Gerard Brady

3.8k citations
57 papers · 2.9k · h-index 29

Impact in

  • Hematology top 2%
    • Acute Myeloid Leukemia Research
    • Hematopoietic Stem Cell Transplantation
  • Immunology top 5%
    • Immune Cell Function and Interaction
    • T-cell and B-cell Immunology

Papers in

    • Molecular Biology Techniques and Applications 7
    • RNA Research and Splicing 6
    • CRISPR and Genetic Engineering 6
    • Virus-based gene therapy research 5

Gerard Brady

57 papers receiving 2.8k citations

Peers

Gerard Brady
Comparison fields: 5 of 99
  • Hematology 340
  • Immunology 548
  • Oncology 662
  • Molecular Biology 1.5k
  • Cancer Research 285
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Citations per field
00.5×1.6×
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Citations per year

Countries citing papers authored by Gerard Brady

Since Specialization
Citations

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

Fields of papers citing papers by Gerard Brady

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Gerard Brady, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Gerard Brady Line = papers co-authored together Gerard Brady links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 57 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2003374
2 1992302
3 1993228
4
Representative in Vitro cDNA Amplification From Individual Hemopoietic Cells and Colonies
1990160
5 1995147
6 1993128
7 1992120
8 1998107
9 199677
10 199975
11 200373
12 201369
13 200768
14 201865
15 200060
16 201957
17 200352
18 199749
19 198349
20
Coexpression of parathyroid hormone related protein and its receptor in early breast cancer predicts poor patient survival.
200249

About Gerard Brady

Gerard Brady is a scholar working on Molecular Biology, Genetics, Oncology, Cancer Research and Immunology, having authored 57 papers that have together received 2.9k indexed citations. Recurring topics across this work include Cancer Genomics and Diagnostics (11 papers), Molecular Biology Techniques and Applications (7 papers), RNA Research and Splicing (6 papers), CRISPR and Genetic Engineering (6 papers), Virus-based gene therapy research (5 papers), Immune Cell Function and Interaction (5 papers), T-cell and Retrovirus Studies (4 papers) and Cancer Cells and Metastasis (4 papers). The work is most often cited by research in Hematology (340 citations), Immunology (548 citations), Oncology (662 citations), Molecular Biology (1.5k citations) and Cancer Research (285 citations). Gerard Brady has collaborated with scholars based in United Kingdom, Canada and Germany. Frequent co-authors include Norman N. Iscove, Ana Cumano, Christopher J. Paige, Mary Barbara, Catherine Booth, Christopher S. Potten, Shin‐ichi Sakakibara, Robert B. Clarke, Gregory Tudor and D. Booth. Their work appears in journals such as Blood, Annals of Oncology, Yeast, The EMBO Journal and British Journal of Cancer.

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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