Daniel Thomson

4.4k total citations · 1 hit paper
17 papers, 3.0k citations indexed

About

Daniel Thomson is a scholar working on Molecular Biology, Cancer Research and Hematology. According to data from OpenAlex, Daniel Thomson has authored 17 papers receiving a total of 3.0k indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 9 papers in Cancer Research and 6 papers in Hematology. Recurrent topics in Daniel Thomson's work include MicroRNA in disease regulation (6 papers), Chronic Myeloid Leukemia Treatments (6 papers) and RNA Research and Splicing (5 papers). Daniel Thomson is often cited by papers focused on MicroRNA in disease regulation (6 papers), Chronic Myeloid Leukemia Treatments (6 papers) and RNA Research and Splicing (5 papers). Daniel Thomson collaborates with scholars based in Australia, Switzerland and United States. Daniel Thomson's co-authors include Marcel E. Dinger, Gregory J. Goodall, Cameron P. Bracken, Michael B. Clark, Bethany Signal, Brian Gloss, Jesper L.V. Mååg, Nenad Bartoniček, Jan M. Szubert and Katherine A. Pillman and has published in prestigious journals such as Nucleic Acids Research, The EMBO Journal and Blood.

In The Last Decade

Daniel Thomson

17 papers receiving 3.0k citations

Hit Papers

Endogenous microRNA sponges: evidence and controversy 2016 2026 2019 2022 2016 500 1000 1.5k

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Daniel Thomson Australia 11 2.6k 2.4k 151 130 87 17 3.0k
Nenad Bartoniček Australia 17 1.8k 0.7× 1.3k 0.6× 315 2.1× 138 1.1× 102 1.2× 28 2.2k
Bárbara Tazón‐Vega Spain 10 2.8k 1.1× 2.6k 1.1× 151 1.0× 135 1.0× 172 2.0× 24 3.6k
Run-Wen Yao China 7 2.3k 0.9× 1.6k 0.7× 71 0.5× 120 0.9× 110 1.3× 12 2.5k
Jian‐Feng Xiang China 14 3.2k 1.2× 2.6k 1.1× 104 0.7× 102 0.8× 71 0.8× 29 3.4k
Monica Ballarino Italy 24 2.1k 0.8× 1.2k 0.5× 107 0.7× 135 1.0× 68 0.8× 40 2.4k
Jeffrey J. Quinn United States 11 3.5k 1.3× 3.2k 1.3× 178 1.2× 185 1.4× 207 2.4× 13 4.1k
Minju Kim South Korea 6 2.7k 1.1× 2.4k 1.0× 409 2.7× 194 1.5× 77 0.9× 8 3.3k
Ankit Malhotra United States 13 2.2k 0.9× 1.2k 0.5× 171 1.1× 64 0.5× 57 0.7× 19 2.5k
David Frendewey United States 21 2.5k 1.0× 960 0.4× 182 1.2× 478 3.7× 93 1.1× 36 3.2k
Danielle Johnston Canada 14 1.3k 0.5× 771 0.3× 32 0.2× 79 0.6× 86 1.0× 29 1.6k

Countries citing papers authored by Daniel Thomson

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Thomson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel Thomson

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Thomson. A scholar is included among the top collaborators of Daniel Thomson 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 Daniel Thomson. Daniel Thomson is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

