Dónal Landers

1.6k citations
35 papers · 750 · h-index 14

Impact in

Papers in

    • Fibroblast Growth Factor Research 8
    • Biomedical Text Mining and Ontologies 3
    • HER2/EGFR in Cancer Research 4

Dónal Landers

32 papers receiving 733 citations

Peers

Dónal Landers
Comparison fields: 5 of 77
  • Health Informatics 33
  • Gastroenterology 43
  • Oncology 188
  • Pulmonary and Respiratory Medicine 211
  • Cancer Research 78
Replace Ahrong Kim with:
Ahrong Kim South Korea
Maren Knödler Germany
Mi Sun Ahn South Korea
Sujuan Xi China
Xiao Hu China
Kaoru Nakano Japan
Haitao Hu China
Margaret G. Keane United Kingdom
Wei Qiang Leow Singapore
Bum‐Sup Jang South Korea
Dónal Landers relative to Ahrong Kim South Korea Ahrong Kim's profile →
Citations per field
00.5×2.8×
Ahrong Kim · 1×
Citations per year

Countries citing papers authored by Dónal Landers

Since Specialization
Citations

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

Fields of papers citing papers by Dónal Landers

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Dónal Landers, 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 Dónal Landers Line = papers co-authored together Dónal Landers links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017153
2 2017115
3 202269
4 201549
5 201748
6 202338
7 201437
8 202323
9 201523
10 201923
11 202319
12 201317
13 201416
14 201714
15 202113
16 202112
17 202210
18 20229
19 19969
20 20169

About Dónal Landers

Dónal Landers is a scholar working on Molecular Biology, Oncology, Pulmonary and Respiratory Medicine, Artificial Intelligence and Cancer Research, having authored 35 papers that have together received 750 indexed citations. Recurring topics across this work include Fibroblast Growth Factor Research (8 papers), HER2/EGFR in Cancer Research (4 papers), Machine Learning in Healthcare (3 papers), Advanced Breast Cancer Therapies (3 papers), Bladder and Urothelial Cancer Treatments (3 papers), Topic Modeling (3 papers), Biomedical Text Mining and Ontologies (3 papers) and Cancer Genomics and Diagnostics (2 papers). The work is most often cited by research in Health Informatics (33 citations), Gastroenterology (43 citations), Oncology (188 citations), Pulmonary and Respiratory Medicine (211 citations) and Cancer Research (78 citations). Dónal Landers has collaborated with scholars based in United Kingdom, Switzerland and United States. Frequent co-authors include Elaine Kilgour, André Freitas, Neil R. Smith, Paul Frewer, Oskar Wysocki, Russell Petty, Yee Chao, Eric Van Cutsem, Wasat Mansoor and David Ferry. Their work appears in journals such as Journal of Clinical Oncology, Cancer Research, Annals of Oncology, BMJ Open and Journal of Hematology & Oncology.

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.

Explore authors with similar magnitude of impact