Yu‐Tzu Tai

25.9k total citations · 7 hit papers
271 papers, 15.1k citations indexed

About

Yu‐Tzu Tai is a scholar working on Hematology, Molecular Biology and Oncology. According to data from OpenAlex, Yu‐Tzu Tai has authored 271 papers receiving a total of 15.1k indexed citations (citations by other indexed papers that have themselves been cited), including 191 papers in Hematology, 148 papers in Molecular Biology and 95 papers in Oncology. Recurrent topics in Yu‐Tzu Tai's work include Multiple Myeloma Research and Treatments (184 papers), Protein Degradation and Inhibitors (51 papers) and Peptidase Inhibition and Analysis (40 papers). Yu‐Tzu Tai is often cited by papers focused on Multiple Myeloma Research and Treatments (184 papers), Protein Degradation and Inhibitors (51 papers) and Peptidase Inhibition and Analysis (40 papers). Yu‐Tzu Tai collaborates with scholars based in United States, China and Italy. Yu‐Tzu Tai's co-authors include Kenneth C. Anderson, Teru Hideshima, Nikhil C. Munshi, Dharminder Chauhan, Paul G. Richardson, Noopur Raje, Klaus Podar, Steven P. Treon, Robert Schlossman and Boris K. Lin and has published in prestigious journals such as Cell, Proceedings of the National Academy of Sciences and Journal of Biological Chemistry.

In The Last Decade

Yu‐Tzu Tai

265 papers receiving 14.9k citations

Hit Papers

5 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.

Neuropilin Is a Semaphorin III Receptor

1997 1.0k citations Yu‐Tzu Tai et al. profile →
Daratumumab, a Novel Therapeutic Human CD38 Monoclonal Antibody, Induces Killing of Multiple Myeloma and Other Hematological Tumors

2010 746 citations Yu‐Tzu Tai, Kenneth C. Anderson et al. profile →
Thalidomide and immunomodulatory derivatives augment natural killer cell cytotoxicity in multiple myeloma

2001 740 citations Noopur Raje, Teru Hideshima et al. Blood profile →
Thalidomide and its analogs overcome drug resistance of human multiple myeloma cells to conventional therapy

2000 708 citations Teru Hideshima, Dharminder Chauhan et al. Blood profile →
The proteasome inhibitor PS-341 potentiates sensitivity of multiple myeloma cells to conventional chemotherapeutic agents: therapeutic applications

2003 575 citations Paul G. Richardson, Yu‐Tzu Tai et al. Blood profile →
Novel anti–B-cell maturation antigen antibody-drug conjugate (GSK2857916) selectively induces killing of multiple myeloma

2014 375 citations Yu‐Tzu Tai, Paul G. Richardson et al. Blood profile →
Biallelic loss of BCMA as a resistance mechanism to CAR T cell therapy in a patient with multiple myeloma

2021 236 citations Mehmet Samur, Mariateresa Fulciniti et al. profile →

Peers

Countries citing papers authored by Yu‐Tzu Tai

Since Specialization

Citations

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

Fields of papers citing papers by Yu‐Tzu Tai

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yu‐Tzu Tai

This figure shows the co-authorship network connecting the top 25 collaborators of Yu‐Tzu Tai. A scholar is included among the top collaborators of Yu‐Tzu 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 Yu‐Tzu Tai. Yu‐Tzu 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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20 of 20 papers shown

