatics
35. Early prediction of estrogen levels for post-hysterectomy menopausal syndrome using machine learning models with an Ayurveda approach- An observational study
    Kashavva Hiremath, Dharthy Budihal, T. U. Aravinth, S. Chithra, R. Thirumalai Selvi · 2025 · Journal of Ayurveda and Holistic Medicine
36. AI – New Avenue for Drug Discovery and Optimization
    Rupesh Dudhe, Anshu Chaudhary Dudhe, Rupesh Dudhe, Suhas Narayan Sakarkar, Omji Porwal · 2021 · Clinical Oncology and Research
37. Automatic Kernel Selection of Support Vector Machine for Drug/Non-Drug Compounds Classification
    Lakshmi Mandal, Nanda Dulal Jana · 2021 · IEEE India Conference
38. Advances in Multiobjective Optimization for Drug Discovery and Development
    J. Dana Honeycutt, Kimberley M. Zorn, Alex M. Clark, Sean Ekins · 2021 · Wiley eBooks
39. Cancer Precision Drug Discovery Using Big Data and Artificial Intelligence Technologies
    Bichandarkoil Jayaram Pratima, N. Nalini · 2022 · Advances in computational intelligence and robotics book series
40. A Very Large-Scale Bioactivity Comparison of Deep Learning and Multiple Machine Learning Algorithms for Drug Discovery
    Thomas R. Lane, Daniel H. Foil, Eni Minerali, Fabio Urbina, Kimberley M. Zorn, Sean Ekins · 2020 · ChemRxiv
41. Aprendizado de máquina e big data na descoberta de novos medicamentos: um mapeamento sistemático
    Luiz Carlos Bertucci Barbosa, Gustavo Moreira Silva, Rosimere Miranda Fortini · 2023 · Brazilian Journal of Development
42. Cancer Precision Drug Discovery Using Big Data and Artificial Intelligence Technologies
    Bichandarkoil Jayaram Pratima, N. Nalini · 2023 · IGI Global eBooks
43. Assay Central User manual - made available for ER paper
    Ekins, Sean · 2018 · Figshare
44. estrogen receptor Bayesian Machine learning models
    Ekins, Sean · 2018 · Figshare
45. Antiviral properties of grape flavonoids on tropical viruses
    Annarita Panighel, Antonella Pasquato, Mirko De Rosso, Riccardo Flamini · 2025 · Studies in natural products chemistry
46. A graph neural network model integrating transfer learning and multimodal features for accurate and interpretable prediction of the bioaccumulation factor of chemical substances
    Mingjiang Xie, Yuanfan Zhao, Jing Zhang, Shuguang Zhu, Jin S. Zhang, Qian Cheng, Wenjing Mao · 2026 · SSRN Electronic Journal
47. Improving the inventive design process by using agile methods and machine learning algorithms
    Masih Hanifi · 2021 · theses.fr (ABES)
48. Pose Estimation for Analyzing Cricket Players Using CNN
    R. Sudharsanan, S. Sangeetha, R. Kokila Devi, B. Dwarakanath, Punniyakotti Varadharajan Gopirajan, S. Shreeyaa · 2026 · Advances in Science, Technology & Innovation/Advances in science, technology & innovation
49. MegaTrans—machine learning models for drug transporters corresponding to the FDA guidance
    Patricia A. Vignaux, Melanie Tojong, Alexander Kyu, Lucy Martinez-Guerrero, Joshua S. Harris, Thomas R. Lane, Stephen H. Wright, Nathan J. Cherrington, Sean Ekins · 2026 · Drug Metabolism and Disposition
50. Cyber Surge: Anticipating and Neutralizing Security Threats
    Vel Murugesh Kumar N, B. Jaison, Anish. T. P, Ravindhar N V, Punniyakotti Varadharajan Gopirajan · 2025 · International Conference on Emerging Engineering Technologies and Applications (IC-EETA)
51. A Comprehensive Evaluation of Machine Learning Pipelines for Toxic Endpoint Prediction
    Lisa-Marie Rolli, Loulwah Arnaout, Andrea Volkamer · 2026 · Research Square
52. Interpretable prediction of bioconcentration factors using a transfer learning-based multimodal graph framework
    Mingjiang Xie, Yuanfan Zhao, Jing Zhang, Jin Zhang, Wenjing Mao · 2026 · Journal of Water Process Engineering