Ken C. N. Chang

2.3k total citations · 1 hit paper
21 papers, 1.8k citations indexed

About

Ken C. N. Chang is a scholar working on Molecular Biology, Genetics and Cancer Research. According to data from OpenAlex, Ken C. N. Chang has authored 21 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 8 papers in Genetics and 7 papers in Cancer Research. Recurrent topics in Ken C. N. Chang's work include Estrogen and related hormone effects (7 papers), Cancer Genomics and Diagnostics (6 papers) and CAR-T cell therapy research (3 papers). Ken C. N. Chang is often cited by papers focused on Estrogen and related hormone effects (7 papers), Cancer Genomics and Diagnostics (6 papers) and CAR-T cell therapy research (3 papers). Ken C. N. Chang collaborates with scholars based in United States, Japan and Canada. Ken C. N. Chang's co-authors include Barry S. Komm, Benita S. Katzenellenbogen, Jonna Frasor, Jeanne M. Danes, C. Richard Lyttle, Joshua D. Stender, W. Lee Kraus, Sunil Nagpal, W. Richard McCombie and Michele A. Cleary and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and Journal of Biological Chemistry.

In The Last Decade

Ken C. N. Chang

19 papers receiving 1.8k citations

Hit Papers

align trajectories sort by overperformance

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.

Profiling of Estrogen Up- and Down-Regulated Gene Expression in Human Breast Cancer Cells: Insights into Gene Networks and Pathways Underlying Estrogenic Control of Proliferation and Cell Phenotype

2003 685 citations Jonna Frasor, Jeanne M. Danes et al. Endocrinology profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ken C. N. Chang United States	13	1.2k	740	469	391	133	21	1.8k
Chao‐Xing Yuan United States	16	1.9k 1.6×	601 0.8×	325 0.7×	258 0.7×	138 1.0×	25	2.3k
Oliver Treeck Germany	25	734 0.6×	732 1.0×	543 1.2×	340 0.9×	181 1.4×	87	1.7k
Wenlin Shao United States	14	1.5k 1.3×	754 1.0×	480 1.0×	238 0.6×	178 1.3×	27	2.0k
Muriel Le Romancer France	30	1.8k 1.5×	544 0.7×	580 1.2×	244 0.6×	195 1.5×	75	2.5k
Johanna Tommiska Finland	25	1.3k 1.1×	560 0.8×	590 1.3×	336 0.9×	46 0.3×	39	1.9k
D. Dubik Canada	9	1.4k 1.2×	483 0.7×	462 1.0×	352 0.9×	136 1.0×	10	1.9k
Meei‐Huey Jeng United States	19	1.2k 1.0×	728 1.0×	565 1.2×	265 0.7×	206 1.5×	30	1.9k
George K. Belka United States	19	1.1k 1.0×	291 0.4×	774 1.7×	472 1.2×	107 0.8×	26	1.9k
Stephan P. Tenbaum Spain	17	1.2k 1.0×	281 0.4×	339 0.7×	223 0.6×	109 0.8×	23	1.6k
Claudia Lanari Argentina	29	966 0.8×	1.0k 1.4×	1.1k 2.3×	436 1.1×	295 2.2×	98	2.4k

Countries citing papers authored by Ken C. N. Chang

Since Specialization

Citations

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

Fields of papers citing papers by Ken C. N. Chang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ken C. N. Chang. 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 Ken C. N. Chang. The network helps show where Ken C. N. Chang may publish in the future.

Co-authorship network of co-authors of Ken C. N. Chang

This figure shows the co-authorship network connecting the top 25 collaborators of Ken C. N. Chang. A scholar is included among the top collaborators of Ken C. N. Chang 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 Ken C. N. Chang. Ken C. N. Chang 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

Mehta–Shah, Neha, Steven M. Horwitz, Pier Luigi Zinzani, et al.. (2024). Prediction of Clinical Response By Phased Variants in Circulating Tumor DNA (ctDNA) in the VALENTINE-PTCL01 Trial of Patients with Relapsed or Refractory (R/R) Peripheral T-Cell Lymphoma (PTCL). Blood. 144(Supplement 1). 4342–4342.

Chang, Ken C. N., Maha Karnoub, Li Liu, et al.. (2023). Quantum-First (Q-F): Clinical Bridging Study for FMS-like Tyrosine Kinase 3-Internal Tandem Duplication ( FLT3-ITD) Companion Diagnostic Development. Blood. 142(Supplement 1). 4260–4260. 1 indexed citations

Perl, Alexander E., Jörge E. Cortes, Siddhartha Ganguly, et al.. (2019). Effect of Co-Mutations and FLT3-ITD Variant Allele Frequency (VAF) on Response to Quizartinib or Salvage Chemotherapy (SC) in Relapsed/Refractory (R/R) Acute Myeloid Leukemia (AML). Blood. 134(Supplement_1). 737–737. 3 indexed citations

Levis, Mark J., Ken C. N. Chang, Christian Laing, et al.. (2018). Development of a Novel Next-Generation Sequencing (NGS)-Based Assay for Measurable Residual Disease (MRD) in FLT3-ITD AML and Its Potential Clinical Application in Patients Treated with Chemotherapy Plus FLT3 Inhibitors. Blood. 132(Supplement 1). 1459–1459. 2 indexed citations

