Yang Liang

3.1k total citations · 1 hit paper
69 papers, 1.7k citations indexed

About

Yang Liang is a scholar working on Hematology, Molecular Biology and Oncology. According to data from OpenAlex, Yang Liang has authored 69 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Hematology, 24 papers in Molecular Biology and 23 papers in Oncology. Recurrent topics in Yang Liang's work include Acute Myeloid Leukemia Research (21 papers), Multiple Myeloma Research and Treatments (12 papers) and Myeloproliferative Neoplasms: Diagnosis and Treatment (9 papers). Yang Liang is often cited by papers focused on Acute Myeloid Leukemia Research (21 papers), Multiple Myeloma Research and Treatments (12 papers) and Myeloproliferative Neoplasms: Diagnosis and Treatment (9 papers). Yang Liang collaborates with scholars based in China, United Kingdom and United States. Yang Liang's co-authors include Robert Peter Gale, Guang‐Biao Zhou, Ping Liu, Bingshun Wang, Jian‐Hua Mao, Chen Zhu, Fang Xu, Lan Wang, Sai-Juan Chen and Huan Li and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Blood and Cancer Research.

In The Last Decade

Yang Liang

60 papers receiving 1.7k citations

Hit Papers

Dissection of mechanisms of Chinese medicinal formula Rea... 2008 2026 2014 2020 2008 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yang Liang China 15 896 434 267 252 194 69 1.7k
Zhongren Ding China 18 386 0.4× 289 0.7× 138 0.5× 357 1.4× 59 0.3× 40 1.6k
Ruiming Rong China 28 884 1.0× 162 0.4× 231 0.9× 61 0.2× 35 0.2× 103 2.2k
Dahn L. Clemens United States 27 733 0.8× 174 0.4× 344 1.3× 50 0.2× 22 0.1× 73 2.4k
Xizhen Xu China 28 608 0.7× 36 0.1× 192 0.7× 387 1.5× 29 0.1× 62 2.3k
Toshikazu Hada Japan 27 885 1.0× 136 0.3× 199 0.7× 80 0.3× 13 0.1× 116 2.2k
Qingchun Zeng China 24 835 0.9× 76 0.2× 93 0.3× 47 0.2× 70 0.4× 113 2.0k
Roberto Guerciolini United States 20 970 1.1× 458 1.1× 461 1.7× 71 0.3× 13 0.1× 40 2.1k
Zengxiang Dong China 22 691 0.8× 115 0.3× 105 0.4× 63 0.3× 26 0.1× 67 1.5k
Aili Cao China 24 752 0.8× 235 0.5× 60 0.2× 46 0.2× 97 0.5× 76 2.1k
Wing K. Cheung United States 18 250 0.3× 434 1.0× 239 0.9× 40 0.2× 31 0.2× 43 1.4k

Countries citing papers authored by Yang Liang

Since Specialization
Citations

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

Fields of papers citing papers by Yang Liang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yang Liang

