Chihae Yang

6.5k total citations · 2 hit papers
71 papers, 3.4k citations indexed

About

Chihae Yang is a scholar working on Computational Theory and Mathematics, Health, Toxicology and Mutagenesis and Small Animals. According to data from OpenAlex, Chihae Yang has authored 71 papers receiving a total of 3.4k indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Computational Theory and Mathematics, 16 papers in Health, Toxicology and Mutagenesis and 11 papers in Small Animals. Recurrent topics in Chihae Yang's work include Computational Drug Discovery Methods (31 papers), Effects and risks of endocrine disrupting chemicals (14 papers) and Carcinogens and Genotoxicity Assessment (11 papers). Chihae Yang is often cited by papers focused on Computational Drug Discovery Methods (31 papers), Effects and risks of endocrine disrupting chemicals (14 papers) and Carcinogens and Genotoxicity Assessment (11 papers). Chihae Yang collaborates with scholars based in United States, United Kingdom and Italy. Chihae Yang's co-authors include Ann M. Richard, James F. Rathman, M Cronin, Romualdo Benigni, Johann Gasteiger, Lothar Terfloth, Alexandre Varnek, Viviana Consonni, Roberto Todeschini and Denis Fourches and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Medicinal Chemistry and Polymer.

In The Last Decade

Chihae Yang

66 papers receiving 3.3k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

QSAR Modeling: Where Have You Been? Where Are You Going To?

2013 1.4k citations M Cronin, Romualdo Benigni et al. profile →
ToxCast Chemical Landscape: Paving the Road to 21st Century Toxicology

2016 480 citations Ann M. Richard, Chihae Yang et al. Chemical Research in Toxicology profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Chihae Yang United States	25	1.9k	1.2k	653	490	400	71	3.4k
Kamel Mansouri United States	25	1.7k 0.9×	1.1k 1.0×	1.5k 2.3×	409 0.8×	485 1.2×	52	4.0k
Judith C. Madden United Kingdom	32	1.2k 0.7×	627 0.5×	740 1.1×	242 0.5×	442 1.1×	104	3.0k
Steven J. Enoch United Kingdom	31	1.2k 0.6×	573 0.5×	720 1.1×	202 0.4×	401 1.0×	79	2.7k
Alexander Sedykh United States	28	1.3k 0.7×	782 0.7×	398 0.6×	412 0.8×	311 0.8×	51	2.3k
James F. Rathman United States	28	1.4k 0.7×	1.2k 1.0×	428 0.7×	823 1.7×	222 0.6×	63	3.9k
Nina Jeliazkova United Kingdom	25	1.5k 0.8×	915 0.8×	347 0.5×	590 1.2×	133 0.3×	67	2.7k
Ovanes Mekenyan Bulgaria	39	2.2k 1.2×	702 0.6×	1.6k 2.5×	235 0.5×	472 1.2×	173	4.6k
Romualdo Benigni Italy	37	2.9k 1.5×	1.6k 1.4×	950 1.5×	632 1.3×	363 0.9×	148	5.5k
Cecilia Bossa Italy	27	864 0.5×	680 0.6×	439 0.7×	191 0.4×	166 0.4×	54	2.1k
Ruili Huang United States	48	2.6k 1.4×	3.3k 2.8×	1.3k 1.9×	422 0.9×	713 1.8×	219	8.0k

Countries citing papers authored by Chihae Yang

Since Specialization

Citations

This map shows the geographic impact of Chihae Yang'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 Chihae Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chihae Yang more than expected).

Fields of papers citing papers by Chihae Yang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chihae Yang. 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 Chihae Yang. The network helps show where Chihae Yang may publish in the future.

Co-authorship network of co-authors of Chihae Yang

This figure shows the co-authorship network connecting the top 25 collaborators of Chihae Yang. A scholar is included among the top collaborators of Chihae Yang 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 Chihae Yang. Chihae Yang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Roncaglioni, Alessandra, et al.. (2025). The evolution of the EFSA OpenFoodTox database. 3(1). 1798–1798. 1 indexed citations

Benfenati, Emilio, Alessandra Roncaglioni, Marco Marzo, et al.. (2024). Maintenance, update and further development of EFSA's Chemical Hazards: OpenFoodTox 2.0. EFSA Supporting Publications. 21(1). 2 indexed citations

Hung, San-Shan, et al.. (2024). A Study on Optimizing Indoor Air Quality Through the Integration of Multi-Point Monitoring and the Design of a Wet Scrubber. 37–41.

Li, Xiting, et al.. (2024). The role of aryl hydrocarbon receptor in the occurrence and development of periodontitis. Frontiers in Immunology. 15. 1494570–1494570.

