Geven Piir

434 total citations
11 papers, 163 citations indexed

About

Geven Piir is a scholar working on Computational Theory and Mathematics, Health, Toxicology and Mutagenesis and Molecular Biology. According to data from OpenAlex, Geven Piir has authored 11 papers receiving a total of 163 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Computational Theory and Mathematics, 5 papers in Health, Toxicology and Mutagenesis and 4 papers in Molecular Biology. Recurrent topics in Geven Piir's work include Computational Drug Discovery Methods (8 papers), Analytical Chemistry and Chromatography (3 papers) and Environmental Toxicology and Ecotoxicology (3 papers). Geven Piir is often cited by papers focused on Computational Drug Discovery Methods (8 papers), Analytical Chemistry and Chromatography (3 papers) and Environmental Toxicology and Ecotoxicology (3 papers). Geven Piir collaborates with scholars based in Estonia, Sweden and Austria. Geven Piir's co-authors include Uko Maran, Sulev Sild, Alfonso T. García‐Sosa, Iiris Kahn, Alessandra Roncaglioni, Emilio Benfenati, E. Vila, Manuel Pastor, Jaan Leis and Nikolai Georgiev Nikolov and has published in prestigious journals such as Journal of Hazardous Materials, Environmental Health Perspectives and Chemosphere.

In The Last Decade

Geven Piir

10 papers receiving 162 citations

Peers

Countries citing papers authored by Geven Piir

Since Specialization

Citations

This map shows the geographic impact of Geven Piir's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Geven Piir with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Geven Piir more than expected).

Fields of papers citing papers by Geven Piir

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Geven Piir. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Geven Piir. The network helps show where Geven Piir may publish in the future.

Co-authorship network of co-authors of Geven Piir

This figure shows the co-authorship network connecting the top 25 collaborators of Geven Piir. A scholar is included among the top collaborators of Geven Piir based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Geven Piir. Geven Piir is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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11 of 11 papers shown

#	Work	Indexed citations
1	Moving towards making (quantitative) structure-activity relationships ((Q)SARs) for toxicity-related endpoints findable, accessible, interoperable and reusable (FAIR) 2025 ·ALTEX ·(unknown), Hassan Basiri, (unknown), (unknown), Steven J. Enoch, James W. Firman, (unknown), (unknown), (unknown), Judith C. Madden, Uko Maran, E. Vila, Nikolai Georgiev Nikolov, Manuel Pastor, Geven Piir, Sulev Sild, (unknown), Nicoleta Sp̂înu, Eva Bay Wedebye, M Cronin	0
2	Predictive Modeling of Pesticides Reproductive Toxicity in Earthworms Using Interpretable Machine-Learning Techniques on Imbalanced Data 2025 ·ACS Omega ·(unknown), Geven Piir, Uko Maran	1
3	Nanomaterial Texture-Based Machine Learning of Ciprofloxacin Adsorption on Nanoporous Carbon 2024 ·International Journal of Molecular Sciences ·Maike Käärik, (unknown), Uko Maran, (unknown), Geven Piir, Jaan Leis	1
4	Interpretable machine learning for the identification of estrogen receptor agonists, antagonists, and binders 2023 ·Chemosphere ·Geven Piir, Sulev Sild, Uko Maran	6
5	Pesticide effect on earthworm lethality via interpretable machine learning 2023 ·Journal of Hazardous Materials ·(unknown), Geven Piir, Uko Maran	7
6	Intrinsic Aqueous Solubility: Mechanistically Transparent Data-Driven Modeling of Drug Substances 2022 ·Pharmaceutics ·(unknown), Sulev Sild, Geven Piir, Uko Maran	14
7	Binary and multi-class classification for androgen receptor agonists, antagonists and binders 2020 ·Chemosphere ·Geven Piir, Sulev Sild, Uko Maran	26
8	Best Practices for QSAR Model Reporting: Physical and Chemical Properties, Ecotoxicity, Environmental Fate, Human Health, and Toxicokinetics Endpoints 2018 ·Environmental Health Perspectives ·Geven Piir, Iiris Kahn, Alfonso T. García‐Sosa, Sulev Sild, (unknown), Uko Maran	61
9	Classifying bio-concentration factor with random forest algorithm, influence of the bio-accumulative vs. non-bio-accumulative compound ratio to modelling result, and applicability domain for random forest model 2014 ·SAR and QSAR in environmental research ·Geven Piir, Sulev Sild, Uko Maran	17
10	Comparative analysis of local and consensus quantitative structure-activity relationship approaches for the prediction of bioconcentration factor 2013 ·SAR and QSAR in environmental research ·Geven Piir, Sulev Sild, Uko Maran	9
11	QSAR model for the prediction of bio-concentration factor using aqueous solubility and descriptors considering various electronic effects 2010 ·SAR and QSAR in environmental research ·Geven Piir, Sulev Sild, Alessandra Roncaglioni, Emilio Benfenati, Uko Maran	21

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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