This figure shows the co-authorship network connecting the top 25 collaborators of Yang Liang. A scholar is included among the top collaborators of Yang Liang 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 Yang Liang. Yang Liang 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.
Xu, Weiling, Yiwen Bu, Min Zeng, et al.. (2025). Clinical Outcome of Extramedullary Multiple Myeloma in the Era of Novel Agents: Insights From a Multicenter Study. Hematological Oncology. 43(4). e70112–e70112.
2.
Wang, Yun, Shuzhao Chen, Shutong Liu, et al.. (2025). The bone marrow immune ecosystem shapes daratumumab acquired resistance in plasma cell myeloma. Leukemia. 39(10). 2504–2515.
3.
Chang, Chunkang, Takahiro Suzuki, Yang Liang, et al.. (2025). Safety and efficacy of luspatercept in treating anemia associated with myelodysplastic syndrome with ring sideroblasts in Asian patients who require red blood cell transfusions: a phase II bridging study. Therapeutic Advances in Hematology. 16. 1584239475–1584239475. 1 indexed citations
4.
Wang, Huafeng, Xudong Wei, Yang Liang, et al.. (2024). Lisaftoclax (APG-2575), a Novel BCL-2 Inhibitor, in Combination with Azacitidine in Treatment of Patients with Myelodysplastic Syndrome (MDS). Blood. 144(Supplement 1). 3202–3202.
5.
6.
Wang, Yun, et al.. (2024). Chronic myeloid leukaemia: Biology and therapy. Blood Reviews. 65. 101196–101196. 6 indexed citations
8.
Chen, Shuzhao, et al.. (2023). A tumor-associated endothelial signature score model in immunotherapy and prognosis across pan-cancers. Frontiers in Pharmacology. 14. 1190660–1190660. 4 indexed citations
9.
Ding, Kaiyang, Xiaoyong Wang, Chen Huang, et al.. (2023). Effectivness and Safety of Orelabrutinib in Chronic Lymphocytic Leukemia/Small Lymphocytic Lymphoma: A Retrospective, Real-World Study in China. Blood. 142(Supplement 1). 6552–6552.
10.
Zhang, Limei, Shuzhao Chen, Weida Wang, Yun Wang, & Yang Liang. (2023). Inflammatory and Nutritional Scoring System for Predicting Prognosis in Patients with Newly Diagnosed Multiple Myeloma. Journal of Inflammation Research. Volume 16. 7–17. 13 indexed citations
11.
Li, Jinyuan, Shuzhao Chen, Yang Li, et al.. (2022). Comprehensive Profiling Analysis of CD209 in Malignancies Reveals the Therapeutic Implication for Tumor Patients Infected With SARS-CoV-2. Frontiers in Genetics. 13. 883234–883234. 2 indexed citations
13.
Chen, Chongxiang, et al.. (2021). JAK-inhibitors for coronavirus disease-2019 (COVID-19): a meta-analysis. Leukemia. 35(9). 2616–2620. 64 indexed citations
14.
Chen, Chongxiang, et al.. (2021). Systematic review and meta-analysis of tocilizumab in persons with coronavirus disease-2019 (COVID-19). Leukemia. 35(6). 1661–1670. 12 indexed citations
15.
Shu, Lingling, Jinyuan Li, Shuzhao Chen, et al.. (2021). Bone Marrow Adipocyte Shapes Metabolism and Immunity in Tumor Microenvironment to Promote Multiple Myeloma. Blood. 138(Supplement 1). 892–892. 5 indexed citations
16.
Taylor, Justin, Xiaoli Mi, Khrystyna North, et al.. (2020). Single-cell genomics reveals the genetic and molecular bases for escape from mutational epistasis in myeloid neoplasms. Blood. 136(13). 1477–1486. 38 indexed citations
17.
Wang, Yun, et al.. (2020). Systematic Construction and Validation of a Metabolic Risk Model for Prognostic Prediction in Acute Myelogenous Leukemia. Frontiers in Oncology. 10. 540–540. 13 indexed citations
18.
Wang, Yun, et al.. (2019). The Role of the HOXA Gene Family in Acute Myeloid Leukemia. Genes. 10(8). 621–621. 50 indexed citations
19.
Li, Qing, Xiuyu Cai, Xiaoqin Chen, et al.. (2019). Long-term outcomes of modified BFM-95 regimen in adults with newly diagnosed standard-risk acute lymphoblastic leukemia: a retrospective single-center study. International Journal of Hematology. 110(4). 458–465. 1 indexed citations
20.
Li, Huimin, Long Yi, Qing Chen, et al.. (2011). Arsenic Trioxide Induces Apoptosis of Burkitt Lymphoma Cell Lines Through Multiple Apoptotic Pathways and Triggers Antiangiogenesis. Oncology Research Featuring Preclinical and Clinical Cancer Therapeutics. 19(3). 149–163. 14 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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