Pravin Ambure

Target (United States) — United States

Computer Science · Physical Sciences

20h-index2.9kcitations33works2.52yr avg
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Research Topics

Computational Drug Discovery Methods(27), Machine Learning in Materials Science(9), Cholinesterase and Neurodegenerative Diseases(8), Synthesis and biological activity(6), Spectroscopy and Chemometric Analyses(5)

Publications33 total

A round-robin exercise for the precise prediction of aqueous solubility of organic chemicals using chemometric, machine learning, and stacking ensemble of deep learning models
2026
Addressing the challenges of acute fish toxicity hazard classification using a non-animal defined approach
Environmental Toxicology and Chemistry·2025· 5 citedOpen Access
G4-QuadScreen: A Computational Tool for Identifying Multi-Target-Directed Anticancer Leads against G-Quadruplex DNA
Cancers·2023· 7 citedOpen Access
Prediction reliability of QSAR models: an overview of various validation tools
Archives of Toxicology·2022· 180 cited
Turning deep-eutectic solvents into value-added products for CO2 capture: A desirability-based virtual screening study
Journal of CO2 Utilization·2022· 41 cited
Machine Learning Approaches in Computational Toxicology Studies
2021· 1 cited
Development of Generalized QSAR Models for Predicting Cytotoxicity and Genotoxicity of Metal Oxides Nanoparticles
International Journal of Quantitative Structure-Property Relationships·2020· 11 citedOpen Access
Importance of Data Curation in QSAR Studies Especially While Modeling Large-Size Datasets
Methods in pharmacology and toxicology·2020· 15 cited
New Workflow for QSAR Model Development from Small Data Sets: Small Dataset Curator and Small Dataset Modeler. Integration of Data Curation, Exhaustive Double Cross-Validation, and a Set of Optimal Model Selection Techniques
Journal of Chemical Information and Modeling·2019· 62 cited
Computer-Aided Drug Design for the Identification of Multi-Target Directed Ligands (MTDLs) in Complex Diseases: An Overview
2019
QSAR-Co: An Open Source Software for Developing Robust Multitasking or Multitarget Classification-Based QSAR Models
Journal of Chemical Information and Modeling·2019· 111 citedOpen Access
Exploration of synthetic antioxidant flavonoid analogs as acetylcholinesterase inhibitors: an approach towards finding their quantitative structure–activity relationship
Medicinal Chemistry Research·2019· 32 cited
How Precise Are Our Quantitative Structure–Activity Relationship Derived Predictions for New Query Chemicals?
ACS Omega·2018· 135 citedOpen Access
“Prediction Reliability Indicator”: A new tool to judge the quality of predictions from QSAR models for new query compounds
Proceedings of MOL2NET 2018, International Conference on Multidisciplinary Sciences, 4th edition·2018· 7 citedOpen Access
Identifying natural compounds as multi-target-directed ligands against Alzheimer’s disease: an <i>in silico</i> approach
Journal of Biomolecular Structure and Dynamics·2018· 75 cited
Is it possible to improve the quality of predictions from an “intelligent” use of multiple QSAR/QSPR/QSTR models?
Journal of Chemometrics·2018· 125 cited
&lt;strong&gt;Intelligent consensus predictor: Towards more precise predictions for external set compounds&lt;/strong&gt;
2017Open Access
CADD Modeling of Multi-Target Drugs Against Alzheimer's Disease
Current Drug Targets·2017· 24 cited
How important is to detect systematic error in predictions and understand statistical applicability domain of QSAR models?
Chemometrics and Intelligent Laboratory Systems·2017· 145 cited
The “double cross-validation” software tool for MLR QSAR model development
Chemometrics and Intelligent Laboratory Systems·2016· 84 cited
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Frequent Co-authors

Kunal Roy(24), Supratik Kar(8), Rahul Balasaheb Aher(4), M. Natália D. S. Cordeiro(4), Rafael Gozalbes(3), Agnieszka Gajewicz(2), Tomasz Puzyn(2), Probir Kumar Ojha(2), Amit Kumar Halder(2), Stephen J. Barigye(2), Jyotsna Bhat-Ambure(2), Eva Serrano‐Candelas(2), Rudra Narayan Das(1), Priyanka De(1), Humberto González‐Díaz(1), Jyotsna Bhat(1), Goutam Brahmachari(1), Chee‐Yan Choo(1), Yunierkis Pérez‐Castillo(1), Abhijit Karmakar(1)