Ming Mai

1.8k total citations
21 papers, 1.1k citations indexed

About

Ming Mai is a scholar working on Molecular Biology, Oncology and Genetics. According to data from OpenAlex, Ming Mai has authored 21 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 8 papers in Oncology and 7 papers in Genetics. Recurrent topics in Ming Mai's work include Myeloproliferative Neoplasms: Diagnosis and Treatment (5 papers), Cancer-related Molecular Pathways (5 papers) and Acute Myeloid Leukemia Research (3 papers). Ming Mai is often cited by papers focused on Myeloproliferative Neoplasms: Diagnosis and Treatment (5 papers), Cancer-related Molecular Pathways (5 papers) and Acute Myeloid Leukemia Research (3 papers). Ming Mai collaborates with scholars based in United States, Canada and France. Ming Mai's co-authors include Jeremy C. Smith, Wanguo Liu, Akira Yokomizo, Chiping Qian, Rebecca F. McClure, Ayalew Tefferi, Animesh Pardanani, Terra L. Lasho, Christy M. Finke and David G. Bostwick and has published in prestigious journals such as Oncogene, The American Journal of Surgical Pathology and Journal of Clinical Pathology.

In The Last Decade

Ming Mai

21 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ming Mai United States 15 688 449 413 364 217 21 1.1k
HG Ahuja United States 12 409 0.6× 458 1.0× 313 0.8× 538 1.5× 46 0.2× 22 1.1k
TC Meeker United States 11 316 0.5× 405 0.9× 349 0.8× 193 0.5× 36 0.2× 16 1.2k
WM Roberts United States 12 367 0.5× 285 0.6× 112 0.3× 348 1.0× 31 0.1× 19 1.0k
S. M. Luger United States 8 407 0.6× 372 0.8× 141 0.3× 492 1.4× 25 0.1× 14 949
Shin Kan Japan 17 276 0.4× 392 0.9× 203 0.5× 161 0.4× 27 0.1× 32 808
KJ Bross Germany 7 146 0.2× 406 0.9× 133 0.3× 432 1.2× 27 0.1× 7 870
Erik Pong United States 16 433 0.6× 358 0.8× 97 0.2× 80 0.2× 33 0.2× 24 1.1k
Jerry Z. Gong United States 7 298 0.4× 648 1.4× 354 0.9× 83 0.2× 30 0.1× 8 1.0k
KC Anderson United States 9 258 0.4× 403 0.9× 334 0.8× 429 1.2× 29 0.1× 12 1.2k
SJ Szilvassy Australia 10 439 0.6× 389 0.9× 199 0.5× 664 1.8× 21 0.1× 12 1.1k

Countries citing papers authored by Ming Mai

Since Specialization
Citations

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

Fields of papers citing papers by Ming Mai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ming Mai

