Min Fang

7.8k total citations · 1 hit paper
182 papers, 4.7k citations indexed

About

Min Fang is a scholar working on Molecular Biology, Hematology and Oncology. According to data from OpenAlex, Min Fang has authored 182 papers receiving a total of 4.7k indexed citations (citations by other indexed papers that have themselves been cited), including 64 papers in Molecular Biology, 51 papers in Hematology and 22 papers in Oncology. Recurrent topics in Min Fang's work include Acute Myeloid Leukemia Research (41 papers), Chronic Myeloid Leukemia Treatments (16 papers) and Acute Lymphoblastic Leukemia research (16 papers). Min Fang is often cited by papers focused on Acute Myeloid Leukemia Research (41 papers), Chronic Myeloid Leukemia Treatments (16 papers) and Acute Lymphoblastic Leukemia research (16 papers). Min Fang collaborates with scholars based in United States, China and United Kingdom. Min Fang's co-authors include Vytas A. Bankaitis, Frederick R. Appelbaum, Elihu H. Estey, Barry E. Storer, Marcos Rivas, Megan Othus, Brent L. Wood, Brenda M. Sandmaier, Zhigang Xie and David Wu and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Clinical Oncology and The Journal of Cell Biology.

In The Last Decade

Min Fang

172 papers receiving 4.6k citations

Hit Papers

Acquisition of a CD19-negative myeloid phenotype allows i... 2016 2026 2019 2022 2016 100 200 300 400 500
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.

  1. Acquisition of a CD19-negative myeloid phenotype allows immune escape of MLL-rearranged B-ALL from CD19 CAR-T-cell therapy
    2016 544 citations Min Fang et al. Blood profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Min Fang United States 34 1.8k 1.7k 848 837 658 182 4.7k
Rolf Marschalek Germany 40 3.3k 1.8× 2.0k 1.2× 569 0.7× 1.4k 1.6× 257 0.4× 225 5.4k
Hideki Muramatsu Japan 38 2.5k 1.4× 1.6k 1.0× 1.0k 1.2× 362 0.4× 1.2k 1.8× 274 5.9k
Martin A. Horstmann Germany 31 2.2k 1.2× 1.6k 0.9× 914 1.1× 1.7k 2.1× 1.3k 2.0× 90 4.9k
Christian Brandts Germany 34 2.5k 1.3× 1.6k 0.9× 891 1.1× 566 0.7× 334 0.5× 110 5.0k
Jean‐Pierre Bourquin Switzerland 34 2.0k 1.1× 1.3k 0.8× 889 1.0× 1.1k 1.4× 126 0.2× 129 3.9k
Grover C. Bagby United States 46 2.7k 1.5× 1.7k 1.0× 870 1.0× 379 0.5× 295 0.4× 130 5.6k
K Kita Japan 31 1.8k 1.0× 1.2k 0.7× 464 0.5× 657 0.8× 182 0.3× 155 3.3k
Seiji Fukuda Japan 41 2.2k 1.2× 851 0.5× 840 1.0× 197 0.2× 372 0.6× 197 5.1k
Adam S. Asch United States 31 1.7k 0.9× 991 0.6× 1.3k 1.5× 389 0.5× 279 0.4× 98 4.6k
Hélène Cavé France 42 2.2k 1.2× 2.4k 1.4× 718 0.8× 2.0k 2.4× 117 0.2× 154 6.3k

Countries citing papers authored by Min Fang

Since Specialization
Citations

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

Fields of papers citing papers by Min Fang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Min Fang

