Chia-Jui Ku

452 total citations
11 papers, 347 citations indexed

About

Chia-Jui Ku is a scholar working on Molecular Biology, Physiology and Cell Biology. According to data from OpenAlex, Chia-Jui Ku has authored 11 papers receiving a total of 347 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 4 papers in Physiology and 3 papers in Cell Biology. Recurrent topics in Chia-Jui Ku's work include Nitric Oxide and Endothelin Effects (3 papers), Immune Cell Function and Interaction (3 papers) and Adenosine and Purinergic Signaling (2 papers). Chia-Jui Ku is often cited by papers focused on Nitric Oxide and Endothelin Effects (3 papers), Immune Cell Function and Interaction (3 papers) and Adenosine and Purinergic Signaling (2 papers). Chia-Jui Ku collaborates with scholars based in United States, Poland and Russia. Chia-Jui Ku's co-authors include James Douglas Engel, Tomonori Hosoya, Dana M. Spence, Ivan Maillard, Ajith Karunarathne, Kim-Chew Lim, Masayuki Yamamoto, William D. Brandt, Sally A. Camper and Paul Root and has published in prestigious journals such as Journal of Clinical Investigation, Genes & Development and Blood.

In The Last Decade

Chia-Jui Ku

11 papers receiving 343 citations

Peers

Chia-Jui Ku

MB

IMMUN

HEMAT

PHYSI

CB

Michelle Nguyen-McCarty United States

Immanuel Andrä Germany

Nicola Hellen United Kingdom

Erik L. Bao United States

Andrew DeVilbiss United States

Kim Vanuytsel United States

Isidoro Cobo United States

Martha Lopez‐Yrigoyen United Kingdom

Frances J. Fogerty United States

Kimihiko Banno Japan

Michelle Nguyen-McCarty United States

Chia-Jui Ku

283 ×1.8

MB

36 ×0.4

IMMUN

87 ×1.1

HEMAT

57 ×1.1

PHYSI

52 ×1.0

CB

Citations per year, relative to Chia-Jui Ku Chia-Jui Ku (= 1×) peers Michelle Nguyen-McCarty

Countries citing papers authored by Chia-Jui Ku

Since Specialization

Citations

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

Fields of papers citing papers by Chia-Jui Ku

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chia-Jui Ku. 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 Chia-Jui Ku. The network helps show where Chia-Jui Ku may publish in the future.

Co-authorship network of co-authors of Chia-Jui Ku

This figure shows the co-authorship network connecting the top 25 collaborators of Chia-Jui Ku. A scholar is included among the top collaborators of Chia-Jui Ku 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 Chia-Jui Ku. Chia-Jui Ku 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

1.

Ku, Chia-Jui, JoAnn Sekiguchi, Bharat Panwar, et al.. (2017). GATA3 Abundance Is a Critical Determinant of T Cell Receptor β Allelic Exclusion. Molecular and Cellular Biology. 37(12). 3 indexed citations

2.

Mizuno, Seiya, Hisashi Oishi, Chia-Jui Ku, et al.. (2016). Lineage-affiliated transcription factors bind the Gata3 Tce1 enhancer to mediate lineage-specific programs. Journal of Clinical Investigation. 126(3). 865–878. 19 indexed citations

3.

Ku, Chia-Jui, Kim-Chew Lim, Sundeep Kalantry, et al.. (2015). A monoallelic-to-biallelic T-cell transcriptional switch regulates GATA3 abundance. Genes & Development. 29(18). 1930–1941. 11 indexed citations

4.

Lim, Kim-Chew, Tomonori Hosoya, William D. Brandt, et al.. (2012). Conditional Gata2 inactivation results in HSC loss and lymphatic mispatterning. Journal of Clinical Investigation. 122(10). 3705–3717. 116 indexed citations

5.

Ku, Chia-Jui, Tomonori Hosoya, Ivan Maillard, & James Douglas Engel. (2012). GATA-3 regulates hematopoietic stem cell maintenance and cell-cycle entry. Blood. 119(10). 2242–2251. 79 indexed citations

6.

Tolan, Nicole V., Jennifer Meyer, Chia-Jui Ku, Ajith Karunarathne, & Dana M. Spence. (2010). Use of the red blood cell as a simple drug target and diagnostic by manipulating and monitoring its ability to release adenosine triphosphate (ATP). Pure and Applied Chemistry. 82(8). 1623–1634. 2 indexed citations

7.

Meyer, Jennifer, et al.. (2009). A Molecular Level Understanding of Zinc Activation of C-peptide and its Effects on Cellular Communication in the Bloodstream. The Review of Diabetic Studies. 6(3). 148–158. 15 indexed citations

8.

Karunarathne, Ajith, Chia-Jui Ku, & Dana M. Spence. (2009). The dual nature of extracellular ATP as a concentration-dependent platelet P2X1 agonist and antagonist. Integrative Biology. 1(11-12). 655–655. 20 indexed citations

9.

Ku, Chia-Jui, et al.. (2008). Interactions between Multiple Cell Types in Parallel Microfluidic Channels: Monitoring Platelet Adhesion to an Endothelium in the Presence of an Anti-Adhesion Drug. Analytical Chemistry. 80(19). 7543–7548. 37 indexed citations

10.

Ku, Chia-Jui, et al.. (2007). Red Blood Cell Stimulation of Platelet Nitric Oxide Production Indicated by Quantitative Monitoring of the Communication between Cells in the Bloodstream. Analytical Chemistry. 79(14). 5133–5138. 26 indexed citations

11.

Ku, Chia-Jui, et al.. (2007). Fluorescence Determination of Nitric Oxide Production in Stimulated and Activated Platelets. Analytical Chemistry. 79(6). 2421–2426. 19 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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