Mark D. Minden

44.3k total citations · 8 hit papers
509 papers, 23.6k citations indexed

About

Mark D. Minden is a scholar working on Hematology, Molecular Biology and Oncology. According to data from OpenAlex, Mark D. Minden has authored 509 papers receiving a total of 23.6k indexed citations (citations by other indexed papers that have themselves been cited), including 301 papers in Hematology, 220 papers in Molecular Biology and 122 papers in Oncology. Recurrent topics in Mark D. Minden's work include Acute Myeloid Leukemia Research (244 papers), Chronic Myeloid Leukemia Treatments (89 papers) and Acute Lymphoblastic Leukemia research (85 papers). Mark D. Minden is often cited by papers focused on Acute Myeloid Leukemia Research (244 papers), Chronic Myeloid Leukemia Treatments (89 papers) and Acute Lymphoblastic Leukemia research (85 papers). Mark D. Minden collaborates with scholars based in Canada, United States and Germany. Mark D. Minden's co-authors include John E. Dick, Tsvee Lapidot, Barbara Murdoch, Christian Sirard, Josef Vormoor, Michael A. Caligiuri, Trang Hoang, Julio Roberto Cáceres‐Cortés, Bruce M. Paterson and Aaron D. Schimmer and has published in prestigious journals such as Nature, Science and New England Journal of Medicine.

In The Last Decade

Mark D. Minden

483 papers receiving 23.2k citations

Hit Papers

A cell initiating human acute myeloid leukaemia after tra... 1994 2026 2004 2015 1994 2001 2012 2011 2010 1000 2.0k 3.0k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mark D. Minden Canada 69 12.1k 8.3k 7.0k 4.0k 3.7k 509 23.6k
Giuseppe Basso Italy 73 10.1k 0.8× 6.8k 0.8× 4.4k 0.6× 3.7k 0.9× 2.9k 0.8× 536 24.1k
Edo Vellenga Netherlands 72 7.6k 0.6× 8.7k 1.0× 5.3k 0.8× 3.4k 0.8× 1.8k 0.5× 487 18.7k
Marina Konopleva United States 94 15.8k 1.3× 15.6k 1.9× 7.9k 1.1× 4.0k 1.0× 3.4k 0.9× 917 30.5k
Guido Marcucci United States 77 14.3k 1.2× 9.8k 1.2× 3.1k 0.4× 2.4k 0.6× 6.1k 1.6× 489 22.5k
Wolfgang E. Berdel Germany 71 11.3k 0.9× 7.3k 0.9× 5.1k 0.7× 1.9k 0.5× 4.3k 1.2× 502 21.3k
Andrew L. Kung United States 81 16.6k 1.4× 4.1k 0.5× 6.6k 0.9× 2.9k 0.7× 4.6k 1.2× 285 24.2k
Carsten Müller‐Tidow Germany 64 11.4k 0.9× 5.3k 0.6× 4.3k 0.6× 2.2k 0.5× 4.3k 1.2× 492 18.0k
Hubert Serve Germany 59 8.5k 0.7× 6.8k 0.8× 3.1k 0.4× 1.7k 0.4× 2.9k 0.8× 299 15.5k
Bob Löwenberg Netherlands 89 14.3k 1.2× 23.5k 2.8× 8.0k 1.1× 5.4k 1.3× 2.8k 0.8× 534 35.9k
Cheryl L. Willman United States 64 8.4k 0.7× 12.3k 1.5× 4.6k 0.6× 1.7k 0.4× 1.2k 0.3× 235 20.5k

Countries citing papers authored by Mark D. Minden

Since Specialization
Citations

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

Fields of papers citing papers by Mark D. Minden

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mark D. Minden. 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 Mark D. Minden. The network helps show where Mark D. Minden may publish in the future.

