Sara A. Monaghan

761 total citations
32 papers, 527 citations indexed

About

Sara A. Monaghan is a scholar working on Hematology, Molecular Biology and Genetics. According to data from OpenAlex, Sara A. Monaghan has authored 32 papers receiving a total of 527 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Hematology, 11 papers in Molecular Biology and 11 papers in Genetics. Recurrent topics in Sara A. Monaghan's work include Acute Myeloid Leukemia Research (12 papers), Multiple Myeloma Research and Treatments (7 papers) and Myeloproliferative Neoplasms: Diagnosis and Treatment (6 papers). Sara A. Monaghan is often cited by papers focused on Acute Myeloid Leukemia Research (12 papers), Multiple Myeloma Research and Treatments (7 papers) and Myeloproliferative Neoplasms: Diagnosis and Treatment (6 papers). Sara A. Monaghan collaborates with scholars based in United States, Taiwan and Belgium. Sara A. Monaghan's co-authors include Vikas Bhushan, Robert W. McKenna, Monte S. Willis, M. L. Miller, Steven H. Kroft, Markus Y. Mapara, Suzanne Lentzsch, Peter Schäfer, Rekha Pal and Shirong Li and has published in prestigious journals such as Blood, The American Journal of Surgical Pathology and Leukemia.

In The Last Decade

Sara A. Monaghan

27 papers receiving 503 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sara A. Monaghan United States 9 223 185 139 100 95 32 527
Stephanie Roberts United Kingdom 9 146 0.7× 220 1.2× 94 0.7× 57 0.6× 105 1.1× 13 600
Kazuki Koizumi Japan 12 227 1.0× 224 1.2× 29 0.2× 136 1.4× 157 1.7× 29 671
Eugenia Prus Israel 16 495 2.2× 364 2.0× 139 1.0× 76 0.8× 527 5.5× 28 990
Richard Coffey United States 8 360 1.6× 116 0.6× 226 1.6× 23 0.2× 252 2.7× 12 657
Jiaying Zhang China 13 66 0.3× 359 1.9× 82 0.6× 126 1.3× 26 0.3× 45 844
MJ Summers United Kingdom 8 257 1.2× 95 0.5× 106 0.8× 47 0.5× 164 1.7× 11 453
Hana Manceau France 16 117 0.5× 557 3.0× 80 0.6× 56 0.6× 86 0.9× 29 932
Yating Zhang China 11 73 0.3× 166 0.9× 50 0.4× 163 1.6× 32 0.3× 30 569
Jie Bai China 15 252 1.1× 336 1.8× 25 0.2× 50 0.5× 161 1.7× 76 635
Gautam Rishi Australia 13 394 1.8× 85 0.5× 217 1.6× 26 0.3× 274 2.9× 22 574

Countries citing papers authored by Sara A. Monaghan

Since Specialization
Citations

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

Fields of papers citing papers by Sara A. Monaghan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sara A. Monaghan. 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 Sara A. Monaghan. The network helps show where Sara A. Monaghan may publish in the future.

