Thomas L. Olson

2.3k total citations
22 papers, 604 citations indexed

About

Thomas L. Olson is a scholar working on Immunology, Genetics and Pathology and Forensic Medicine. According to data from OpenAlex, Thomas L. Olson has authored 22 papers receiving a total of 604 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Immunology, 13 papers in Genetics and 10 papers in Pathology and Forensic Medicine. Recurrent topics in Thomas L. Olson's work include Chronic Lymphocytic Leukemia Research (13 papers), Lymphoma Diagnosis and Treatment (9 papers) and Immune Cell Function and Interaction (8 papers). Thomas L. Olson is often cited by papers focused on Chronic Lymphocytic Leukemia Research (13 papers), Lymphoma Diagnosis and Treatment (9 papers) and Immune Cell Function and Interaction (8 papers). Thomas L. Olson collaborates with scholars based in United States, Finland and India. Thomas L. Olson's co-authors include Thomas P. Loughran, Satu Mustjoki, David J. Feith, Michael J. Clemente, Pekka Ellonen, Kimmo Porkka, Hanna Rajala, Andrés Jerez, Emma Andersson and Cait E. Hamele and has published in prestigious journals such as Blood, Frontiers in Immunology and British Journal of Haematology.

In The Last Decade

Thomas L. Olson

20 papers receiving 601 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Thomas L. Olson United States 12 374 315 300 143 107 22 604
Hanna Rajala Finland 14 482 1.3× 398 1.3× 333 1.1× 216 1.5× 107 1.0× 19 768
Rudolf Übelhart Germany 9 438 1.2× 452 1.4× 332 1.1× 85 0.6× 200 1.9× 13 748
Vasantha Brito‐Babapulle United Kingdom 15 283 0.8× 498 1.6× 457 1.5× 233 1.6× 171 1.6× 29 773
Nnenna Osuji United Kingdom 13 322 0.9× 548 1.7× 458 1.5× 178 1.2× 86 0.8× 23 678
N Spector United States 9 269 0.7× 211 0.7× 323 1.1× 301 2.1× 140 1.3× 10 754
Marcus Dühren-von Minden Germany 10 410 1.1× 465 1.5× 332 1.1× 122 0.9× 319 3.0× 11 886
Daphne R. Friedman United States 12 254 0.7× 217 0.7× 174 0.6× 126 0.9× 330 3.1× 38 699
Patricia Johansson Germany 11 130 0.3× 170 0.5× 166 0.6× 107 0.7× 105 1.0× 21 373
AC Fluckiger Israel 8 380 1.0× 274 0.9× 180 0.6× 103 0.7× 112 1.0× 10 540
H Mellstedt Sweden 9 223 0.6× 225 0.7× 194 0.6× 121 0.8× 154 1.4× 16 501

Countries citing papers authored by Thomas L. Olson

Since Specialization
Citations

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

Fields of papers citing papers by Thomas L. Olson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Thomas L. Olson. 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 Thomas L. Olson. The network helps show where Thomas L. Olson may publish in the future.