This figure shows the co-authorship network connecting the top 25 collaborators of Min Fang. A scholar is included among the top collaborators of Min Fang 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 Min Fang. Min Fang 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
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Fang, Min, Hayley Lavender, Angela Thistlethwaite, et al.. (2024). Tackling immunosuppression by Neisseria gonorrhoeae to facilitate vaccine design. PLoS Pathogens. 20(11). e1012688–e1012688. 3 indexed citations
4.
Fromm, Jonathan R., Min Fang, Brian G. Till, et al.. (2023). Long-term efficacy and safety of pembrolizumab with R-CHOP as first-line therapy for DLBCL.. Journal of Clinical Oncology. 41(16_suppl). 7561–7561. 1 indexed citations
5.
Cassaday, Ryan D., Olga Sala‐Torra, Philip A. Stevenson, et al.. (2023). Phase II study of dose-adjusted EPOCH as initial therapy for adults with high-risk acute lymphoblastic leukemia. Leukemia & lymphoma. 64(5). 927–937. 4 indexed citations
6.
Zeng, Hao‐Long, Min Fang, Xin Liu, et al.. (2023). Hepatoprotective Effects of Rosmarinic Acid on Ovalbumin-Induced Intestinal Food Allergy Mouse Model. Molecules. 28(2). 788–788. 11 indexed citations
7.
Liu, Fang, Qing-qin Yin, Tingting Jiang, et al.. (2023). Exploration of Lipid Metabolism Alterations in Children with Active Tuberculosis Using UHPLC-MS/MS. Journal of Immunology Research. 2023. 1–11. 3 indexed citations
8.
Lu, Ping, Min Fang, Lei Yao, et al.. (2022). Massage of Bladder Meridian Relieved Anxiety Induced by Chronic Stress in Rats. BioMed Research International. 2022(1). 5639716–5639716. 2 indexed citations
9.
Zhang, Yingying, Di Lan, Shi-Bing Liang, et al.. (2021). Non-traditional Acupuncture Therapies for Smoking Cessation: A Systematic Review of Randomized Controlled Trials. Research Square. 1 indexed citations
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Fang, Min, David Pépin, Patricia K. Donahoe, et al.. (2018). Quantification of Müllerian Inhibiting Substance/Anti-Müllerian Hormone polypeptide by isotope dilution mass spectrometry. Analytical Biochemistry. 560. 50–55. 4 indexed citations
12.
Pogosova‐Agadjanyan, Era L., Anna Moseley, Megan Othus, et al.. (2017). Impact of Specimen Heterogeneity on Biomarkers in Repository Samples from Patients with Acute Myeloid Leukemia: A SWOG Report. Biopreservation and Biobanking. 16(1). 42–52. 6 indexed citations
13.
Fang, Min, et al.. (2017). Robust Parsing and Automated ELN Risk Classification for Acute Myeloid Leukemia. Blood. 130. 3947–3947. 1 indexed citations
14.
Bianchi‐Frias, Daniella, Ryan Basom, Jeffrey J. Delrow, et al.. (2016). Cells Comprising the Prostate Cancer Microenvironment Lack Recurrent Clonal Somatic Genomic Aberrations. Molecular Cancer Research. 14(4). 374–384. 29 indexed citations
15.
Davison, Jerry, Xiaoyu Qu, Colm Morrissey, et al.. (2016). Methylation profiling identified novel differentially methylated markers including OPCML and FLRT2 in prostate cancer. Epigenetics. 11(4). 247–258. 36 indexed citations
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Qu, Xiaoyu, Jerry Davison, Liping Du, et al.. (2015). Identification of differentially methylated markers among cytogenetic risk groups of acute myeloid leukemia. Epigenetics. 10(6). 526–535. 20 indexed citations
18.
Yeung, Cecilia C.S., Aaron T. Gerds, Min Fang, et al.. (2015). Relapse after Allogeneic Hematopoietic Cell Transplantation for Myelodysplastic Syndromes: Analysis of Late Relapse Using Comparative Karyotype and Chromosome Genome Array Testing. Biology of Blood and Marrow Transplantation. 21(9). 1565–1575. 16 indexed citations
19.
Schoenborn, Jamie, Colm Morrissey, Xia Jing, et al.. (2015). High-Resolution Genomic Profiling of Disseminated Tumor Cells in Prostate Cancer. Journal of Molecular Diagnostics. 18(1). 131–143. 7 indexed citations
20.
Feng, Yuan, et al.. (2007). Chromosome behaviors in two species of psyllids (Homoptera: Psylloidea). Entomotaxonomia. 119–124. 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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