Co-authorship network of co-authors of Mark D. Minden

This figure shows the co-authorship network connecting the top 25 collaborators of Mark D. Minden. A scholar is included among the top collaborators of Mark D. Minden 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 Mark D. Minden. Mark D. Minden 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.
Culp‐Hill, Rachel, Andrea Arruda, Tracy Murphy, et al.. (2025). Plasma lipid levels predict chemotherapy response and survival in acute myeloid leukemia. Blood. 146(21). 2589–2596.
2.
Deshpande, Nandan, Shashank Sathe, Govardhan Anande, et al.. (2022). The splicing factor RBM17 drives leukemic stem cell maintenance by evading nonsense-mediated decay of pro-leukemic factors. Nature Communications. 13(1). 3833–3833. 15 indexed citations
3.
Walker, Alison R., John C. Byrd, James S. Blachly, et al.. (2020). Entospletinib in Combination with Induction Chemotherapy in Previously Untreated Acute Myeloid Leukemia: Response and Predictive Significance of HOXA9 and MEIS1 Expression. Clinical Cancer Research. 26(22). 5852–5859. 27 indexed citations
4.
Grandal, Ildiko, Daniele Merico, Careesa C. Liu, et al.. (2020). B cell acute lymphoblastic leukemia cells mediate RANK-RANKL–dependent bone destruction. Science Translational Medicine. 12(561). 20 indexed citations
5.
Ly, Michelle, Stefan Rentas, Nicholas Wong, et al.. (2019). Diminished AHR Signaling Drives Human Acute Myeloid Leukemia Stem Cell Maintenance. Cancer Research. 79(22). 5799–5811. 24 indexed citations
6.
Dzneladze, Irakli, John F. Woolley, Youqi Han, et al.. (2018). SubID, a non-median dichotomization tool for heterogeneous populations, reveals the pan-cancer significance of INPP4B and its regulation by EVI1 in AML. PLoS ONE. 13(2). e0191510–e0191510. 8 indexed citations
7.
Lee, Jong Bok, Mark D. Minden, Weihsu C. Chen, et al.. (2017). Allogeneic Human Double Negative T Cells as a Novel Immunotherapy for Acute Myeloid Leukemia and Its Underlying Mechanisms. Clinical Cancer Research. 24(2). 370–382. 80 indexed citations
8.
Roma, Alessia, Robert S. Stevens, Praveen P. N. Rao, et al.. (2017). Estrogen Receptor β Is a Novel Target in Acute Myeloid Leukemia. Molecular Cancer Therapeutics. 16(11). 2618–2626. 31 indexed citations
9.
Chen, Weihsu C., Julie S. Yuan, Yan Xing, et al.. (2016). An Integrated Analysis of Heterogeneous Drug Responses in Acute Myeloid Leukemia That Enables the Discovery of Predictive Biomarkers. Cancer Research. 76(5). 1214–1224. 15 indexed citations
10.
Yee, Karen, David W. Hedley, Sue Chow, et al.. (2016). A phase I trial of the aurora kinase inhibitor, ENMD-2076, in patients with relapsed or refractory acute myeloid leukemia or chronic myelomonocytic leukemia. Investigational New Drugs. 34(5). 614–624. 27 indexed citations
11.
Angka, Leonard, Andrew Mitchell, Rose Hurren, et al.. (2015). Targeting Mitochondria with Avocatin B Induces Selective Leukemia Cell Death. Cancer Research. 75(12). 2478–2488. 134 indexed citations
12.
Pandyra, Aleksandra A., Peter Mullen, Manpreet Kalkat, et al.. (2014). Immediate Utility of Two Approved Agents to Target Both the Metabolic Mevalonate Pathway and Its Restorative Feedback Loop. Cancer Research. 74(17). 4772–4782. 64 indexed citations
13.
Kantarjian, Hagop M., Xavier Thomas, Anna Dmoszyńska, et al.. (2012). Multicenter, Randomized, Open-Label, Phase III Trial of Decitabine Versus Patient Choice, With Physician Advice, of Either Supportive Care or Low-Dose Cytarabine for the Treatment of Older Patients With Newly Diagnosed Acute Myeloid Leukemia. Journal of Clinical Oncology. 30(21). 2670–2677. 818 indexed citations breakdown →
14.
Größ, Stefan, Rob A. Cairns, Mark D. Minden, et al.. (2010). Cancer-associated metabolite 2-hydroxyglutarate accumulates in acute myelogenous leukemia with isocitrate dehydrogenase 1 and 2 mutations. The Journal of Experimental Medicine. 207(2). 339–344. 558 indexed citations breakdown →
15.
Wood, Tabitha E., Shadi Dalili, Craig D. Simpson, et al.. (2010). Selective Inhibition of Histone Deacetylases Sensitizes Malignant Cells to Death Receptor Ligands. Molecular Cancer Therapeutics. 9(1). 246–256. 56 indexed citations
16.
Kornblau, Steven M., Mark D. Minden, David B. Rosen, et al.. (2010). Dynamic Single-Cell Network Profiles in Acute Myelogenous Leukemia Are Associated with Patient Response to Standard Induction Therapy. Clinical Cancer Research. 16(14). 3721–3733. 46 indexed citations
17.
Han, Youqi, Lin Yang, Fernando Suárez, et al.. (2008). Wilms' Tumor 1 Suppressor Gene Mediates Antiestrogen Resistance via Down-Regulation of Estrogen Receptor-α Expression in Breast Cancer Cells. Molecular Cancer Research. 6(8). 1347–1355. 24 indexed citations
18.
Bastianutto, Carlo, Asim Mian, Joseph D. Mocanu, et al.. (2007). Local Radiotherapy Induces Homing of Hematopoietic Stem Cells to the Irradiated Bone Marrow. Cancer Research. 67(21). 10112–10116. 29 indexed citations
19.
Yuan, Rui, Fatemeh Haghighi, Susan M. White, et al.. (2006). A Single Nucleotide Polymorphism Chip-Based Method for Combined Genetic and Epigenetic Profiling: Validation in Decitabine Therapy and Tumor/Normal Comparisons. Cancer Research. 66(7). 3443–3451. 46 indexed citations
20.
Wiljer, David, et al.. (2006). Getting results for hematology patients through access to the electronic health record. Canadian Oncology Nursing Journal. 16(3). 154–158. 21 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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