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, Lothar Terfloth, Johann Gasteiger, Yvonne C. Martin, Artem Cherkasov, Viviana Consonni and V. Е. Kuz’min 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

QSAR Modeling: Where Have You Been? Where Are You Going To? 2013 2026 2017 2021 2013 2016 400 800 1.2k

Peers — A (Enhanced Table)

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

Name h Career Trend 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

20 of 20 papers shown
1.
Roncaglioni, Alessandra, et al.. (2025). The evolution of the EFSA OpenFoodTox database. 3(1). 1798–1798. 1 indexed citations
2.
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
3.
Li, Xiting, et al.. (2024). The role of aryl hydrocarbon receptor in the occurrence and development of periodontitis. Frontiers in Immunology. 15. 1494570–1494570.
5.
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
6.
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
7.
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
8.
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
9.
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
10.
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
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.
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
13.
Cronin, M, Judith C. Madden, Chihae Yang, & Andrew Worth. (2018). Unlocking the potential of in silico chemical safety assessment – A report on a cross-sector symposium on current opportunities and future challenges. Computational Toxicology. 10. 38–43. 27 indexed citations
14.
Tsakovska, Ivanka, Ilza Pajeva, Petko Alov, et al.. (2017). Quantitative structure-skin permeability relationships. Toxicology. 387. 27–42. 72 indexed citations
15.
Yang, Chihae, Susan Barlow, Vessela Vitcheva, et al.. (2017). Thresholds of Toxicological Concern for cosmetics-related substances: New database, thresholds, and enrichment of chemical space. Food and Chemical Toxicology. 109(Pt 1). 170–193. 74 indexed citations
16.
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
17.
Alov, Petko, M Cronin, Elena Fioravanzo, et al.. (2013). Toward better understanding of liver steatosis MoA: Molecular modelling study of PPAR gamma receptor. Toxicology Letters. 221. S85–S85. 2 indexed citations
18.
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
19.
Fostel, Jennifer, Lyle D. Burgoon, Craig Zwickl, et al.. (2007). Toward a Checklist for Exchange and Interpretation of Data from a Toxicology Study. Toxicological Sciences. 99(1). 26–34. 13 indexed citations
20.
Blower, Paul E., Chihae Yang, Michael A. Fligner, et al.. (2002). Pharmacogenomic analysis: correlating molecular substructure classes with microarray gene expression data. The Pharmacogenomics Journal. 2(4). 259–271. 76 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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