Wallden, Brett, Irena Pekker, Naeem Dowidar, et al.. (2016). Development and analytical performance of a molecular diagnostic for anti-PD1 response on the nCounter Dx Analysis System.. Journal of Clinical Oncology. 34(15_suppl). 3034–3034. 16 indexed citations

Qiu, Ping, Gladys Arreaza, Maureen G. Maguire, et al.. (2016). Data Interoperability of Whole Exome Sequencing (WES) Based Mutational Burden Estimates from Different Laboratories. International Journal of Molecular Sciences. 17(5). 651–651. 15 indexed citations

Chang, Ken C. N., Yun Zhao, Saumya Pant, et al.. (2014). Validation of next-generation sequencing cancer panels for clinical somatic mutation profilin: Identification of source of variations and artifacts using FFPE tissues.. Journal of Clinical Oncology. 32(15_suppl). e22180–e22180.

Chang, Ken C. N. & Yun Zhao. (2014). Validation of Next Generation Sequencing Cancer Panels for Clinical Somatic Mutation Profiling-- Identification of Source of Variations and Artifacts using FFPE Tissues. 1(1). 3 indexed citations

Chang, Ken C. N., Stefan Galuska, Russell Weiner, & Matthew J. Marton. (2013). Development and Validation of a Clinical Trial Patient Stratification Assay That Interrogates 27 Mutation Sites in MAPK Pathway Genes. PLoS ONE. 8(8). e72239–e72239. 1 indexed citations

10.

Shen, Qi, Yuchen Bai, Ken C. N. Chang, et al.. (2011). Liver X Receptor-Retinoid X Receptor (LXR-RXR) Heterodimer Cistrome Reveals Coordination of LXR and AP1 Signaling in Keratinocytes. Journal of Biological Chemistry. 286(16). 14554–14563. 43 indexed citations

11.

Li, Ning, M.A. Rivera-Bermudez, Mei Zhang, et al.. (2010). LXR modulation blocks prostaglandin E ₂ production and matrix degradation in cartilage and alleviates pain in a rat osteoarthritis model. Proceedings of the National Academy of Sciences. 107(8). 3734–3739. 71 indexed citations

12.

Stender, Joshua D., Kyuri Kim, Tze Howe Charn, et al.. (2010). Genome-Wide Analysis of Estrogen Receptor α DNA Binding and Tethering Mechanisms Identifies Runx1 as a Novel Tethering Factor in Receptor-Mediated Transcriptional Activation. Molecular and Cellular Biology. 30(16). 3943–3955. 164 indexed citations

13.

Chang, Ken C. N., et al.. (2010). Estrogen Receptor β Is a Novel Therapeutic Target for Photoaging. Molecular Pharmacology. 77(5). 744–750. 33 indexed citations

14.

Chang, Ken C. N., et al.. (2009). Gene expression profiling studies of three SERMs and their conjugated estrogen combinations in human breast cancer cells: Insights into the unique antagonistic effects of bazedoxifene on conjugated estrogens. The Journal of Steroid Biochemistry and Molecular Biology. 118(1-2). 117–124. 62 indexed citations

15.

Chang, Ken C. N., et al.. (2008). Temporal profile of estrogen-dependent gene expression in LHRH-producing GT1–7 cells. Neurochemistry International. 54(2). 119–134. 9 indexed citations

16.

Berrodin, Thomas J., Ken C. N. Chang, Barry S. Komm, Leonard P. Freedman, & Sunil Nagpal. (2008). Differential Biochemical and Cellular Actions of Premarin Estrogens: Distinct Pharmacology of Bazedoxifene-Conjugated Estrogens Combination. Molecular Endocrinology. 23(1). 74–85. 58 indexed citations

17.

Chang, Ken C. N., Qi Shen, Scott A. Jelinsky, et al.. (2008). Liver X Receptor Is a Therapeutic Target for Photoaging and Chronological Skin Aging. Molecular Endocrinology. 22(11). 2407–2419. 38 indexed citations

18.

Stender, Joshua D., Jonna Frasor, Barry S. Komm, et al.. (2007). Estrogen-Regulated Gene Networks in Human Breast Cancer Cells: Involvement of E2F1 in the Regulation of Cell Proliferation. Molecular Endocrinology. 21(9). 2112–2123. 97 indexed citations

19.

Silva, José M., Mamie Z. Li, Ken C. N. Chang, et al.. (2005). Second-generation shRNA libraries covering the mouse and human genomes. Nature Genetics. 37(11). 1281–1288. 491 indexed citations

20.

Frasor, Jonna, Jeanne M. Danes, Barry S. Komm, et al.. (2003). Profiling of Estrogen Up- and Down-Regulated Gene Expression in Human Breast Cancer Cells: Insights into Gene Networks and Pathways Underlying Estrogenic Control of Proliferation and Cell Phenotype. Endocrinology. 144(10). 4562–4574. 685 indexed citations breakdown →

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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