YT Tai

980 total citations
10 papers, 543 citations indexed

About

YT Tai is a scholar working on Molecular Biology, Hematology and Oncology. According to data from OpenAlex, YT Tai has authored 10 papers receiving a total of 543 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 7 papers in Hematology and 4 papers in Oncology. Recurrent topics in YT Tai's work include Multiple Myeloma Research and Treatments (7 papers), Cancer Mechanisms and Therapy (3 papers) and Peptidase Inhibition and Analysis (3 papers). YT Tai is often cited by papers focused on Multiple Myeloma Research and Treatments (7 papers), Cancer Mechanisms and Therapy (3 papers) and Peptidase Inhibition and Analysis (3 papers). YT Tai collaborates with scholars based in United States, Austria and Germany. YT Tai's co-authors include Teru Hideshima, Benno Rattel, Matthias Friedrich, Oliver S. Thomas, Jochen Wahl, Paul J. Adam, Susanne Hipp, Diann Blanset, D Chauhan and Nikhil C. Munshi and has published in prestigious journals such as Blood, Oncogene and Leukemia.

In The Last Decade

YT Tai

10 papers receiving 537 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
YT Tai United States	6	366	247	245	95	90	10	543
Irene Manrique Spain	9	206 0.6×	199 0.8×	151 0.6×	53 0.6×	58 0.6×	15	384
Heather Kostner United States	7	263 0.7×	413 1.7×	107 0.4×	208 2.2×	102 1.1×	12	624
Turner Kufe United States	6	216 0.6×	164 0.7×	128 0.5×	40 0.4×	148 1.6×	7	368
Emmanuelle Ménoret France	10	444 1.2×	160 0.6×	194 0.8×	30 0.3×	119 1.3×	14	574
Torsten Steinbrunn Germany	11	348 1.0×	98 0.4×	211 0.9×	26 0.3×	56 0.6×	21	460
John S. Strader United States	4	582 1.6×	275 1.1×	384 1.6×	20 0.2×	53 0.6×	7	706
D Chauhan United States	5	274 0.7×	151 0.6×	192 0.8×	15 0.2×	81 0.9×	7	403
Marie-Pierre Gras France	8	207 0.6×	149 0.6×	102 0.4×	88 0.9×	258 2.9×	12	525
Sinto Sebastian United States	8	265 0.7×	188 0.8×	76 0.3×	51 0.5×	24 0.3×	11	412
Soraya Wuillème‐Toumi France	5	467 1.3×	151 0.6×	230 0.9×	15 0.2×	75 0.8×	6	553

Countries citing papers authored by YT Tai

Since Specialization

Citations

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

Fields of papers citing papers by YT Tai

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of YT Tai

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

All Works

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10 of 10 papers shown

1.

Song, Yan, S Li, Arjun Ray, et al.. (2017). Blockade of deubiquitylating enzyme Rpn11 triggers apoptosis in multiple myeloma cells and overcomes bortezomib resistance. Oncogene. 36(40). 5631–5638. 83 indexed citations

2.

Harada, Takeshi, Hiroto Ohguchi, Yohann Grondin, et al.. (2017). HDAC3 regulates DNMT1 expression in multiple myeloma: therapeutic implications. Leukemia. 31(12). 2670–2677. 66 indexed citations

3.

Hipp, Susanne, YT Tai, Diann Blanset, et al.. (2016). A novel BCMA/CD3 bispecific T-cell engager for the treatment of multiple myeloma induces selective lysis in vitro and in vivo. Leukemia. 31(8). 1743–1751. 194 indexed citations

4.

Hideshima, Teru, Francesca Cottini, Hiroto Ohguchi, et al.. (2015). Rational combination treatment with histone deacetylase inhibitors and immunomodulatory drugs in multiple myeloma. Blood Cancer Journal. 5(5). e312–e312. 53 indexed citations

5.

Podar, Klaus, Steven Le Gouill, Joseph T. Opferman, et al.. (2007). A pivotal role for Mcl-1 in Bortezomib-induced apoptosis. Oncogene. 27(6). 721–731. 106 indexed citations

6.

Tai, YT, Klaus Podar, Reshma Shringarpure, et al.. (2003). Insulin-like growth factor-1 induces adhesion and migration in human multiple myeloma cells via activation of b1-integrin and phosphatidylinositol 3-kinase/AKT signaling beta.. Blood. 102(11). 33 indexed citations

7.

Shringarpure, Reshma, D Chauhan, Renate Burger, et al.. (2003). Gene expression analysis of tumor cells sensitive and resistant to PS-341 (Bortezomib) treatment: Clinical implications.. Blood. 102(11). 1 indexed citations

8.

Podar, Klaus, Gustavo Mostoslavsky, YT Tai, et al.. (2003). Critical role for Hck-mediated phosphorylation of Gab1 and Gab2 docking proteins in interleukin-6-induced proliferation and survival of multiple myeloma cells.. Blood. 102(11). 1 indexed citations

9.

Weisberg, Ellen, YT Tai, Boris K. Lin, et al.. (2002). LAQ824 is a novel histone deacetylase inhibitor with significant activity against multiple myeloma: Results of a pre-clinical evaluation in vitro and in vivo.. Blood. 100(11). 5 indexed citations

10.

Gupta, Tapas K. Das, Richard LeBlanc, Klaus Podar, et al.. (2001). beta-Lapachone is safe and effective in Biege-Nude-Xid mouse xenograft model of human plasmacytoma.. Blood. 98(11). 1 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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