Adrian P. Wiegmans

4.2k total citations · 2 hit papers
30 papers, 3.2k citations indexed

About

Adrian P. Wiegmans is a scholar working on Molecular Biology, Oncology and Cancer Research. According to data from OpenAlex, Adrian P. Wiegmans has authored 30 papers receiving a total of 3.2k indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Molecular Biology, 19 papers in Oncology and 8 papers in Cancer Research. Recurrent topics in Adrian P. Wiegmans's work include Cancer Cells and Metastasis (8 papers), DNA Repair Mechanisms (7 papers) and PARP inhibition in cancer therapy (6 papers). Adrian P. Wiegmans is often cited by papers focused on Cancer Cells and Metastasis (8 papers), DNA Repair Mechanisms (7 papers) and PARP inhibition in cancer therapy (6 papers). Adrian P. Wiegmans collaborates with scholars based in Australia, United States and Germany. Adrian P. Wiegmans's co-authors include Andreas Möller, Richard J. Lobb, Shu Wen, Antoine Leimgruber, Christina S.F. Wong, Kum Kum Khanna, Leonie A. Cluse, Ricky W. Johnstone, Sunyoung Ham and Fares Al‐Ejeh and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Blood and PLoS ONE.

In The Last Decade

Adrian P. Wiegmans

30 papers receiving 3.2k citations

Hit Papers

Optimized exosome isolation protocol for cell cult... 2007 2026 2013 2019 2015 2007 400 800 1.2k

Peers

Adrian P. Wiegmans
Victoria Sanz‐Moreno United Kingdom
Mihai Gagea United States
Neethan A. Lobo United States
Koji Ueda Japan
Kimal Rajapakshe United States
Adrian P. Wiegmans
Citations per year, relative to Adrian P. Wiegmans Adrian P. Wiegmans (= 1×) peers Rasoul Salehi

Countries citing papers authored by Adrian P. Wiegmans

Since Specialization
Citations

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

Fields of papers citing papers by Adrian P. Wiegmans

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Adrian P. Wiegmans. 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 Adrian P. Wiegmans. The network helps show where Adrian P. Wiegmans may publish in the future.

Co-authorship network of co-authors of Adrian P. Wiegmans

This figure shows the co-authorship network connecting the top 25 collaborators of Adrian P. Wiegmans. A scholar is included among the top collaborators of Adrian P. Wiegmans 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 Adrian P. Wiegmans. Adrian P. Wiegmans 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
1.
Wiegmans, Adrian P., James Monkman, William Mullally, et al.. (2024). Poor patient outcome correlates with active engulfment of cytokeratin positive CTCs within cancer-associated monocyte population in lung cancer. Clinical & Experimental Metastasis. 41(3). 219–228. 3 indexed citations
2.
Parker, Amelia L., Madeleine Benguigui, Jaime Fornetti, et al.. (2022). Current challenges in metastasis research and future innovation for clinical translation. Clinical & Experimental Metastasis. 39(2). 263–277. 42 indexed citations
3.
Wiegmans, Adrian P., Pascal H. G. Duijf, Mark N. Adams, et al.. (2021). Genome instability and pressure on non-homologous end joining drives chemotherapy resistance via a DNA repair crisis switch in triple negative breast cancer. NAR Cancer. 3(2). zcab022–zcab022. 8 indexed citations
4.
Wiegmans, Adrian P., et al.. (2020). Circulating Tumor Cells in Metastatic Breast Cancer: From Genome Instability to Metastasis. Frontiers in Molecular Biosciences. 7. 134–134. 21 indexed citations
5.
Wiegmans, Adrian P., Jodi M. Saunus, Sunyoung Ham, et al.. (2019). Secreted cellular prion protein binds doxorubicin and correlates with anthracycline resistance in breast cancer. JCI Insight. 5. 22 indexed citations
6.
Ham, Sunyoung, Luize G. Lima, Alexandra Müller, et al.. (2018). Breast Cancer-Derived Exosomes Alter Macrophage Polarization via gp130/STAT3 Signaling. Frontiers in Immunology. 9. 871–871. 158 indexed citations
8.
Harris, Jonathan M., Kum Kum Khanna, Fares Al‐Ejeh, et al.. (2017). Quinazolinone derivatives as inhibitors of homologous recombinase RAD51. Bioorganic & Medicinal Chemistry Letters. 27(14). 3096–3100. 17 indexed citations
9.
Lim, Yi Chieh & Adrian P. Wiegmans. (2016). Tracking metastatic breast cancer: the future of biology in biosensors. Medical Oncology. 33(4). 36–36. 6 indexed citations
10.
Johnston, Rebecca L., Leesa Wockner, Amy E. McCart Reed, et al.. (2016). High content screening application for cell-type specific behaviour in heterogeneous primary breast epithelial subpopulations. Breast Cancer Research. 18(1). 18–18. 7 indexed citations
11.
Wiegmans, Adrian P., et al.. (2015). Differences in Expression of Key DNA Damage Repair Genes after Epigenetic-Induced BRCAness Dictate Synthetic Lethality with PARP1 Inhibition. Molecular Cancer Therapeutics. 14(10). 2321–2331. 39 indexed citations
12.
Tilch, Erik, Michael C. Quinn, Adrian P. Wiegmans, et al.. (2015). Using the MCF10A/MCF10CA1a Breast Cancer Progression Cell Line Model to Investigate the Effect of Active, Mutant Forms of EGFR in Breast Cancer Development and Treatment Using Gefitinib. PLoS ONE. 10(5). e0125232–e0125232. 24 indexed citations
13.
Zhang, Kai, et al.. (2015). Prion protein scrapie and the normal cellular prion protein. Prion. 10(1). 63–82. 37 indexed citations
14.
Khanna, Kum Kum, et al.. (2014). Targeting homologous recombination, new pre-clinical and clinical therapeutic combinations inhibiting RAD51. Cancer Treatment Reviews. 41(1). 35–45. 97 indexed citations
15.
Wiegmans, Adrian P., Amber E. Alsop, Michael Bots, et al.. (2011). Deciphering the Molecular Events Necessary for Synergistic Tumor Cell Apoptosis Mediated by the Histone Deacetylase Inhibitor Vorinostat and the BH3 Mimetic ABT-737. Cancer Research. 71(10). 3603–3615. 45 indexed citations
16.
Wiegmans, Adrian P., et al.. (2011). Potential roles for prions and protein-only inheritance in cancer. Cancer and Metastasis Reviews. 31(1-2). 1–19. 27 indexed citations
17.
Al‐Ejeh, Fares, Rajesh Kumar, Adrian P. Wiegmans, et al.. (2010). Harnessing the complexity of DNA-damage response pathways to improve cancer treatment outcomes. Oncogene. 29(46). 6085–6098. 115 indexed citations
18.
Whitecross, Kate F., Amber E. Alsop, Leonie A. Cluse, et al.. (2008). Defining the target specificity of ABT-737 and synergistic antitumor activities in combination with histone deacetylase inhibitors. Blood. 113(9). 1982–1991. 71 indexed citations
19.
Lindemann, Ralph K., Andrea Newbold, Kate F. Whitecross, et al.. (2007). Analysis of the apoptotic and therapeutic activities of histone deacetylase inhibitors by using a mouse model of B cell lymphoma. Proceedings of the National Academy of Sciences. 104(19). 8071–8076. 166 indexed citations
20.
Saleh, Mary, et al.. (2000). The treatment of established intracranial tumors by in situ retroviral IFN-γ transfer. Gene Therapy. 7(20). 1715–1724. 35 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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