Mary McGrath

536 total citations
19 papers, 284 citations indexed

About

Mary McGrath is a scholar working on Hematology, Molecular Biology and Public Health, Environmental and Occupational Health. According to data from OpenAlex, Mary McGrath has authored 19 papers receiving a total of 284 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Hematology, 7 papers in Molecular Biology and 7 papers in Public Health, Environmental and Occupational Health. Recurrent topics in Mary McGrath's work include Chronic Myeloid Leukemia Treatments (7 papers), Acute Myeloid Leukemia Research (5 papers) and Acute Lymphoblastic Leukemia research (5 papers). Mary McGrath is often cited by papers focused on Chronic Myeloid Leukemia Treatments (7 papers), Acute Myeloid Leukemia Research (5 papers) and Acute Lymphoblastic Leukemia research (5 papers). Mary McGrath collaborates with scholars based in United States, China and France. Mary McGrath's co-authors include Chunhua Song, Zheng Ge, Qi Han, Jie Zi, Baoan Chen, Yan Gu, Fengchang Qiao, Jinlong Ma, Jiaojiao Hu and Siyu Gu and has published in prestigious journals such as Blood, Cancer Research and International Journal of Molecular Sciences.

In The Last Decade

Mary McGrath

17 papers receiving 283 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mary McGrath United States 10 183 110 53 36 34 19 284
Juliana M. Benito United States 5 125 0.7× 103 0.9× 70 1.3× 14 0.4× 50 1.5× 10 230
James B. Studd United Kingdom 7 256 1.4× 77 0.7× 36 0.7× 22 0.6× 92 2.7× 9 362
Manon Ouimet Canada 11 198 1.1× 127 1.2× 46 0.9× 16 0.4× 54 1.6× 16 309
Zhen Shang China 10 242 1.3× 91 0.8× 135 2.5× 29 0.8× 100 2.9× 35 390
M.D. Minden Canada 7 152 0.8× 87 0.8× 86 1.6× 29 0.8× 52 1.5× 16 289
E. L. Woodward Sweden 8 113 0.6× 33 0.3× 42 0.8× 20 0.6× 50 1.5× 14 225
Jaime M. Guidry Auvil United States 5 124 0.7× 85 0.8× 92 1.7× 16 0.4× 70 2.1× 12 257
Aliaksandra Maroz Germany 5 292 1.6× 205 1.9× 156 2.9× 16 0.4× 24 0.7× 7 438
Matthew D. Witkin United States 6 286 1.6× 43 0.4× 109 2.1× 20 0.6× 81 2.4× 8 365
Andrea Zangrando Italy 8 147 0.8× 46 0.4× 123 2.3× 24 0.7× 95 2.8× 9 303

