Gail L. Brown

605 total citations
41 papers, 469 citations indexed

About

Gail L. Brown is a scholar working on Molecular Biology, Oncology and Hematology. According to data from OpenAlex, Gail L. Brown has authored 41 papers receiving a total of 469 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 13 papers in Oncology and 11 papers in Hematology. Recurrent topics in Gail L. Brown's work include Glutathione Transferases and Polymorphisms (14 papers), Myeloproliferative Neoplasms: Diagnosis and Treatment (9 papers) and Acute Myeloid Leukemia Research (8 papers). Gail L. Brown is often cited by papers focused on Glutathione Transferases and Polymorphisms (14 papers), Myeloproliferative Neoplasms: Diagnosis and Treatment (9 papers) and Acute Myeloid Leukemia Research (8 papers). Gail L. Brown collaborates with scholars based in United States, Australia and United Kingdom. Gail L. Brown's co-authors include James Keck, Azra Raza, Naomi Galili, Marsha Jones, Lisa Meng, Donna Greenberg, Scott E. Smith, Ralph V. Boccia, Alan F. List and John E. Godwin and has published in prestigious journals such as Journal of Clinical Oncology, Blood and Cancer.

In The Last Decade

Gail L. Brown

41 papers receiving 454 citations

Peers

Gail L. Brown
Comparison fields: 5 of 62
  • Molecular Biology 256
  • Hematology 118
  • Reproductive Medicine 74
  • Oncology 71
  • Genetics 68
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Minjia Sheng China
Usawadee Dier United States
Lidija K. Gorsic United States
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Xiaojing Lin China
Adina Aviram Israel
R. C. Horns United States
Jelena Brkić Canada
Jamsheed Javid Saudi Arabia
Katrien Swerts Belgium
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Citations per field, relative to Gail L. Brown
Gail L. Brown · 1×
Citations per year, relative to Gail L. Brown
Gail L. Brown · 1×

Countries citing papers authored by Gail L. Brown

Since Specialization
Citations

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

Fields of papers citing papers by Gail L. Brown

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gail L. Brown. 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 Gail L. Brown. The network helps show where Gail L. Brown may publish in the future.

Co-authorship network of co-authors of Gail L. Brown

This figure shows the co-authorship network connecting the top 25 collaborators of Gail L. Brown. A scholar is included among the top collaborators of Gail L. Brown 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 Gail L. Brown. Gail L. Brown 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
# Work Indexed citations
1 1
2 3
3 1
4 20
5 18
6 18
7 36
8 47
9 21
10 2
11 18
12 49
13 19
14 2
15
Synergistic effect of TELCYTA™ (TLK286) in combination with paclitaxel, doxorubicin, carboplatin, oxaliplatin, cisplatin, docetaxel, gemcitabine and iressa in human cancer cells.
7
16 26
17
TLK286-induced activation of the stress response apoptotic signaling pathway
6
18
Phase 1 dose optimization study for V-echinocandin
5
19 11
20 10

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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