Richard, Ann M., Ryan Lougee, Matthew S. Adams, et al.. (2023). A New CSRML Structure-Based Fingerprint Method for Profiling and Categorizing Per- and Polyfluoroalkyl Substances (PFAS). Chemical Research in Toxicology. 36(3). 508–534. 17 indexed citations

Yang, Chihae, James F. Rathman, Aleksandra Mostrąg, et al.. (2023). High Throughput Read-Across for Screening a Large Inventory of Related Structures by Balancing Artificial Intelligence/Machine Learning and Human Knowledge. Chemical Research in Toxicology. 36(7). 1081–1106. 8 indexed citations

Yang, Chihae, James F. Rathman, Monika Batke, et al.. (2023). Update of the Cancer Potency Database (CPDB) to enable derivations of Thresholds of Toxicological Concern (TTC) for cancer potency. Food and Chemical Toxicology. 182. 114182–114182. 4 indexed citations

Benfenati, Emilio, Alessandra Roncaglioni, Marco Marzo, et al.. (2022). Maintenance, update and further development of EFSA's Chemical Hazards: OpenFoodTox 2.0. EFSA Supporting Publications. 19(12). 6 indexed citations

Yamada, Takashi, et al.. (2021). Development of a New Threshold of Toxicological Concern Database of Non-cancer Toxicity Endpoints for Industrial Chemicals. Frontiers in Toxicology. 3. 626543–626543. 7 indexed citations

10.

Yang, Chihae, James F. Rathman, Tomasz Magdziarz, et al.. (2020). Do Similar Structures Have Similar No Observed Adverse Effect Level (NOAEL) Values? Exploring Chemoinformatics Approaches for Estimating NOAEL Bounds and Uncertainties. Chemical Research in Toxicology. 34(2). 616–633. 14 indexed citations

11.

Firman, James W., et al.. (2020). A Robust, Mechanistically Based In Silico Structural Profiler for Hepatic Cholestasis. Chemical Research in Toxicology. 34(2). 641–655. 4 indexed citations

12.

Rathman, James F., Chihae Yang, Aleksandra Mostrąg, et al.. (2020). Development of a Battery of In Silico Prediction Tools for Drug-Induced Liver Injury from the Vantage Point of Translational Safety Assessment. Chemical Research in Toxicology. 34(2). 601–615. 10 indexed citations

13.

Yang, Chihae, M Cheeseman, James F. Rathman, et al.. (2020). A new paradigm in threshold of toxicological concern based on chemoinformatics analysis of a highly curated database enriched with antimicrobials. Food and Chemical Toxicology. 143. 111561–111561. 15 indexed citations

14.

Benigni, Romualdo, Rositsa Serafimova, Juan Manuel Parra Morte, et al.. (2020). Evaluation of the applicability of existing (Q)SAR models for predicting the genotoxicity of pesticides and similarity analysis related with genotoxicity of pesticides for facilitating of grouping and read across: An EFSA funded project. Regulatory Toxicology and Pharmacology. 114. 104658–104658. 31 indexed citations

15.

Benigni, Romualdo, Chiara Laura Battistelli, Cecilia Bossa, et al.. (2019). Evaluation of the applicability of existing (Q)SAR models for predicting the genotoxicity of pesticides and similarity analysis related with genotoxicity of pesticides for facilitating of grouping and read across. EFSA Supporting Publications. 16(3). 28 indexed citations

16.

Mellor, Claire L., Richard Marchese Robinson, Steven J. Enoch, et al.. (2018). Molecular fingerprint-derived similarity measures for toxicological read-across: Recommendations for optimal use. Regulatory Toxicology and Pharmacology. 101. 121–134. 71 indexed citations

17.

Cronin, M, Sylvia E. Escher, James W. Firman, et al.. (2017). Extension of the carcinogen dose–response database for threshold of toxicological concern. Toxicology Letters. 280. S284–S284. 1 indexed citations

18.

Williams, Faith M., Helga Rothe, Alessandro Chiodini, et al.. (2016). Assessing the safety of cosmetic chemicals: Consideration of a flux decision tree to predict dermally delivered systemic dose for comparison with oral TTC (Threshold of Toxicological Concern). Regulatory Toxicology and Pharmacology. 76. 174–186. 43 indexed citations

19.

Tsakovska, Ivanka, Ilza Pajeva, Petko Alov, et al.. (2016). The application of molecular modelling in the safety assessment of chemicals: A case study on ligand-dependent PPARγ dysregulation. Toxicology. 392. 140–154. 19 indexed citations

20.

Benfenati, Emilio, Romualdo Benigni, David M. DeMarini, et al.. (2009). Predictive Models for Carcinogenicity and Mutagenicity: Frameworks, State-of-the-Art, and Perspectives. Journal of Environmental Science and Health Part C. 27(2). 57–90. 90 indexed citations

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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