17 of 17 papers shown
1.
Ray, Roslyn M., Daniel Thomson, Iram Khan, et al.. (2024). DNA-PK inhibition enhances gene editing efficiency in HSPCs for CRISPR-based treatment of X-linked hyper IgM syndrome. Molecular Therapy — Methods & Clinical Development. 32(3). 101297–101297. 1 indexed citations
3.
Shanmuganathan, Naranie, Carol Wadham, Daniel Thomson, et al.. (2022). RNA-Based Targeted Gene Sequencing Improves the Diagnostic Yield of Mutant Detection in Chronic Myeloid Leukemia. Journal of Molecular Diagnostics. 24(7). 803–822. 5 indexed citations
4.
Thomson, Daniel, Nur Hezrin Shahrin, Paul Wang, et al.. (2020). Aberrant RAG-mediated recombination contributes to multiple structural rearrangements in lymphoid blast crisis of chronic myeloid leukemia. Leukemia. 34(8). 2051–2063. 24 indexed citations
5.
Awad, Shady Adnan, Olli Dufva, Aleksandr Ianevski, et al.. (2020). RUNX1 mutations in blast-phase chronic myeloid leukemia associate with distinct phenotypes, transcriptional profiles, and drug responses. Leukemia. 35(4). 1087–1099. 35 indexed citations
6.
Shanmuganathan, Naranie, Carol Wadham, Nur Hezrin Shahrin, et al.. (2020). Mutated Cancer-Related Genes Detected at Diagnosis of CML and a Novel Class of Variant Associated with the Philadelphia Translocation Are Both Independent Predictors of Inferior Outcomes. Blood. 136(Supplement 1). 46–47. 3 indexed citations
7.
Shanmuganathan, Naranie, Daniel Thomson, Carol Wadham, et al.. (2019). RNA Splicing Defects in Cancer-Linked Genes Indicate Mutation or Focal Gene Deletion and Are Associated with TKI Resistance in CML. Blood. 134(Supplement_1). 662–662. 1 indexed citations
8.
Thomson, Daniel, Nur Hezrin Shahrin, Paul Wang, et al.. (2018). High Recombination Activating Gene (RAG) Expression and RAG Mediated Recombination Is Associated with Oncogenic Rearrangement Observed with Tyrosine Kinase Inhibitor Resistant CML. Blood. 132(Supplement 1). 3001–3001. 1 indexed citations
9.
Thomson, Daniel & Marcel E. Dinger. (2016). Endogenous microRNA sponges: evidence and controversy. Nature Reviews Genetics. 17(5). 272–283. 1620 indexed citations breakdown →
10.
Thomson, Daniel, Katherine A. Pillman, Matthew L. Anderson, et al.. (2014). Assessing the gene regulatory properties of Argonaute-bound small RNAs of diverse genomic origin. Nucleic Acids Research. 43(1). 470–481. 34 indexed citations
11.
Thomson, Daniel, Jesper L.V. Mååg, Nenad Bartoniček, et al.. (2014). lncRNAdb v2.0: expanding the reference database for functional long noncoding RNAs. Nucleic Acids Research. 43(D1). D168–D173. 420 indexed citations
12.
Bracken, Cameron P., Josephine A. Wright, David Lawrence, et al.. (2014). Genome‐wide identification of miR‐200 targets reveals a regulatory network controlling cell invasion. The EMBO Journal. 33(18). 2040–2056. 115 indexed citations
13.
Thomson, Daniel, Cameron P. Bracken, Jan M. Szubert, & Gregory J. Goodall. (2013). On Measuring miRNAs after Transient Transfection of Mimics or Antisense Inhibitors. PLoS ONE. 8(1). e55214–e55214. 99 indexed citations
14.
Thomson, Daniel, Keith M. Giles, Sanaz Maleki, et al.. (2011). miR-124a is frequently down-regulated in glioblastoma and is involved in migration and invasion. European Journal of Cancer. 47(6). 953–963. 116 indexed citations
15.
Thomson, Daniel, Cameron P. Bracken, & Gregory J. Goodall. (2011). Experimental strategies for microRNA target identification. Nucleic Acids Research. 39(16). 6845–6853. 442 indexed citations
16.
Bracken, Cameron P., Jan M. Szubert, Tim R. Mercer, et al.. (2011). Global analysis of the mammalian RNA degradome reveals widespread miRNA-dependent and miRNA-independent endonucleolytic cleavage. Nucleic Acids Research. 39(13). 5658–5668. 69 indexed citations
17.
McFarland, Ken, et al.. (2000). Cisplatin‐based therapy: a neurological and neuropsychological review. Psycho-Oncology. 9(1). 29–39. 11 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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