Co-authorship network of co-authors of Thomas L. Olson

This figure shows the co-authorship network connecting the top 25 collaborators of Thomas L. Olson. A scholar is included among the top collaborators of Thomas L. Olson 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 Thomas L. Olson. Thomas L. Olson 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.
2.
Olson, Thomas L., Cait E. Hamele, William D. Baker, et al.. (2024). Activating STAT3 mutations in CD8+ T-cells correlate to serological positivity in rheumatoid arthritis. Frontiers in Immunology. 15. 1466276–1466276.
3.
Xing, Jeffrey C., Cait E. Hamele, Ross C. Hardison, et al.. (2022). Genomic landscape of TCRαβ and TCRγδ T-large granular lymphocyte leukemia. Blood. 139(20). 3058–3072. 37 indexed citations
4.
Olson, Thomas L., Jeffrey C. Xing, Kristine C. Olson, et al.. (2021). Frequent somatic TET2 mutations in chronic NK-LGL leukemia with distinct patterns of cytopenias. Blood. 138(8). 662–673. 33 indexed citations
5.
Xing, Jeffrey C., Cait E. Hamele, Thomas L. Olson, et al.. (2020). Analysis of Genomic Landscape of Large Granular Lymphocyte Leukemia Reveals Etiologic Insights. Blood. 136(Supplement 1). 27–28. 1 indexed citations
6.
Baer, Constance, Shunsuke Kimura, Ilaria Iacobucci, et al.. (2020). Recurrent Mutations of the C-C Motif Chemokine Ligand 22 (CCL22) Define a Distinct Subgroup of Chronic Lymphoproliferative Disorder of NK Cells (CLPD-NK). Blood. 136(Supplement 1). 19–19. 2 indexed citations
7.
Paila, Umadevi, Kristine C. Olson, Jeffrey C. Xing, et al.. (2019). Genomics of LGL leukemia and select other rare leukemia/lymphomas. Best Practice & Research Clinical Haematology. 32(3). 196–206. 11 indexed citations
8.
Yang, Lei, Robert S. Harris, Lin Lin, et al.. (2019). Retrovirus insertion site analysis of LGL leukemia patient genomes. BMC Medical Genomics. 12(1). 88–88. 11 indexed citations
9.
Yang, Jun, Francis LeBlanc, Cait E. Hamele, et al.. (2018). TRAIL mediates and sustains constitutive NF-κB activation in LGL leukemia. Blood. 131(25). 2803–2815. 32 indexed citations
10.
Yang, Jun, Yong Zhang, Meili Zhang, et al.. (2018). IL-2 and IL-15 blockade by BNZ-1, an inhibitor of selective γ-chain cytokines, decreases leukemic T-cell viability. Leukemia. 33(5). 1243–1255. 37 indexed citations
11.
12.
Olson, Kristine C., et al.. (2017). Calcitriol-mediated reduction in IFN-γ output in T cell large granular lymphocytic leukemia requires vitamin D receptor upregulation. The Journal of Steroid Biochemistry and Molecular Biology. 177. 140–148. 7 indexed citations
13.
Savola, Paula, Oscar Brück, Thomas L. Olson, et al.. (2017). Somatic STAT3 mutations in Felty syndrome: an implication for a common pathogenesis with large granular lymphocyte leukemia. Haematologica. 103(2). 304–312. 51 indexed citations
14.
Yan, Yiyi, Thomas L. Olson, Susan B. Nyland, David J. Feith, & Thomas P. Loughran. (2014). Emergence of a STAT3 mutated NK clone in LGL leukemia. Leukemia Research Reports. 4(1). 4–7. 7 indexed citations
15.
Rajala, Hanna, Thomas L. Olson, Michael J. Clemente, et al.. (2014). The analysis of clonal diversity and therapy responses using STAT3 mutations as a molecular marker in large granular lymphocytic leukemia. Haematologica. 100(1). 91–99. 68 indexed citations
16.
Andersson, Emma, Hanna Rajala, Samuli Eldfors, et al.. (2013). Novel somatic mutations in large granular lymphocytic leukemia affecting the STAT-pathway and T-cell activation. Blood Cancer Journal. 3(12). e168–e168. 44 indexed citations
17.
Rajala, Hanna, Samuli Eldfors, Heikki Kuusanmäki, et al.. (2013). Discovery of somatic STAT5b mutations in large granular lymphocytic leukemia. Blood. 121(22). 4541–4550. 195 indexed citations
18.
Rajala, Hanna, Samuli Eldfors, Heikki Kuusanmäki, et al.. (2012). Discovery of STAT5b Mutations and Small Subclones of STAT3 Mutations in Large Granular Lymphocytic (LGL) Leukemia. Blood. 120(21). 871–871. 3 indexed citations
19.
Pastor, Danielle M., Lisa S. Poritz, Thomas L. Olson, et al.. (2010). Primary cell lines: false representation or model system? a comparison of four human colorectal tumors and their coordinately established cell lines.. PubMed. 3(1). 69–83. 28 indexed citations
20.
Kline, C. Leah B., Thomas L. Olson, & Rosalyn Irby. (2008). Src activity alters α3 integrin expression in colon tumor cells. Clinical & Experimental Metastasis. 26(2). 77–87. 8 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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