Darl D. Flake
About
Darl D. Flake is a scholar working on Cancer Research, Oncology and Rheumatology.
According to data from OpenAlex, Darl D. Flake has authored 34 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Cancer Research, 11 papers in Oncology and 9 papers in Rheumatology. Recurrent topics in Darl D. Flake's work include Cancer Genomics and Diagnostics (11 papers), Rheumatoid Arthritis Research and Therapies (9 papers) and Cutaneous Melanoma Detection and Management (5 papers). Darl D. Flake is often cited by papers focused on Cancer Genomics and Diagnostics (11 papers), Rheumatoid Arthritis Research and Therapies (9 papers) and Cutaneous Melanoma Detection and Management (5 papers). Darl D. Flake collaborates with scholars based in United States, Germany and Denmark. Darl D. Flake's co-authors include Jerry S. Lanchbury, Alexander Gutin, Steven Stone, Susanne Wagner, Daniel M. Berney, Henrik Møller, Peter T. Scardino, Jack Cuzick, V. O. Speights and Gregory P. Swanson and has published in prestigious journals such as Journal of Clinical Oncology, PLoS ONE and Cancer.
In The Last Decade
Darl D. Flake
33 papers receiving 1.4k citations
Hit Papers
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late) cites · hero ref
| Name | h | Career | Trend | Papers | Cites | |||||
|---|---|---|---|---|---|---|---|---|---|---|
| Darl D. Flake United States | 14 | 592 | 580 | 514 | 464 | 238 | 34 | 1.4k | ||
| Christopher J. Lafargue United States | 16 | 640 1.1× | 947 1.6× | 825 1.6× | 567 1.2× | 131 0.6× | 30 | 1.8k | ||
| Zaida García‐Casado Spain | 20 | 482 0.8× | 782 1.3× | 229 0.4× | 427 0.9× | 187 0.8× | 79 | 1.3k | ||
| M Giai Italy | 18 | 460 0.8× | 474 0.8× | 219 0.4× | 268 0.6× | 262 1.1× | 33 | 1.2k | ||
| Marcin Krzystanek Denmark | 15 | 753 1.3× | 733 1.3× | 251 0.5× | 611 1.3× | 209 0.9× | 21 | 1.4k | ||
| Matthias Choschzick Germany | 24 | 480 0.8× | 396 0.7× | 242 0.5× | 250 0.5× | 104 0.4× | 51 | 1.4k | ||
| Stephanie M. McGregor United States | 18 | 345 0.6× | 490 0.8× | 374 0.7× | 245 0.5× | 46 0.2× | 52 | 1.3k | ||
| Paul J. van Diest Netherlands | 22 | 549 0.9× | 833 1.4× | 184 0.4× | 454 1.0× | 177 0.7× | 40 | 1.6k | ||
| Emanuele Palescandolo United States | 15 | 472 0.8× | 830 1.4× | 251 0.5× | 315 0.7× | 60 0.3× | 19 | 1.6k | ||
| Francine B. de Abreu United States | 16 | 352 0.6× | 338 0.6× | 256 0.5× | 372 0.8× | 65 0.3× | 36 | 906 | ||
| Weiwei Shi China | 19 | 631 1.1× | 430 0.7× | 263 0.5× | 457 1.0× | 154 0.6× | 75 | 1.3k |
Countries citing papers authored by Darl D. Flake
Since
Specialization
Citations
This map shows the geographic impact of Darl D. Flake'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 Darl D. Flake with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Darl D. Flake more than expected).
Fields of papers citing papers by Darl D. Flake
Since
Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences
This network shows the impact of papers produced by Darl D. Flake. 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 Darl D. Flake. The network helps show where Darl D. Flake may publish in the future.
Co-authorship network of co-authors of Darl D. Flake
This figure shows the co-authorship network connecting the top 25 collaborators of Darl D. Flake. A scholar is included among the top collaborators of Darl D. Flake 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 Darl D. Flake. Darl D. Flake is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
1.
Sasso, Eric H., Darl D. Flake, Rotem Ben‐Shachar, et al.. (2024). External validation of a multi-biomarker-based score for predicting risk of cardiovascular disease in patients with rheumatoid arthritis. PLoS ONE. 19(5). e0296459–e0296459.
2.
Papadopoulos, Nickolas, Anne Marie Lennon, Darl D. Flake, et al.. (2023). 202P Participant perceptions and mammography adherence from DETECT-A: The first prospective interventional trial of a multi-cancer early detection (MCED) blood test. Annals of Oncology. 34. S262–S263.
3.
Shore, Neal D., Darl D. Flake, Stephanie Meek, et al.. (2022). Hereditary cancer risk assessment in the community urology practice setting.. Journal of Clinical Oncology. 40(6_suppl). 278–278.
4.
Shore, Neal D., Elizabeth S. Cogan, Diana Iliev, et al.. (2022). Hereditary cancer risk assessment and genetic testing in the community urology practice setting. The Prostate. 82(7). 850–857.