Countries citing papers authored by Mary McGrath

Since Specialization
Citations

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

Fields of papers citing papers by Mary McGrath

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mary McGrath

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

All Works

19 of 19 papers shown
1.
Song, Chunhua, Pavan Kumar Dhanyamraju, Mary McGrath, et al.. (2021). Transcriptional Regulation of PIK3CD and PIKFYVE in T-Cell Acute Lymphoblastic Leukemia by IKAROS and Protein Kinase CK2. International Journal of Molecular Sciences. 22(2). 819–819. 8 indexed citations
2.
Weyand, Angela C., Kate D. Fitzgerald, Mary McGrath, et al.. (2021). Depression in Female Adolescents with Heavy Menstrual Bleeding. The Journal of Pediatrics. 240. 171–176. 21 indexed citations
3.
McGrath, Mary, et al.. (2021). Double and single mixed-lineage leukemia-rearranged subclones in pediatric acute myeloid leukemia: a case report. Journal of Medical Case Reports. 15(1). 228–228.
5.
Tong, Yongqing, Bei Liu, Hongyun Zheng, et al.. (2020). A novel G6PD deleterious variant identified in three families with severe glucose-6-phosphate dehydrogenase deficiency. BMC Medical Genetics. 21(1). 150–150. 9 indexed citations
6.
Qiao, Bin, Biheng Cheng, Yan Li, et al.. (2020). Two novel deleterious variants of Angiotensin‐I‐converting Enzyme gene identified in a family with recurrent anhydramnios. Molecular Genetics & Genomic Medicine. 8(6). e1239–e1239.
7.
Zi, Jie, Qi Han, Siyu Gu, et al.. (2020). Targeting NAT10 Induces Apoptosis Associated With Enhancing Endoplasmic Reticulum Stress in Acute Myeloid Leukemia Cells. Frontiers in Oncology. 10. 40 indexed citations
8.
Gowda, Chandrika, Chunhua Song, Yali Ding, et al.. (2019). Cellular signaling and epigenetic regulation of gene expression in leukemia. Advances in Biological Regulation. 75. 100665–100665. 17 indexed citations
9.
Yang, Dongqin, Qi Zhang, Yunfang Ma, et al.. (2019). Augmenting the therapeutic efficacy of adenosine against pancreatic cancer by switching the Akt/p21-dependent senescence to apoptosis. EBioMedicine. 47. 114–127. 24 indexed citations
10.
Peterson, Jess F., Beth A. Pitel, Stephanie A. Smoley, et al.. (2019). Detection of a cryptic NUP214/ABL1 gene fusion by mate-pair sequencing (MPseq) in a newly diagnosed case of pediatric T-lymphoblastic leukemia. Molecular Case Studies. 5(2). a003533–a003533. 7 indexed citations
11.
Zhang, Qi, Qi Han, Jie Zi, et al.. (2019). Mutations in EZH2 are associated with poor prognosis for patients with myeloid neoplasms. Genes & Diseases. 6(3). 276–281. 22 indexed citations
12.
Song, Chunhua, Zheng Ge, Chandrika Gowda, et al.. (2019). Abstract 286: Synergistic efficacy of CK2 inhibitor with common chemotherapy drugs by restoring Ikaros function in high-risk ALL. 286–286. 1 indexed citations
13.
Yang, Cheng, Yuan Song, Zhaowei Chen, et al.. (2019). A Nonsense Mutation in COL4A4 Gene Causing Isolated Hematuria in Either Heterozygous or Homozygous State. Frontiers in Genetics. 10. 628–628. 5 indexed citations
14.
Song, Chunhua, Chandrika Gowda, Yali Ding, et al.. (2019). Abstract 286: Synergistic efficacy of CK2 inhibitor with common chemotherapy drugs by restoring Ikaros function in high-risk ALL. Cancer Research. 79(13_Supplement). 286–286. 1 indexed citations
15.
Tong, Yongqing, Zhijun Zhao, Bei Liu, et al.. (2018). 5′/ 3′ imbalance strategy to detect ALK fusion genes in circulating tumor RNA from patients with non-small cell lung cancer. Journal of Experimental & Clinical Cancer Research. 37(1). 68–68. 27 indexed citations
16.
Liu, Bei, Jian Gu, Ying Xia, et al.. (2018). New rapid method to detect BCR-ABL fusion genes with multiplex RT-qPCR in one-tube at a time. Leukemia Research. 69. 47–53. 11 indexed citations
17.
Hu, Jiaojiao, Qi Han, Yan Gu, et al.. (2018). Circular RNA PVT1 Expression and its Roles in Acute Lymphoblastic Leukemia. Epigenomics. 10(6). 723–732. 70 indexed citations
18.
Gu, Yan, Qi Han, Mary McGrath, et al.. (2018). Clinical Significance of Novel SH2B3 Mutations in Adult Chinese Acute Lymphoblastic Leukemia Patients. Blood. 132(Supplement 1). 2657–2657. 1 indexed citations
19.
Liu, Fuchen, Wenli Zhang, Mary McGrath, et al.. (2018). Targeting CAND1 promotes caspase-8/RIP1-dependent apoptosis in liver cancer cells.. PubMed. 10(5). 1357–1372. 13 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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