Daniel Van Dyke

1.4k total citations · 1 hit paper
17 papers, 848 citations indexed

About

Daniel Van Dyke is a scholar working on Genetics, Hematology and Molecular Biology. According to data from OpenAlex, Daniel Van Dyke has authored 17 papers receiving a total of 848 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Genetics, 7 papers in Hematology and 6 papers in Molecular Biology. Recurrent topics in Daniel Van Dyke's work include Chronic Lymphocytic Leukemia Research (5 papers), Myeloproliferative Neoplasms: Diagnosis and Treatment (5 papers) and Acute Myeloid Leukemia Research (4 papers). Daniel Van Dyke is often cited by papers focused on Chronic Lymphocytic Leukemia Research (5 papers), Myeloproliferative Neoplasms: Diagnosis and Treatment (5 papers) and Acute Myeloid Leukemia Research (4 papers). Daniel Van Dyke collaborates with scholars based in United States, France and Israel. Daniel Van Dyke's co-authors include Curtis A. Hanson, Ayalew Tefferi, Animesh Pardanani, Susan M. Schwager, Domenica Caramazza, Kebede H. Begna, Wenting Wu, Naseema Gangat, Rakhee Vaidya and Francisco Cervantes and has published in prestigious journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and Blood.

In The Last Decade

Daniel Van Dyke

16 papers receiving 840 citations

Hit Papers

DIPSS Plus: A Refined Dynamic International Prognostic Sc... 2010 2026 2015 2020 2010 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel Van Dyke United States 7 749 572 409 238 100 17 848
GB Faguet United States 8 388 0.5× 281 0.5× 129 0.3× 106 0.4× 58 0.6× 17 474
Ilyas Chachoua Belgium 9 619 0.8× 512 0.9× 471 1.2× 171 0.7× 10 0.1× 14 765
Ana Aventín Spain 11 148 0.2× 339 0.6× 350 0.9× 56 0.2× 49 0.5× 18 610
Sonja Schindela Germany 13 314 0.4× 620 1.1× 368 0.9× 34 0.1× 65 0.7× 25 830
Svetlana Krichevsky Israel 12 171 0.2× 229 0.4× 243 0.6× 82 0.3× 92 0.9× 25 480
Chiara Cavalloni Italy 8 466 0.6× 302 0.5× 314 0.8× 144 0.6× 62 0.6× 15 524
M. C. Martyré France 10 489 0.7× 507 0.9× 245 0.6× 169 0.7× 26 0.3× 14 648
Samuel B. Luty United States 9 313 0.4× 311 0.5× 193 0.5× 133 0.6× 15 0.1× 13 500
Claire Curtis United Kingdom 7 177 0.2× 138 0.2× 154 0.4× 217 0.9× 67 0.7× 9 475
Yoshitaka Sunami Japan 10 307 0.4× 263 0.5× 246 0.6× 70 0.3× 18 0.2× 18 449

Countries citing papers authored by Daniel Van Dyke

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Van Dyke

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel Van Dyke. 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 Daniel Van Dyke. The network helps show where Daniel Van Dyke may publish in the future.

Co-authorship network of co-authors of Daniel Van Dyke

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

All Works

17 of 17 papers shown
1.
Parikh, Sameer A., Kari G. Rabe, Neil E. Kay, et al.. (2021). The CLL International Prognostic Index predicts outcomes in monoclonal B-cell lymphocytosis and Rai 0 CLL. Blood. 138(2). 149–159. 23 indexed citations
2.
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
3.
Hammond, William A., Pooja Advani, Rhett P. Ketterling, et al.. (2018). Biphenotypic Acute Leukemia versus Myeloid Antigen-Positive ALL: Clinical Relevance of WHO Criteria for Mixed Phenotype Acute Leukemia. SHILAP Revista de lepidopterología. 2018. 1–4. 1 indexed citations
4.
Dias, Ajoy, Aref Al‐Kali, Daniel Van Dyke, et al.. (2017). Inversion 3 Cytogenetic Abnormality in an Allogeneic Hematopoietic Cell Transplant Recipient Representative of a Donor-Derived Constitutional Abnormality. Biology of Blood and Marrow Transplantation. 23(9). 1582–1587. 4 indexed citations
5.
Prior, Thomas W., Daynna J. Wolff, Daniel Van Dyke, & Cynthia M. Powell. (2016). ADDENDUM: Laboratory guideline for Turner syndrome. Genetics in Medicine. 18(1). 107–107. 2 indexed citations
6.
Prior, Thomas W., Daynna J. Wolff, Daniel Van Dyke, & Cynthia M. Powell. (2016). ADDENDUM: Technical standards and guidelines for myotonic dystrophy type 1 testing. Genetics in Medicine. 18(1). 107–107. 1 indexed citations
7.
Ojha, Juhi, Jackline de Paula Ayres-Silva, Charla Secreto, et al.. (2014). Deep sequencing identifies genetic heterogeneity and recurrent convergent evolution in chronic lymphocytic leukemia. Blood. 125(3). 492–498. 38 indexed citations
8.
Raza, Sania S., Ryan A. Knudson, Animesh Pardanani, et al.. (2012). Sole abnormalities of chromosome 7 in myeloid malignancies: Spectrum, histopathologic correlates, and prognostic implications. American Journal of Hematology. 87(7). 684–686. 21 indexed citations
9.
10.
Gangat, Naseema, Domenica Caramazza, Rakhee Vaidya, et al.. (2010). DIPSS Plus: A Refined Dynamic International Prognostic Scoring System for Primary Myelofibrosis That Incorporates Prognostic Information From Karyotype, Platelet Count, and Transfusion Status. Journal of Clinical Oncology. 29(4). 392–397. 657 indexed citations breakdown →
11.
Hussein, Kebede, Animesh Pardanani, Daniel Van Dyke, Curtis A. Hanson, & Ayalew Tefferi. (2009). IPSS-Independent Cytogenetic Risk Categorization in Primary Myelofibrosis.. Blood. 114(22). 2909–2909. 1 indexed citations
12.
Leis, José F., Esteban Braggio, Scott Van Wier, et al.. (2009). Impact of IgVH Gene Mutational Status and VH Family Usage on Chromosomal Aberrations Detected by High-Resolution Array-CGH in B-CLL.. Blood. 114(22). 1246–1246. 1 indexed citations
13.
Wu, Xiaosheng, Grzegorz S. Nowakowski, Stephanie A. Smoley, et al.. (2008). Cytogenetic Analysis of Normal Human B Cells Following CpG Stimulation: Implications for Interpretation of CpG Induced CLL Metaphase Analysis. Blood. 112(11). 3124–3124. 2 indexed citations
14.
Santana-Dávila, Rafael, C. Christopher Hook, Scott H. Kaufmann, et al.. (2007). Trisomy 13 in patients with hematological malignancies. Journal of Clinical Oncology. 25(18_suppl). 7055–7055.
15.
Vance, Gail H., et al.. (2001). Cytogenetic analysis and construction of a BAC contig across a common neocentromeric region from 9p. Chromosoma. 110(4). 275–283. 27 indexed citations
17.
Smith, Simon A., et al.. (1993). High throughput DNA sequencing using an automated electrophoresis analysis system and a novel sequence assembly program.. PubMed. 14(6). 1014–8. 6 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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