Ai-Min Hui

3.7k total citations · 1 hit paper
16 papers, 2.2k citations indexed

About

Ai-Min Hui is a scholar working on Molecular Biology, Oncology and Hematology. According to data from OpenAlex, Ai-Min Hui has authored 16 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 5 papers in Oncology and 5 papers in Hematology. Recurrent topics in Ai-Min Hui's work include Ubiquitin and proteasome pathways (6 papers), Multiple Myeloma Research and Treatments (5 papers) and Epigenetics and DNA Methylation (4 papers). Ai-Min Hui is often cited by papers focused on Ubiquitin and proteasome pathways (6 papers), Multiple Myeloma Research and Treatments (5 papers) and Epigenetics and DNA Methylation (4 papers). Ai-Min Hui collaborates with scholars based in United States, Japan and United Kingdom. Ai-Min Hui's co-authors include Howard A. Fine, Lixin Sun, Alexander O. Vortmeyer, Antonino Passaniti, Yuri Kotliarov, Qin Su, Marc K. Rosenblum, Sandra Pastorino, Jennifer Walling and Tom Mikkelsen and has published in prestigious journals such as Blood, Hepatology and Cancer Cell.

In The Last Decade

Ai-Min Hui

16 papers receiving 2.1k 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.

Neuronal and glioma-derived stem cell factor induces angiogenesis within the brain

2006 692 citations Lixin Sun, Ai-Min Hui et al. Cancer Cell profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ai-Min Hui United States	15	1.4k	558	532	324	315	16	2.2k
Dorina Gui United States	23	862 0.6×	345 0.6×	236 0.4×	243 0.8×	191 0.6×	52	1.7k
Yuichi Shiraishi Japan	26	1.2k 0.8×	348 0.6×	538 1.0×	545 1.7×	260 0.8×	98	2.1k
Jeffrey Lin United States	19	558 0.4×	794 1.4×	216 0.4×	76 0.2×	196 0.6×	39	1.6k
Yijiang Shi United States	21	1.8k 1.3×	521 0.9×	654 1.2×	251 0.8×	163 0.5×	35	2.2k
Francesco Galimi Italy	24	1.1k 0.8×	1.2k 2.1×	101 0.2×	458 1.4×	82 0.3×	35	2.5k
Iacopo Petrini Italy	27	884 0.6×	1.0k 1.8×	86 0.2×	688 2.1×	214 0.7×	91	2.5k
Markus Thomas Germany	19	1.4k 1.0×	520 0.9×	68 0.1×	409 1.3×	71 0.2×	28	2.1k
Beatriz Martı́nez-Delgado Spain	28	1.2k 0.8×	601 1.1×	112 0.2×	823 2.5×	169 0.5×	81	2.2k
Victoria Tovar Spain	19	1.1k 0.8×	456 0.8×	93 0.2×	639 2.0×	47 0.1×	26	2.3k
Michael Lahn United States	23	1.3k 0.9×	1.1k 2.0×	63 0.1×	400 1.2×	203 0.6×	42	2.2k

Countries citing papers authored by Ai-Min Hui

Since Specialization

Citations

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

Fields of papers citing papers by Ai-Min Hui

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ai-Min Hui. 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 Ai-Min Hui. The network helps show where Ai-Min Hui may publish in the future.

Co-authorship network of co-authors of Ai-Min Hui

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

All Works

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16 of 16 papers shown

Sanchorawala, Vaishali, Giovanni Palladini, Vishal Kukreti, et al.. (2017). A phase 1/2 study of the oral proteasome inhibitor ixazomib in relapsed or refractory AL amyloidosis. Blood. 130(5). 597–605. 101 indexed citations

Smith, David C., Thea Kalebic, Jeffrey R. Infante, et al.. (2015). Phase 1 study of ixazomib, an investigational proteasome inhibitor, in advanced non-hematologic malignancies. Investigational New Drugs. 33(3). 652–663. 35 indexed citations

Richardson, Paul G., Philippe Moreau, Jacob P. Laubach, et al.. (2015). The Investigational Proteasome Inhibitor Ixazomib for the Treatment of Multiple Myeloma. Future Oncology. 11(8). 1153–1168. 22 indexed citations

Kumar, Shaji, Jesús G. Berdeja, Rubén Niesvizky, et al.. (2014). Safety and tolerability of ixazomib, an oral proteasome inhibitor, in combination with lenalidomide and dexamethasone in patients with previously untreated multiple myeloma: an open-label phase 1/2 study. The Lancet Oncology. 15(13). 1503–1512. 205 indexed citations

Richardson, Paul G., Rachid Baz, Michael Wang, et al.. (2014). Phase 1 study of twice-weekly ixazomib, an oral proteasome inhibitor, in relapsed/refractory multiple myeloma patients. Blood. 124(7). 1038–1046. 166 indexed citations

Kumar, Shaji, William Bensinger, Todd M. Zimmerman, et al.. (2014). Phase 1 study of weekly dosing with the investigational oral proteasome inhibitor ixazomib in relapsed/refractory multiple myeloma. Blood. 124(7). 1047–1055. 157 indexed citations

Sun, Lixin, Ai-Min Hui, Qin Su, et al.. (2006). Neuronal and glioma-derived stem cell factor induces angiogenesis within the brain. Cancer Cell. 9(4). 287–300. 692 indexed citations breakdown →

Kimura, Makoto, Dongfeng Tan, Kyoko Fujiwara, et al.. (2005). Frequent trefoil factor 3 (TFF3) overexpression and promoter hypomethylation in mouse and human hepatocellular carcinomas. International Journal of Oncology. 26(2). 369–77. 48 indexed citations

Hui, Ai-Min, Wei Zhang, Wei Chen, et al.. (2004). Agents with Selective Estrogen Receptor (ER) Modulator Activity Induce ApoptosisIn vitroandIn vivoin ER-Negative Glioma Cells. Cancer Research. 64(24). 9115–9123. 60 indexed citations

10.

Hui, Ai-Min, et al.. (2002). Proliferative marker Ki-67 in gallbladder carcinomas: high expression level predicts early recurrence after surgical resection. Cancer Letters. 176(2). 191–198. 20 indexed citations

11.

Takayama, Tadatoshi, et al.. (2001). An Obstructed Venous Aneurysm Presenting as an Abdominal Mass: Report of a Case. Surgery Today. 31(4). 336–339. 5 indexed citations

12.

Torzilli, Guido, Masami Minagawa, Tadatoshi Takayama, et al.. (1999). Accurate preoperative evaluation of liver mass lesions without fine-needle biopsy. Hepatology. 30(4). 889–893. 241 indexed citations

13.

Hui, Ai-Min, Lin Sun, Yae Kanai, Michiie Sakamoto, & Setsuo Hirohashi. (1998). Reduced p27Kip1 expression in hepatocellular carcinomas. Cancer Letters. 132(1-2). 67–73. 28 indexed citations

14.

Kanai, Yae, Saori Ushijima, Atsushi Ochiai, et al.. (1998). DNA hypermethylation at the D17S5 locus is associated with gastric carcinogenesis. Cancer Letters. 122(1-2). 135–141. 54 indexed citations

15.

Kanai, Yae, Saori Ushijima, Ai-Min Hui, et al.. (1997). The E-cadherin gene is silenced by CpG methylation in human hepatocellular carcinomas. International Journal of Cancer. 71(3). 355–359. 225 indexed citations

16.

Hui, Ai-Min, Seiji Kawasaki, Masatoshi Makuuchi, et al.. (1994). Liver Injury Following Normothermic Ischemia in Steatotic Rat Liver. Hepatology. 20(5). 1287–1293. 93 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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