🏆 Finalist — NIH Data Sharing Index (“S-Index”) Challenge

Igor V. Tetko

Society for Chemical Engineering and Biotechnology

ORCID: 0000-0002-6855-0012

Also affiliated with Helmholtz Munich, Institute of Structural and Molecular Biology

Computer ScienceMaterials ScienceChemistryBiochemistry, Genetics and Molecular Biology

Pilot corpus only

This score is computed over theSindex pilot corpus and does not cover the full scientific literature. Scores are relative to papers we have ingested — papers, authors, and institutions outside the pilot are not represented. Methodology.

Top 1%percentile
4.9Author DataRank

Indexed papers

2in pilot corpus
datarank_citation_only_1hop_v6· scope data_onlyMethodology
Why this DataRank?

An author's DataRank is the sum of the DataRanks of all 2 indexed papers attributed to them. A prolific author with many moderate-impact papers can outrank one with a single high-impact paper.

Author scores recompute whenever paper DataRanks are refreshed, so this number lags the underlying paper scores by at most one batch run.

Read the full methodology →

Top data-sharing exemplar

The highest-impact dataset this researcher has shared, ranked by DataRank — the single contribution doing the most to lift their data-sharing standing.

CATMoS: Collaborative Acute Toxicity Modeling Suite

Environmental Health Perspectives(2021)10.1289/ehp8495
Top 4%
4.9DataRank
Top 4%142 citations

Agnes L. Karmaus, Jeremy Fitzpatrick, Grace Patlewicz, Prachi Pradeep, Domenico Alberga +95 more

Papers

Driven by 12 papers — median percentile 96. Top paper: “CATMoS: Collaborative Acute Toxicity Modeling Suite”.

CATMoS: Collaborative Acute Toxicity Modeling Suite

Environmental Health Perspectives(2021)10.1289/ehp8495
Top 4%
4.9DataRank
Top 4%142 citations

Agnes L. Karmaus, Jeremy Fitzpatrick, Grace Patlewicz, Prachi Pradeep, Domenico Alberga +95 more

Artificial Neural Networks and Machine Learning – ICANN 2019: Text and Time Series

Lecture Notes in Computer Science(2019)10.1007/978-3-030-30490-4
N/A
1.6DataRank · unranked
37 citations

Věra Kůrková, Pavel Karpov, Fabian Joachim Theis, Theis, Fabian, Igor V. Tetko

QSAR without borders

Chemical Society Reviews(2020)10.1039/d0cs00098a
N/A
1.0DataRank · unranked
870 citations

Jürgen Bajorath, Robert P. Sheridan, Igor V. Tetko, Dmitry Filimonov, Vladimir Poroikov +14 more

Tox24 Challenge

Chemical Research in Toxicology(2024)10.1021/acs.chemrestox.4c00192
N/A
0.425DataRank · unranked
16 citations

Igor V. Tetko

Artificial Neural Networks and Machine Learning – ICANN 2019: Workshop and Special Sessions

Lecture Notes in Computer Science(2019)10.1007/978-3-030-30493-5
N/A
0.312DataRank · unranked
7 citations

Věra Kůrková, Pavel Karpov, Fabian Joachim Theis, Theis, Fabian, Igor V. Tetko

Artificial Neural Networks and Machine Learning – ICANN 2019: Deep Learning

Lecture Notes in Computer Science(2019)10.1007/978-3-030-30484-3
N/A
0.208DataRank · unranked
3 citations

Věra Kůrková, Pavel Karpov, Fabian Joachim Theis, Theis, Fabian, Igor V. Tetko

Artificial Neural Networks and Machine Learning – ICANN 2019: Image Processing

Lecture Notes in Computer Science(2019)10.1007/978-3-030-30508-6
N/A
0.104DataRank · unranked
1 citations

Věra Kůrková, Pavel Karpov, Fabian Joachim Theis, Theis, Fabian, Igor V. Tetko

Erratum: CATMoS: Collaborative Acute Toxicity Modeling Suite

Environmental Health Perspectives(2021)10.1289/ehp10369
N/A
0DataRank · unranked
31 citations

Agnes L. Karmaus, Jeremy Fitzpatrick, Grace Patlewicz, Prachi Pradeep, Domenico Alberga +95 more

Assessment of fine-tuned large language models for real-world chemistry and material science applications

Chemical Science(2024)10.1039/d4sc04401k
N/A
0DataRank · unranked
51 citations

M.V. Gil, Kevin Maik Jablonka, Alex Abrudan, Andy S. Anker, Mehrdad Asgari +45 more

Assessment of Fine-Tuned Large Language Models for Real-World Chemistry and Material Science Applications

ChemRxiv(2024)10.26434/chemrxiv-2024-mm31v
N/A
0DataRank · unranked
2 citations

M.V. Gil, Kevin Maik Jablonka, Alex Abrudan, Andy S. Anker, Mehrdad Asgari +41 more

Therapeutic Potential of Targeting Prokineticin Receptors in Diseases

Pharmacological Reviews(2023)10.1124/pharmrev.122.000801
N/A
0DataRank · unranked
18 citations

Amin Kremić, A Jouve, Roberta Lattanzi, Rossella Miele, Mohamed Benharouga +9 more

Trade-off Predictivity and Explainability for Machine-Learning Powered Predictive Toxicology: An in-Depth Investigation with Tox21 Data Sets

Chemical Research in Toxicology(2021)10.1021/acs.chemrestox.0c00373
N/A
0DataRank · unranked
67 citations

Ruili Huang, Igor V. Tetko, Zhonghua Xia, Joshua Xu, Weida Tong