Dónal Landers

1.6k total citations
35 papers, 728 citations indexed

About

Dónal Landers is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine and Oncology. According to data from OpenAlex, Dónal Landers has authored 35 papers receiving a total of 728 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 11 papers in Pulmonary and Respiratory Medicine and 10 papers in Oncology. Recurrent topics in Dónal Landers's work include Fibroblast Growth Factor Research (8 papers), HER2/EGFR in Cancer Research (4 papers) and Cancer Genomics and Diagnostics (4 papers). Dónal Landers is often cited by papers focused on Fibroblast Growth Factor Research (8 papers), HER2/EGFR in Cancer Research (4 papers) and Cancer Genomics and Diagnostics (4 papers). Dónal Landers collaborates with scholars based in United Kingdom, Switzerland and United States. Dónal Landers's co-authors include Elaine Kilgour, André Freitas, Neil R. Smith, Paul Frewer, Oskar Wysocki, David Ferry, Eric Van Cutsem, Wasat Mansoor, Paul K. Stockman and Yee Chao and has published in prestigious journals such as Journal of Clinical Oncology, Cancer Research and Clinical Cancer Research.

In The Last Decade

Dónal Landers

31 papers receiving 713 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Dónal Landers 382 253 219 127 102 35 728
Ka-On Lam 200 0.5× 368 1.5× 443 2.0× 225 1.8× 135 1.3× 57 968
Mi Sun Ahn 188 0.5× 524 2.1× 466 2.1× 107 0.8× 96 0.9× 48 840
Haitao Hu 164 0.4× 148 0.6× 153 0.7× 81 0.6× 111 1.1× 37 456
Lan Peng 187 0.5× 104 0.4× 285 1.3× 137 1.1× 132 1.3× 27 703
Sujuan Xi 110 0.3× 280 1.1× 236 1.1× 128 1.0× 75 0.7× 22 710
Judith Offman 184 0.5× 170 0.7× 341 1.6× 143 1.1× 108 1.1× 30 806
Keita Koseki 101 0.3× 127 0.5× 80 0.4× 110 0.9× 50 0.5× 11 410
Hongying Lv 207 0.5× 152 0.6× 184 0.8× 55 0.4× 87 0.9× 18 445
Tarjei S. Hveem 161 0.4× 177 0.7× 332 1.5× 59 0.5× 211 2.1× 21 841
Bum‐Sup Jang 133 0.3× 147 0.6× 221 1.0× 52 0.4× 105 1.0× 67 663

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-authorship network of co-authors of Dónal Landers