This figure shows the co-authorship network connecting the top 25 collaborators of Ming Mai. A scholar is included among the top collaborators of Ming Mai 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 Ming Mai. Ming Mai 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.
King, Rebecca L., Kerstin L. Edlefsen, Lisa Shane, et al.. (2020). Novel t(1;8)(p31.3;q21.3) NFIA-RUNX1T1 Translocation in an Infant Erythroblastic Sarcoma. American Journal of Clinical Pathology. 156(1). 129–138. 10 indexed citations
2.
3.
He, Rong, Wei Ding, David S. Viswanatha, et al.. (2018). PD-1 Expression in Chronic Lymphocytic Leukemia/Small Lymphocytic Lymphoma (CLL/SLL) and Large B-cell Richter Transformation (DLBCL-RT). The American Journal of Surgical Pathology. 42(7). 843–854. 51 indexed citations
4.
He, Rong, Patricia T. Greipp, Ming Mai, et al.. (2016). BCR–JAK2 fusion in a myeloproliferative neoplasm with associated eosinophilia. Cancer Genetics. 209(5). 223–228. 15 indexed citations
5.
McClure, Rebecca F., Ming Mai, & Scott T. McClure. (2014). High-Throughput Sequencing Using the Ion Torrent Personal Genome Machine for Clinical Evaluation of Somatic Hypermutation Status in Chronic Lymphocytic Leukemia. Journal of Molecular Diagnostics. 17(2). 145–154. 6 indexed citations
6.
Pardanani, Animesh, Terra L. Lasho, Christy M. Finke, et al.. (2010). IDH1 and IDH2 mutation analysis in chronic- and blast-phase myeloproliferative neoplasms. Leukemia. 24(6). 1146–1151. 139 indexed citations
7.
Tefferi, Ayalew, Terra L. Lasho, Omar Abdel‐Wahab, et al.. (2010). IDH1 and IDH2 mutation studies in 1473 patients with chronic-, fibrotic- or blast-phase essential thrombocythemia, polycythemia vera or myelofibrosis. Leukemia. 24(7). 1302–1309. 251 indexed citations
8.
McClure, Rebecca F., James D. Hoyer, & Ming Mai. (2006). TheJAK2V617F Mutation is Absent in Patients with Erythrocytosis Due to High Oxygen Affinity Hemoglobin Variants. Hemoglobin. 30(4). 487–489. 8 indexed citations
9.
Baudhuin, Linnea M., Ming Mai, Amy J. French, et al.. (2005). Analysis of hMLH1 and hMSH2 Gene Dosage Alterations in Hereditary Nonpolyposis Colorectal Cancer Patients by Novel Methods. Journal of Molecular Diagnostics. 7(2). 226–235. 21 indexed citations
10.
Mai, Ming, J. D. Hoyer, & Rebecca F. McClure. (2004). Use of multiple displacement amplification to amplify genomic DNA before sequencing of the α and β haemoglobin genes. Journal of Clinical Pathology. 57(6). 637–640. 21 indexed citations
11.
Dong, X., et al.. (2001). Genomic structure, chromosome mapping and expression analysis of the human AXIN2 gene. Cytogenetic and Genome Research. 93(1-2). 26–28. 31 indexed citations
12.
Mai, Ming, Akira Yokomizo, Chongsheng Qian, et al.. (2000). Differential expression and allelotyping of the p73 gene in neuroblastoma.. International Journal of Oncology. 16(1). 181–5. 14 indexed citations
13.
Mai, Ming, Chiping Qian, Akira Yokomizo, Jeremy C. Smith, & Wanguo Liu. (1999). Cloning of the Human Homolog of Conductin (AXIN2), a Gene Mapping to Chromosome 17q23–q24. Genomics. 55(3). 341–344. 60 indexed citations
14.
Lindor, Noralane M., Patrick C. Roche, Ming Mai, et al.. (1999). p73 mutations are not detected in sporadic and hereditary breast cancer. Breast Cancer Research and Treatment. 58(1). 25–29. 18 indexed citations
15.
Yokomizo, Akira, Ming Mai, Donald J. Tindall, et al.. (1999). Overexpression of the wild type p73 gene in human bladder cancer. Oncogene. 18(8). 1629–1633. 119 indexed citations
16.
Yokomizo, Akira, Ming Mai, David G. Bostwick, et al.. (1999). Mutation and expression analysis of thep73 gene in prostate cancer. The Prostate. 39(2). 94–100. 33 indexed citations
17.
Yokomizo, Akira, Ming Mai, David G. Bostwick, et al.. (1999). Mutation and expression analysis of the p73 gene in prostate cancer. The Prostate. 39(2). 94–100. 2 indexed citations
18.
Mai, Ming, Haojie Huang, Chris Reed, et al.. (1998). Genomic Organization and Mutation Analysis ofp73in Oligodendrogliomas with Chromosome 1 p-Arm Deletions. Genomics. 51(3). 359–363. 62 indexed citations
19.
Mai, Ming, Chiping Qian, Akira Yokomizo, et al.. (1998). Loss of imprinting and allele switching of p73 in renal cell carcinoma. Oncogene. 17(13). 1739–1741. 69 indexed citations
20.
Minamoto, Toshiko, Nami Yamashita, Atsushi Ochiai, et al.. (1996). Analysis of mutant K-ras in multiple sites of normal appearing mucosa of colorectal cancer patients. International Journal of Oncology. 9(5). 911–5. 4 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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