Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Epithelial to Mesenchymal Transition Is a Determinant of Sensitivity of Non–Small-Cell Lung Carcinoma Cell Lines and Xenografts to Epidermal Growth Factor Receptor Inhibition
2005525 citationsStuart Thomson, Elizabeth Buck et al.Cancer Researchprofile →
Countries citing papers authored by Neil W. Gibson
Since
Specialization
Citations
This map shows the geographic impact of Neil W. Gibson'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 Neil W. Gibson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Neil W. Gibson more than expected).
This network shows the impact of papers produced by Neil W. Gibson. 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 Neil W. Gibson. The network helps show where Neil W. Gibson may publish in the future.
Co-authorship network of co-authors of Neil W. Gibson
This figure shows the co-authorship network connecting the top 25 collaborators of Neil W. Gibson.
A scholar is included among the top collaborators of Neil W. Gibson 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 Neil W. Gibson. Neil W. Gibson is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Chau, B. Nelson, et al.. (2013). Therapeutic modulation of microRNAs. Drug Discovery Today Therapeutic Strategies. 10(3). e127–e132.2 indexed citations
Buck, Elizabeth, Alexandra Eyzaguirre, Maryland Rosenfeld-Franklin, et al.. (2007). Inhibition of IGF-1R by OSI-906 potentiates efficacy of various molecular targeted agents by blocking feedback loops converging at the level of IRS-1. Molecular Cancer Therapeutics. 6.1 indexed citations
Ji, Qunsheng, Mark J. Mulvihill, Maryland Rosenfeld-Franklin, et al.. (2007). Preclinical characterization of OSI-906: A novel IGF-1R kinase inhibitor in clinical trials. Molecular Cancer Therapeutics. 6.4 indexed citations
10.
Lee, Chong-Soon, Gerd P. Pfeifer, & Neil W. Gibson. (1994). Mapping of DNA alkylation sites induced by aziridinylbenzoquinones in human cells by ligation-mediated polymerase chain reaction.. PubMed. 54(7). 1622–6.5 indexed citations
11.
Mulcahy, Ríona, et al.. (1994). Metabolism of bioreductive antitumor compounds by purified rat and human DT-diaphorases.. PubMed. 54(12). 3196–201.93 indexed citations
Gibson, Neil W., John A. Hartley, John M. Strong, & Kurt W. Kohn. (1986). 2-Chloroethyl (methylsulfonyl)methanesulfonate (NSC-338947), a more selective DNA alkylating agent than the chloroethylnitrosoureas.. PubMed. 46(2). 553–7.21 indexed citations
Gibson, Neil W., Leonard C. Erickson, & Kurt W. Kohn. (1985). DNA damage and differential cytotoxicity produced in human cells by 2-chloroethyl (methylsulfonyl)methanesulfonate (NSC 338947), a new DNA-chloroethylating agent.. PubMed. 45(4). 1674–9.16 indexed citations
20.
Gibson, Neil W., et al.. (1981). A comparative study of the anti-tumour activity of N-methylformamide and related compounds.. British Journal of Cancer. 44.1 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.