This figure shows the co-authorship network connecting the top 25 collaborators of Dónal Landers. A scholar is included among the top collaborators of Dónal Landers 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 Dónal Landers. Dónal Landers 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.
Wysocki, Oskar, et al.. (2025). Translating the machine; An assessment of clinician understanding of ophthalmological artificial intelligence outputs. International Journal of Medical Informatics. 201. 105958–105958.
2.
Frost, Hannah, et al.. (2023). SemEval-2023 Task 7: Multi-Evidence Natural Language Inference for Clinical Trial Data. Research Explorer (The University of Manchester). 2216–2226. 23 indexed citations
3.
Frost, Hannah, et al.. (2023). NLI4CT: Multi-Evidence Natural Language Inference for Clinical Trial Reports. Research Explorer (The University of Manchester). 16745–16764. 2 indexed citations
4.
Stevenson, Julie-Anne, Hannah Frost, Donna M. Graham, et al.. (2023). Digital ECMT Cancer Trial Matching Tool: an Open Source Research Application to Support Oncologists in the Identification of Precision Medicine Clinical Trials. JCO Clinical Cancer Informatics. 7(7). e2200137–e2200137. 5 indexed citations
5.
Wysocka, Magdalena, Oskar Wysocki, Marie Zufferey, Dónal Landers, & André Freitas. (2023). A systematic review of biologically-informed deep learning models for cancer: fundamental trends for encoding and interpreting oncology data. BMC Bioinformatics. 24(1). 198–198. 32 indexed citations
6.
Wysocka, Magdalena, Oskar Wysocki, Manon Pillai, et al.. (2023). Meta-analysis informed machine learning: Supporting cytokine storm detection during CAR-T cell Therapy. Journal of Biomedical Informatics. 142. 104367–104367. 19 indexed citations
7.
Wysocki, Oskar, Markel Vigo, Anne Armstrong, et al.. (2022). Assessing the communication gap between AI models and healthcare professionals: Explainability, utility and trust in AI-driven clinical decision-making. Artificial Intelligence. 316. 103839–103839. 61 indexed citations
8.
Frost, Hannah, et al.. (2022). Patient attrition in Molecular Tumour Boards: a systematic review. British Journal of Cancer. 127(8). 1557–1564. 5 indexed citations
9.
Freeman, Anna, Alastair Watson, Oskar Wysocki, et al.. (2021). Wave comparisons of clinical characteristics and outcomes of COVID-19 admissions - Exploring the impact of treatment and strain dynamics. Journal of Clinical Virology. 146. 105031–105031. 12 indexed citations
10.
Burke, Hannah, Ahilanandan Dushianthan, Michael Celinski, et al.. (2021). Research Evaluation Alongside Clinical Treatment in COVID-19 (REACT COVID-19): an observational and biobanking study. BMJ Open. 11(1). e043012–e043012. 13 indexed citations
11.
12.
Paik, Paul K., Ronglai Shen, Michael F. Berger, et al.. (2017). A Phase Ib Open-Label Multicenter Study of AZD4547 in Patients with Advanced Squamous Cell Lung Cancers. Clinical Cancer Research. 23(18). 5366–5373. 115 indexed citations
13.
Saka, Hideo, Chiyoe Kitagawa, Yoshihito Kogure, et al.. (2017). Safety, tolerability and pharmacokinetics of the fibroblast growth factor receptor inhibitor AZD4547 in Japanese patients with advanced solid tumours: a Phase I study. Investigational New Drugs. 35(4). 451–462. 48 indexed citations
14.
15.
Hughes, Andrew, Dónal Landers, Hendrik‐Tobias Arkenau, et al.. (2016). Development and Evaluation of a New Technological Way of Engaging Patients and Enhancing Understanding of Drug Tolerability in Early Clinical Development: PROACT. Advances in Therapy. 33(6). 1012–1024. 3 indexed citations
16.
Powles, Thomas, Elaine Kilgour, Hendrik‐Tobias Arkenau, et al.. (2016). BISCAY, a phase Ib, biomarker-directed multidrug umbrella study in patients with metastatic bladder cancer.. Journal of Clinical Oncology. 34(15_suppl). TPS4577–TPS4577. 9 indexed citations
17.
Jones, Robert H., David Alan Anthoney, Robert J. Jones, et al.. (2016). FIESTA: A phase Ib and pharmacokinetic trial of AZD4547 in combination with gemcitabine and cisplatin.. Journal of Clinical Oncology. 34(15_suppl). 4521–4521. 2 indexed citations
18.
Rodríguez‐Vida, Alejo, Matilde Saggese, Simon Hughes, et al.. (2015). Complexity of FGFR signalling in metastatic urothelial cancer. Journal of Hematology & Oncology. 8(1). 119–119. 23 indexed citations
19.
Arkenau, Hendrik‐Tobias, Matilde Saggese, Antoine Hollebecque, et al.. (2014). A phase 1 expansion cohort of the fibroblast growth factor receptor (FGFR) inhibitor AZD4547 in patients (pts) with advanced gastric (GC) and gastroesophageal (GOJ) cancer.. Journal of Clinical Oncology. 32(15_suppl). 2620–2620. 16 indexed citations
20.
Landers, Dónal, et al.. (1996). Dapsone induced methaemoglobinaemia. International Journal of STD & AIDS. 7(6). 445–446. 9 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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