Ian Scanlon

714 citations
9 papers · 582 · h-index 8

Impact in

Papers in

    • Melanoma and MAPK Pathways 3
    • Protein Degradation and Inhibitors 2
    • Cancer therapeutics and mechanisms 1
    • Virus-based gene therapy research 5

Ian Scanlon

9 papers receiving 566 citations

Peers

Ian Scanlon
Comparison fields: 5 of 61
  • Oncology 193
  • Biotechnology 60
  • Molecular Biology 421
  • Computational Theory and Mathematics 84
  • Genetics 84
Replace Kristine M. Kim with:
Kristine M. Kim South Korea
Jan Martin United Kingdom
Vladimir Khazak United States
Chudi Ndubaku United States
Ashutosh Pal United States
O.-G. Issinger Germany
Sherif Tawfic United States
Lakshman Bindu United States
Gretchen A. Repasky United States
Mary Ellen Simcox United States
Ian Scanlon relative to Kristine M. Kim South Korea Kristine M. Kim's profile →
Citations per field
00.5×1.5×2.4×
Kristine M. Kim · 1×
Citations per year

Countries citing papers authored by Ian Scanlon

Since Specialization
Citations

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

Fields of papers citing papers by Ian Scanlon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 23 scholars most cited alongside Ian Scanlon, 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 Ian Scanlon Line = papers co-authored together Ian Scanlon links everyone, so they are left out of the graph.

All Works

9 of 9 papers shown
#Work
1 2004360
2 200750
3 200537
4
Three new prodrugs for suicide gene therapy using carboxypeptidase G2 elicit bystander efficacy in two xenograft models.
200232
5 200831
6 200527
7 200524
8 200418
9 20053

About Ian Scanlon

Ian Scanlon is a scholar working on Molecular Biology, Genetics, Biotechnology, Organic Chemistry and Oncology, having authored 9 papers that have together received 582 indexed citations. Recurring topics across this work include Virus-based gene therapy research (5 papers), Cancer Research and Treatments (4 papers), Click Chemistry and Applications (3 papers), Melanoma and MAPK Pathways (3 papers), Protein Degradation and Inhibitors (2 papers), Cancer Mechanisms and Therapy (1 paper), Pharmacogenetics and Drug Metabolism (1 paper) and Cancer therapeutics and mechanisms (1 paper). The work is most often cited by research in Oncology (193 citations), Biotechnology (60 citations), Molecular Biology (421 citations), Computational Theory and Mathematics (84 citations) and Genetics (84 citations). Ian Scanlon has collaborated with scholars based in United Kingdom and United States. Frequent co-authors include Caroline J. Springer, Frank Friedlos, Richard Marais, Lesley Ogilvie, Douglas Hedley, Dan Niculescu‐Duvaz, Jan Martin, Robert Hayward, Maria Karasarides and Antonio Chiloeches. Their work appears in journals such as Journal of Medicinal Chemistry, Cancer Research, Tetrahedron Letters, Oncogene and PubMed.

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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