Co-authorship network of co-authors of Sara A. Monaghan

This figure shows the co-authorship network connecting the top 25 collaborators of Sara A. Monaghan. A scholar is included among the top collaborators of Sara A. Monaghan 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 Sara A. Monaghan. Sara A. Monaghan 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.
Groves, Christopher J., Michael A. Linden, Ahmad Al‐Attar, et al.. (2025). Ad hoc antibody modification of a validated flow cytometric immunophenotyping panel—recommendations and safeguards for clinical laboratories. Cytometry Part B Clinical Cytometry. 110(1). 11–21.
2.
Monaghan, Sara A., Bryan Rea, Nidhi Aggarwal, et al.. (2025). Myeloid Neoplasms With Oligomonocytosis Exhibit Heterogenous Pathologic and Genetic Features. Modern Pathology. 38(10). 100823–100823. 1 indexed citations
3.
Wang, Yu‐Fen, Huanyu Chen, Joseph D. Tario, et al.. (2025). A machine learning framework for cross-institute standardized analysis of flow cytometry in differentiating acute myeloid leukemia from non-neoplastic conditions. Computers in Biology and Medicine. 193. 110394–110394.
4.
Al‐Attar, Ahmad, et al.. (2025). The Utility of TRBC1 Immunohistochemistry in the Evaluation of T-Cell Lymphomas. The American Journal of Surgical Pathology. 49(12). 1258–1265.
5.
Monaghan, Sara A., Steven Eck, Silvia T. Bunting, et al.. (2024). Flow cytometry assay modifications: Recommendations for method validation based on CLSI H62 guidelines. Cytometry Part B Clinical Cytometry. 108(3). 252–266. 3 indexed citations
6.
Bailey, Nathanael G., et al.. (2024). IRF8 Demonstrates Positivity in a Significant Subset of Histiocytic and Dendritic Cell Neoplasms. The American Journal of Surgical Pathology. 49(2). 98–103. 1 indexed citations
7.
Wang, Yu‐Fen, Joseph D. Tario, Sara A. Monaghan, et al.. (2023). Machine Learning-Facilitated Cross-Panel Automatic Classification at Both Sample and Cell Level in Acute Myeloid Leukemia. Blood. 142(Supplement 1). 5019–5019. 1 indexed citations
8.
Qi, Zhongxia, Sonam Prakash, Kwun Wah Wen, et al.. (2022). Distinct pathologic feature of myeloid neoplasm with t(v;11p15); NUP98 rearrangement. Human Pathology. 123. 11–19. 4 indexed citations
9.
Monaghan, Sara A., Yen‐Chun Liu, Michael Boyiadzis, et al.. (2021). A Machine Learning Approach to the Classification of Acute Leukemias and Distinction From Nonneoplastic Cytopenias Using Flow Cytometry Data. American Journal of Clinical Pathology. 157(4). 546–553. 26 indexed citations
10.
11.
12.
Monaghan, Sara A., et al.. (2017). Acute Myeloid Leukemia With a Rare t(7;14)(q21;q32) and Trisomy 4 With Poor Clinical Outcome: A Case Report. Laboratory Medicine. 48(4). 376–380.
13.
Monaghan, Sara A., Raymond E. Felgar, Melissa Kelly, et al.. (2016). Does Taking the Fellowship In-Service Hematopathology Examination and Performance Relate to Success on the American Board of Pathology Hematology Examination?. American Journal of Clinical Pathology. 146(1). 107–112. 6 indexed citations
14.
Xu, Xiangdong, Mu Su, Nicolas Lévy, et al.. (2014). Myeloid neoplasm with t(3;8)(q26;q24): report of six cases and review of the literature. Leukemia & lymphoma. 55(11). 2532–2537. 6 indexed citations
15.
Monaghan, Sara A., Urvashi Surti, Ketah Doty, & Fiona E. Craig. (2012). Altered neutrophil maturation patterns that limit identification of myelodysplastic syndromes. Cytometry Part B Clinical Cytometry. 82B(4). 217–228. 5 indexed citations
16.
Monaghan, Sara A., Lijun Dai, Markus Y. Mapara, et al.. (2012). Longitudinal bone marrow evaluations for myelodysplasia in patients with myeloma before and after treatment with lenalidomide. Leukemia & lymphoma. 54(9). 1965–1974. 5 indexed citations
17.
Monaco, Sara E., Sara A. Monaghan, Jason Stamm, et al.. (2011). Toxoplasmosis in a post‐transplant bronchoalveolar lavage: A case report. Diagnostic Cytopathology. 40(7). 629–634. 4 indexed citations
18.
Monaghan, Sara A., et al.. (2011). ZAP‐70 and Bcl‐2 expression in B lymphoblastic leukemia cells and hematogones. Cytometry Part B Clinical Cytometry. 82B(2). 85–92. 2 indexed citations
19.
Willis, Monte S., Sara A. Monaghan, M. L. Miller, et al.. (2005). Zinc-Induced Copper Deficiency. American Journal of Clinical Pathology. 123(1). 125–131. 186 indexed citations
20.
Monaghan, Sara A., et al.. (2003). Pan B‐cell markers are not redundant in analysis of chronic lymphocytic leukemia (CLL). Cytometry Part B Clinical Cytometry. 56B(1). 30–42. 28 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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