5.
Tward, Jonathan D., Thorsten Schlomm, Daniel Canter, et al.. (2021). Personalizing Localized Prostate Cancer: Validation of a Combined Clinical Cell-cycle Risk (CCR) Score Threshold for Prognosticating Benefit From Multimodality Therapy. Clinical Genitourinary Cancer. 19(4). 296–304.e3.
6.
Curtis, Jeffrey R., Michael E. Weinblatt, Nancy A. Shadick, et al.. (2021). Validation of the adjusted multi-biomarker disease activity score as a prognostic test for radiographic progression in rheumatoid arthritis: a combined analysis of multiple studies. Arthritis Research & Therapy. 23(1). 1–1.
7.
Baker, Joshua F., Jeffrey R. Curtis, David Chernoff, et al.. (2020). Evaluation of the impact of age and adiposity on a multi-biomarker disease activity score before and after adjustment. Clinical Rheumatology. 40(6). 2419–2426.
8.
Soliman, Hatem, Susanne Wagner, Darl D. Flake, et al.. (2020). Evaluation of the 12-Gene Molecular Score and the 21-Gene Recurrence Score as Predictors of Response to Neo-adjuvant Chemotherapy in Estrogen Receptor-Positive, HER2-Negative Breast Cancer. Annals of Surgical Oncology. 27(3). 765–771.
9.
Morris, David, James S. Woods, Jennifer Logan, et al.. (2020). Prognostic capabilities and clinical utility of cell cycle progression testing, prostate imaging reporting and data system, version 2, and clinicopathologic data in management of localized prostate cancer. Urologic Oncology Seminars and Original Investigations. 39(6). 366.e19–366.e28.
10.
Curtis, Jeffrey R., Fenglong Xie, C. S. Crowson, et al.. (2020). FRI0553 DEVELOPMENT AND VALIDATION OF A BIOMARKER-BASED CARDIOVASCULAR RISK PREDICTION SCORE IN RHEUMATOID ARTHRITIS. Annals of the Rheumatic Diseases. 79. 878–879.
11.
Curtis, Jeffrey R., Cecilie Heegaard Brahe, Mikkel Østergaard, et al.. (2019). Predicting risk for radiographic damage in rheumatoid arthritis: comparative analysis of the multi-biomarker disease activity score and conventional measures of disease activity in multiple studies. Current Medical Research and Opinion. 35(9). 1483–1493.
12.
Chernoff, David, et al.. (2018). Determination of the minimally important difference (MID) in multi-biomarker disease activity (MBDA) test scores: impact of diurnal and daily biomarker variation patterns on MBDA scores. Clinical Rheumatology. 38(2). 437–445.
13.
Ko, Jennifer S., Loren E. Clarke, Eugen C. Minca, et al.. (2018). Correlation of melanoma gene expression score with clinical outcomes on a series of melanocytic lesions. Human Pathology. 86. 213–221.
14.
Curtis, Jeffrey R., Darl D. Flake, Michael E. Weinblatt, et al.. (2018). AB0244 Development of an adjusted multi-biomarker disease activity (MBDA) score for rheumatoid arthritis (RA) that accounts for age, sex and adiposity, with subsequent evaluation of ability to predict risk for radiographic damage. Annals of the Rheumatic Diseases. 77. 1304–1304.
15.
Ko, Jennifer S., Balwir Matharoo‐Ball, Steven D. Billings, et al.. (2017). Diagnostic Distinction of Malignant Melanoma and Benign Nevi by a Gene Expression Signature and Correlation to Clinical Outcomes. Cancer Epidemiology Biomarkers & Prevention. 26(7). 1107–1113.
16.
Keyser, Chad A., Éverton K. K. Fernandes, Drauzio E.N. Rangel, et al.. (2017). Laboratory bioassays and field-cage trials of Metarhizium spp. isolates with field-collected Mormon crickets (Anabrus simplex). BioControl. 62(2). 257–268.
17.
Clarke, Loren E., Darl D. Flake, Klaus J. Busam, et al.. (2016). An independent validation of a gene expression signature to differentiate malignant melanoma from benign melanocytic nevi. Cancer. 123(4). 617–628.
18.
Clarke, Loren E., M. Bryan Warf, Darl D. Flake, et al.. (2015). Clinical validation of a gene expression signature that differentiates benign nevi from malignant melanoma. Journal of Cutaneous Pathology. 42(4). 244–252.
19.
DeLoia, Julie A., Kirsten M. Timms, Kristin K. Zorn, et al.. (2012). BRCA1/2 mutations and expression: Response to platinum chemotherapy in patients with advanced stage epithelial ovarian cancer. Gynecologic Oncology. 125(3). 677–682.
20.
Cuzick, Jack, Gregory P. Swanson, Gabrielle Fisher, et al.. (2011). Prognostic value of an RNA expression signature derived from cell cycle proliferation genes in patients with prostate cancer: a retrospective study. The Lancet Oncology. 12(3). 245–255.
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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