#	Title	Journal	Authors	Indexed citations
1	ABL1 kinase plays an important role in spontaneous and chemotherapy-induced genomic instability in multiple myeloma	Blood	Subodh Kumar, Srikanth Talluri et al.	3
2	BCMA-Specific ADC MEDI2228 and Daratumumab Induce Synergistic Myeloma Cytotoxicity via IFN-Driven Immune Responses and Enhanced CD38 Expression	Clinical Cancer Research	Lijie Xing, Su Wang et al.	22
3	Bortezomib Induces Anti–Multiple Myeloma Immune Response Mediated by cGAS/STING Pathway Activation	Blood Cancer Discovery	Annamaria Gullà, Eugenio Morelli et al.	92
4	ROBO1 Promotes Homing, Dissemination, and Survival of Multiple Myeloma within the Bone Marrow Microenvironment	Blood Cancer Discovery	Giada Bianchi, Peter G. Czarnecki et al.	12
5	Polycomb-like Protein 3 Induces Proliferation and Drug Resistance in Multiple Myeloma and Is Regulated by miRNA-15a	Molecular Cancer Research	Tengteng Yu, Xiaoke Ma et al.	21
6	Preclinical evaluation of CD8+ anti-BCMA mRNA CAR T cells for treatment of multiple myeloma	Leukemia	Liang Lin, Shih‐Feng Cho et al.	64
7	Progression signature underlies clonal evolution and dissemination of multiple myeloma	Blood	Yu J. Shen, Yuji Mishima et al.	32
8	Rational design of a trimeric APRIL-based CAR-binding domain enables efficient targeting of multiple myeloma	Blood Advances	Andrea Schmidts, Maria Ormhøj et al.	85
9	Antibody-Dependent Cellular Phagocytosis by Macrophages is a Novel Mechanism of Action of Elotuzumab	Molecular Cancer Therapeutics	Ahmed T. Kurdi, Siobhan Glavey et al.	70
10	SLC46A3 as a Potential Predictive Biomarker for Antibody–Drug Conjugates Bearing Noncleavable Linked Maytansinoid and Pyrrolobenzodiazepine Warheads	Clinical Cancer Research	Krista Kinneer, John Meekin et al.	58
11	Ribonucleotide Reductase Catalytic Subunit M1 (RRM1) as a Novel Therapeutic Target in Multiple Myeloma	Clinical Cancer Research	M. Sagawa, Hiroto Ohguchi et al.	30
12	Blocking HDAC3 in Bone Marrow Stromal Cells Has Direct Anti-Multiple Myeloma Effect and Modulates T Cell Function	Blood	Matthew Ho, Jiye Liu et al.	2
13	Bone Marrow Microenvironment Induces Genomic Instability and Enables Clonal Evolution in Multiple Myeloma	Blood	Tommaso Perini, Raphaël Szalat et al.	1
14	Synthetic Lethal Approaches Exploiting DNA Damage in Aggressive Myeloma	Cancer Discovery	Francesca Cottini, Teru Hideshima et al.	87
15	Targeting the miR-221–222/PUMA/BAK/BAX Pathway Abrogates Dexamethasone Resistance in Multiple Myeloma	Cancer Research	Jianjun Zhao, Yiguo Hu et al.	72
16	miR-30-5p Functions as a Tumor Suppressor and Novel Therapeutic Tool by Targeting the Oncogenic Wnt/β-Catenin/BCL9 Pathway	Cancer Research	Jianjun Zhao, Jianhong Lin et al.	159
17	Selective and Potent Akt Inhibition Triggers Anti-Myeloma Activities and Enhances Fatal Endoplasmic Reticulum Stress Induced by Proteasome Inhibition	Cancer Research	Naoya Mimura, Teru Hideshima et al.	66
18	Dual Inhibition of Canonical and Noncanonical NF-κB Pathways Demonstrates Significant Antitumor Activities in Multiple Myeloma	Clinical Cancer Research	Claire Fabre, Naoya Mimura et al.	66
19	Targeting Angiogenesis via a c-Myc/Hypoxia-Inducible Factor-1α–Dependent Pathway in Multiple Myeloma	Cancer Research	Jing Zhang, Martin Sattler et al.	76
20	Up-Regulation of c-Jun Inhibits Proliferation and Induces Apoptosis via Caspase-Triggered c-Abl Cleavage in Human Multiple Myeloma	Cancer Research	Klaus Podar, Marc S. Raab et al.	55

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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