Yanming Zhang

6.3k total citations
148 papers, 2.0k citations indexed

About

Yanming Zhang is a scholar working on Hematology, Molecular Biology and Genetics. According to data from OpenAlex, Yanming Zhang has authored 148 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 67 papers in Hematology, 31 papers in Molecular Biology and 28 papers in Genetics. Recurrent topics in Yanming Zhang's work include Acute Myeloid Leukemia Research (45 papers), Hematopoietic Stem Cell Transplantation (15 papers) and Lymphoma Diagnosis and Treatment (13 papers). Yanming Zhang is often cited by papers focused on Acute Myeloid Leukemia Research (45 papers), Hematopoietic Stem Cell Transplantation (15 papers) and Lymphoma Diagnosis and Treatment (13 papers). Yanming Zhang collaborates with scholars based in United States, China and Germany. Yanming Zhang's co-authors include Janet D. Rowley, John Finn, Douglas R. Dougan, Leslie W. Tari, David J. Hosfield, Ronald V. Swanson, Jun Gu, Nengming Xiao, Ryma Benayed and Depei Wu and has published in prestigious journals such as Nucleic Acids Research, Journal of Biological Chemistry and Nature Communications.

In The Last Decade

Yanming Zhang

134 papers receiving 2.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yanming Zhang United States 23 932 571 494 280 268 148 2.0k
Masahide Yamamoto Japan 24 634 0.7× 375 0.7× 322 0.7× 247 0.9× 170 0.6× 103 1.8k
Lei Gao China 25 711 0.8× 986 1.7× 667 1.4× 133 0.5× 211 0.8× 170 2.4k
Hajime Okita Japan 25 1.2k 1.3× 349 0.6× 174 0.4× 550 2.0× 176 0.7× 124 2.2k
Yubin Kang United States 24 748 0.8× 614 1.1× 457 0.9× 269 1.0× 199 0.7× 97 1.9k
Changgeng Ruan China 32 856 0.9× 375 0.7× 1.6k 3.1× 267 1.0× 226 0.8× 202 3.1k
Makoto Hamasaki Japan 31 982 1.1× 628 1.1× 287 0.6× 976 3.5× 289 1.1× 120 2.7k
Tushar D. Bhagat United States 24 1.5k 1.6× 452 0.8× 410 0.8× 158 0.6× 117 0.4× 55 2.4k
Michael Steurer Austria 27 885 0.9× 745 1.3× 615 1.2× 188 0.7× 323 1.2× 103 2.7k
Jian Bo China 18 803 0.9× 762 1.3× 202 0.4× 254 0.9× 111 0.4× 65 2.4k

Countries citing papers authored by Yanming Zhang

Since Specialization
Citations

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

Fields of papers citing papers by Yanming Zhang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yanming Zhang

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

All Works

20 of 20 papers shown
1.
Zhang, Yanming, et al.. (2025). Association of Ticagrelor Metabolic SNPs With Adverse Drug Reactions in Patients With Acute Coronary Syndrome. Clinical Cardiology. 48(12). e70232–e70232.
2.
3.
Agaram, Narasimhan P., Konstantinos Linos, Carol D. Morris, et al.. (2025). 31 SNP Array Analysis of Synovial Chondromatosis with Atypical Features. Laboratory Investigation. 105(3). 102254–102254.
4.
Dehner, Carina, George Jour, Yanming Zhang, et al.. (2025). Beyond Hybrid Morphology: A Large Series of Fusion-Driven Benign Peripheral Nerve Sheath Tumors Including 5 Tumors With Novel Fusions. Modern Pathology. 38(10). 100806–100806. 1 indexed citations
5.
Zhang, Yanming, et al.. (2025). Supply chain digitalization and transparency: the privacy calculus perspective. Industrial Management & Data Systems. 1–26.
6.
Dermawan, Josephine K., Yanming Zhang, Chad Vanderbilt, et al.. (2024). Detection of GRM1 gene rearrangements in chondromyxoid fibroma: a comparison of fluorescence in‐situ hybridisation, RNA sequencing and immunohistochemical analysis. Histopathology. 85(6). 889–898. 3 indexed citations
7.
Shen, Sherry, Weining Ma, David N. Brown, et al.. (2023). HER2 Genetic Intratumor Heterogeneity Is Associated With Resistance to Trastuzumab and Trastuzumab Emtansine Therapy in Recurrent High-Grade Endometrial Cancer. Modern Pathology. 36(11). 100299–100299. 12 indexed citations
8.
9.
Wang, Xiangyu, et al.. (2023). Tandem bispecific CD123/CLL‐1 CAR‐T cells exhibit specific cytolytic effector functions against human acute myeloid leukaemia. European Journal Of Haematology. 112(1). 83–93. 15 indexed citations
10.
Epstein‐Peterson, Zachary D., Andriy Derkach, Susan M. Geyer, et al.. (2022). Effect of additional cytogenetic abnormalities on survival in arsenic trioxide-treated acute promyelocytic leukemia. Blood Advances. 6(11). 3433–3439. 7 indexed citations
11.
Ganzel, Chezi, Zhuoxin Sun, Timour Baslan, et al.. (2022). Measurable residual disease by flow cytometry in acute myeloid leukemia is prognostic, independent of genomic profiling. Leukemia Research. 123. 106971–106971. 5 indexed citations
12.
Baslan, Timour, Sam Kovaka, Fritz J. Sedlazeck, et al.. (2021). High resolution copy number inference in cancer using short-molecule nanopore sequencing. Nucleic Acids Research. 49(21). e124–e124. 13 indexed citations
13.
Mohanty, Abhinita, Edward A. Athanasian, John H. Healey, et al.. (2021). Recurrent loss of chromosome 22 and SMARCB1 deletion in extra‐axial chordoma: A clinicopathological and molecular analysis. Genes Chromosomes and Cancer. 60(12). 796–807. 13 indexed citations
14.
Yang, Soo‐Ryum, Umut Aypar, Ezra Y. Rosen, et al.. (2020). A Performance Comparison of Commonly Used Assays to Detect RET Fusions. Clinical Cancer Research. 27(5). 1316–1328. 50 indexed citations
15.
Yellapantula, Venkata D., Malin Hultcrantz, Even H. Rustad, et al.. (2020). Correction: Comprehensive detection of recurring genomic abnormalities: a targeted sequencing approach for multiple myeloma. Blood Cancer Journal. 10(1). 1 indexed citations
16.
Xiao, Wenbin, Linde A. Miles, Robert L. Bowman, et al.. (2020). A JAK2/IDH1-mutant MPN clone unmasked by ivosidenib in an AML patient without antecedent MPN. Blood Advances. 4(23). 6034–6038. 2 indexed citations
17.
Yellapantula, Venkata D., Malin Hultcrantz, Even H. Rustad, et al.. (2019). Comprehensive detection of recurring genomic abnormalities: a targeted sequencing approach for multiple myeloma. Blood Cancer Journal. 9(12). 101–101. 35 indexed citations
19.
Xiao, Wenbin, Mariko Yabe, Michael Offin, et al.. (2018). Evolution of a chemosensitive core-binding factor AML into an aggressive leukemia with eosinophilic differentiation. Blood Advances. 2(13). 1517–1521. 2 indexed citations
20.
Diolaiti, Daniel, Filemon S. Dela Cruz, Gunes Gundem, et al.. (2018). A recurrent novel MGA–NUTM1 fusion identifies a new subtype of high-grade spindle cell sarcoma. Molecular Case Studies. 4(6). a003194–a003194. 39 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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