Brooke Middlebrook

734 total citations
16 papers, 451 citations indexed

About

Brooke Middlebrook is a scholar working on Molecular Biology, Oncology and Public Health, Environmental and Occupational Health. According to data from OpenAlex, Brooke Middlebrook has authored 16 papers receiving a total of 451 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Molecular Biology, 8 papers in Oncology and 3 papers in Public Health, Environmental and Occupational Health. Recurrent topics in Brooke Middlebrook's work include Cutaneous Melanoma Detection and Management (8 papers), Melanoma and MAPK Pathways (8 papers) and CAR-T cell therapy research (4 papers). Brooke Middlebrook is often cited by papers focused on Cutaneous Melanoma Detection and Management (8 papers), Melanoma and MAPK Pathways (8 papers) and CAR-T cell therapy research (4 papers). Brooke Middlebrook collaborates with scholars based in United States. Brooke Middlebrook's co-authors include Stephanie A. Pangas, Robert W. Cook, Michelle Myers, Martin M. Matzuk, Clare Johnson, Kristen M. Oelschlager, Derek Maetzold, Kyle R. Covington, Xiaohui Li and Karen W. Eldin and has published in prestigious journals such as Journal of Clinical Oncology, Blood and Endocrinology.

In The Last Decade

Brooke Middlebrook

14 papers receiving 436 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Brooke Middlebrook United States 11 276 229 110 71 68 16 451
Jane Humphreys United Kingdom 8 133 0.5× 213 0.9× 13 0.1× 127 1.8× 36 0.5× 10 402
Sarah J. Kurley United States 12 277 1.0× 322 1.4× 44 0.4× 61 0.9× 161 2.4× 25 514
Kristine Jacobson United States 8 339 1.2× 324 1.4× 59 0.5× 75 1.1× 33 0.5× 13 569
Nadja Kopp United States 9 388 1.4× 163 0.7× 57 0.5× 64 0.9× 18 0.3× 21 643
S. Donini Italy 8 138 0.5× 283 1.2× 27 0.2× 263 3.7× 26 0.4× 14 521
Marilyn Davis United States 12 133 0.5× 141 0.6× 71 0.6× 200 2.8× 24 0.4× 24 505
H Nishigaki Japan 16 148 0.5× 108 0.5× 77 0.7× 225 3.2× 18 0.3× 41 630
E D'Andrea Italy 12 148 0.5× 108 0.5× 28 0.3× 115 1.6× 36 0.5× 22 401
Fátima Vaz Portugal 7 114 0.4× 91 0.4× 38 0.3× 34 0.5× 12 0.2× 27 287
Norman G. Nagl United States 7 696 2.5× 133 0.6× 25 0.2× 88 1.2× 37 0.5× 7 744

Countries citing papers authored by Brooke Middlebrook

Since Specialization
Citations

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

Fields of papers citing papers by Brooke Middlebrook

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Brooke Middlebrook

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

All Works

16 of 16 papers shown
1.
Gastman, Brian, Jonathan S. Zager, Jane L. Messina, et al.. (2019). Performance of a 31‐gene expression profile test in cutaneous melanomas of the head and neck. Head & Neck. 41(4). 871–879. 13 indexed citations
2.
Cook, Robert W., Brooke Middlebrook, Jeff Wilkinson, et al.. (2018). Analytic validity of DecisionDx-Melanoma, a gene expression profile test for determining metastatic risk in melanoma patients. Diagnostic Pathology. 13(1). 13–13. 37 indexed citations
3.
Hsueh, Eddy C., James R. DeBloom, Jonathan Lee, et al.. (2017). Interim analysis of survival in a prospective, multi-center registry cohort of cutaneous melanoma tested with a prognostic 31-gene expression profile test. Journal of Hematology & Oncology. 10(1). 152–152. 66 indexed citations
4.
Ferris, Laura K., Aaron S. Farberg, Brooke Middlebrook, et al.. (2017). Identification of high-risk cutaneous melanoma tumors is improved when combining the online American Joint Committee on Cancer Individualized Melanoma Patient Outcome Prediction Tool with a 31-gene expression profile–based classification. Journal of the American Academy of Dermatology. 76(5). 818–825.e3. 41 indexed citations
5.
Fleming, Martin D., Brooke Middlebrook, Kyle R. Covington, et al.. (2017). Performance of a prognostic 31-gene expression profile test in stage III cutaneous melanoma subjects.. Journal of Clinical Oncology. 35(15_suppl). 9578–9578.
6.
Berger, Adam C., Robert S. Davidson, Indy Chabra, et al.. (2016). Clinical impact of a 31-gene expression profile test for cutaneous melanoma in 156 prospectively and consecutively tested patients. Current Medical Research and Opinion. 32(9). 1599–1604. 51 indexed citations
7.
Cook, Robert W., Tony Tsai, Yevgeniy Shildkrot, et al.. (2016). Clinical Performance and Management Outcomes with the DecisionDx-UM Gene Expression Profile Test in a Prospective Multicenter Study. Journal of Oncology. 2016. 1–9. 36 indexed citations
8.
Meldi, Kristen, Robert W. Cook, Tony Tsai, et al.. (2016). A prospective, multi-center study to evaluate the performance and clinical utility of a 15-gene expression profile for uveal melanoma.. Journal of Clinical Oncology. 34(15_suppl). 9575–9575. 1 indexed citations
9.
Zager, Jonathan S., Jane L. Messina, Vernon K. Sondak, et al.. (2016). Performance of a 31-gene expression profile in a previously unreported cohort of 334 cutaneous melanoma patients.. Journal of Clinical Oncology. 34(15_suppl). 9581–9581. 8 indexed citations
10.
Bhowmik, Debajyoti, Menaka Bhor, Brooke Middlebrook, et al.. (2015). The Effectiveness of Tyrosine Kinase Inhibitors and Molecular Monitoring Patterns in Newly Diagnosed Patients With Chronic Myeloid Leukemia in the Community Setting. Clinical Lymphoma Myeloma & Leukemia. 15(10). 599–605. 18 indexed citations
11.
Lawson, David H., Robert W. Cook, Clare Johnson, et al.. (2015). Continued evaluation of a 31-gene expression profile test (GEP) for prediction of distant metastasis (DM) in cutaneous melanoma (CM).. Journal of Clinical Oncology. 33(15_suppl). 9066–9066. 6 indexed citations
12.
13.
Myers, Michelle, Swamy K. Tripurani, Brooke Middlebrook, et al.. (2011). Loss of Gremlin Delays Primordial Follicle Assembly but Does Not Affect Female Fertility in Mice1. Biology of Reproduction. 85(6). 1175–1182. 27 indexed citations
14.
Nagaraja, Ankur K., Brooke Middlebrook, Saneal Rajanahally, et al.. (2010). Defective Gonadotropin-Dependent Ovarian Folliculogenesis and Granulosa Cell Gene Expression in Inhibin-Deficient Mice. Endocrinology. 151(10). 4994–5006. 24 indexed citations
15.
Myers, Michelle, Brooke Middlebrook, Martin M. Matzuk, & Stephanie A. Pangas. (2009). Loss of inhibin alpha uncouples oocyte-granulosa cell dynamics and disrupts postnatal folliculogenesis. Developmental Biology. 334(2). 458–467. 65 indexed citations
16.
Middlebrook, Brooke, et al.. (2009). Smad1-Smad5 Ovarian Conditional Knockout Mice Develop a Disease Profile Similar to the Juvenile Form of Human Granulosa Cell Tumors. Endocrinology. 150(12). 5208–5217. 58 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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