Carol Wai

2.0k total citations · 1 hit paper
5 papers, 879 citations indexed

About

Carol Wai is a scholar working on Public Health, Environmental and Occupational Health, Hematology and Immunology. According to data from OpenAlex, Carol Wai has authored 5 papers receiving a total of 879 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Public Health, Environmental and Occupational Health, 4 papers in Hematology and 2 papers in Immunology. Recurrent topics in Carol Wai's work include Acute Lymphoblastic Leukemia research (4 papers), Acute Myeloid Leukemia Research (3 papers) and Immune Cell Function and Interaction (2 papers). Carol Wai is often cited by papers focused on Acute Lymphoblastic Leukemia research (4 papers), Acute Myeloid Leukemia Research (3 papers) and Immune Cell Function and Interaction (2 papers). Carol Wai collaborates with scholars based in Canada, United States and France. Carol Wai's co-authors include Jon C. Aster, Andrew P. Weng, Arthur Lau, Carlos G. Rodríguez, Yue‐Ming Li, Hong Sai, John W. Tobias, Stephen C. Blacklow, Dean W. Felsher and John M. Millholland and has published in prestigious journals such as Nature Medicine, The Journal of Experimental Medicine and Genes & Development.

In The Last Decade

Carol Wai

5 papers receiving 870 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.

c-Myc is an important direct target of Notch1 in T-cell acute lymphoblastic leukemia/lymphoma

2006 673 citations Andrew P. Weng, John M. Millholland et al. Genes & Development profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Carol Wai Canada	4	646	194	178	174	147	5	879
Tomas Vilimas United States	8	572 0.9×	193 1.0×	202 1.1×	167 1.0×	202 1.4×	8	829
Archana Agarwal United States	7	679 1.1×	219 1.1×	154 0.9×	200 1.1×	103 0.7×	18	971
Todd Ashworth United States	12	622 1.0×	117 0.6×	134 0.8×	175 1.0×	131 0.9×	13	851
Richard Monni France	8	305 0.5×	147 0.8×	200 1.1×	244 1.4×	99 0.7×	8	603
Corrado Caslini United States	14	746 1.2×	136 0.7×	139 0.8×	229 1.3×	42 0.3×	20	937
Christopher Slape United States	15	691 1.1×	92 0.5×	104 0.6×	513 2.9×	135 0.9×	29	970
Teresa Larson United Kingdom	7	629 1.0×	204 1.1×	135 0.8×	368 2.1×	158 1.1×	8	943
Jorge DiMartino United States	14	829 1.3×	137 0.7×	217 1.2×	588 3.4×	117 0.8×	42	1.2k
Kaat Durinck Belgium	13	335 0.5×	111 0.6×	93 0.5×	98 0.6×	101 0.7×	26	548
Monique Passier Netherlands	10	260 0.4×	187 1.0×	99 0.6×	144 0.8×	52 0.4×	11	490

Countries citing papers authored by Carol Wai

Since Specialization

Citations

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

Fields of papers citing papers by Carol Wai

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Carol Wai

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

All Works

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5 of 5 papers shown

1.

Giambra, Vincenzo, Christopher Jenkins, Hongfang Wang, et al.. (2012). NOTCH1 promotes T cell leukemia-initiating activity by RUNX-mediated regulation of PKC-θ and reactive oxygen species. Nature Medicine. 18(11). 1693–1698. 68 indexed citations

2.

Medyouf, Hind, Samuel Gusscott, Hongfang Wang, et al.. (2011). High-level IGF1R expression is required for leukemia-initiating cell activity in T-ALL and is supported by Notch signaling. The Journal of Cell Biology. 194(3). i8–i8. 4 indexed citations

3.

Medyouf, Hind, Samuel Gusscott, Hongfang Wang, et al.. (2011). High-level IGF1R expression is required for leukemia-initiating cell activity in T-ALL and is supported by Notch signaling. The Journal of Experimental Medicine. 208(9). 1809–1822. 131 indexed citations

4.

Giambra, Vincenzo, Oksana Nemirovsky, Sonya H.L. Lam, et al.. (2010). Notch-Mediated Suppression of PKCθ Reduces Reactive Oxygen Species and Promotes Leukemic Stem Cell Activity In T-Cell Acute Lymphoblastic Leukemia (T-ALL). Blood. 116(21). 12–12. 3 indexed citations

5.

Weng, Andrew P., John M. Millholland, Yumi Yashiro–Ohtani, et al.. (2006). c-Myc is an important direct target of Notch1 in T-cell acute lymphoblastic leukemia/lymphoma. Genes & Development. 20(15). 2096–2109. 673 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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