Tom Mikkelson

680 total citations · 1 hit paper
6 papers, 530 citations indexed

About

Tom Mikkelson is a scholar working on Genetics, Oncology and Molecular Biology. According to data from OpenAlex, Tom Mikkelson has authored 6 papers receiving a total of 530 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Genetics, 4 papers in Oncology and 1 paper in Molecular Biology. Recurrent topics in Tom Mikkelson's work include Glioma Diagnosis and Treatment (5 papers), Cancer Treatment and Pharmacology (2 papers) and Brain Metastases and Treatment (1 paper). Tom Mikkelson is often cited by papers focused on Glioma Diagnosis and Treatment (5 papers), Cancer Treatment and Pharmacology (2 papers) and Brain Metastases and Treatment (1 paper). Tom Mikkelson collaborates with scholars based in United States, Australia and China. Tom Mikkelson's co-authors include Jeffrey G. Supko, Stuart A. Grossman, Joy Fisher, Serena Desideri, Quentin McAfee, Daniel F. Heitjan, Xiaobu Ye, Andrea B. Troxel, Laura Pontiggia and Daniel Wang and has published in prestigious journals such as Journal of Clinical Oncology, Clinical Cancer Research and International Journal of Radiation Oncology*Biology*Physics.

In The Last Decade

Tom Mikkelson

6 papers receiving 527 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

A phase I/II trial of hydroxychloroquine in conjunction with radiation therapy and concurrent and adjuvant temozolomide in patients with newly diagnosed glioblastoma multiforme

2014 409 citations Myrna R. Rosenfeld, Xiaobu Ye et al. Autophagy profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Tom Mikkelson United States	5	312	287	122	104	80	6	530
G. Mallon United States	5	233 0.7×	255 0.9×	65 0.5×	52 0.5×	59 0.7×	6	409
Yutaka Tamada Japan	9	236 0.8×	244 0.9×	65 0.5×	18 0.2×	56 0.7×	13	414
Yan Cui China	11	61 0.2×	324 1.1×	209 1.7×	34 0.3×	19 0.2×	25	446
Nami McCarty United States	15	113 0.4×	287 1.0×	71 0.6×	48 0.5×	13 0.2×	23	526
Craig Harlos Canada	8	72 0.2×	196 0.7×	115 0.9×	99 1.0×	7 0.1×	14	381
Manuela Hugle Germany	11	66 0.2×	263 0.9×	41 0.3×	14 0.1×	19 0.2×	14	365
Dan Cojocari Canada	11	74 0.2×	272 0.9×	80 0.7×	45 0.4×	6 0.1×	13	518
Antonio Lucena-Cacace Spain	14	78 0.3×	365 1.3×	104 0.9×	13 0.1×	45 0.6×	23	598
S Chen China	7	141 0.5×	386 1.3×	298 2.4×	11 0.1×	11 0.1×	12	582

Countries citing papers authored by Tom Mikkelson

Since Specialization

Citations

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

Fields of papers citing papers by Tom Mikkelson

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tom Mikkelson

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

All Works

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6 of 6 papers shown

1.

Davare, Monika A., Anupriya Agarwal, Jacob P. Wagner, et al.. (2018). Rare but Recurrent ROS1 Fusions Resulting From Chromosome 6q22 Microdeletions are Targetable Oncogenes in Glioma. Clinical Cancer Research. 24(24). 6471–6482. 37 indexed citations

2.

Hodges, Tiffany R., Sherise D. Ferguson, Hillary G. Caruso, et al.. (2016). Prioritization schema for immunotherapy clinical trials in glioblastoma. OncoImmunology. 5(6). e1145332–e1145332. 33 indexed citations

3.

Rosenfeld, Myrna R., Xiaobu Ye, Jeffrey G. Supko, et al.. (2014). A phase I/II trial of hydroxychloroquine in conjunction with radiation therapy and concurrent and adjuvant temozolomide in patients with newly diagnosed glioblastoma multiforme. Autophagy. 10(8). 1359–1368. 409 indexed citations breakdown →

4.

Peereboom, David M., Jeffrey G. Supko, Kathryn A. Carson, et al.. (2010). A phase I/II trial and pharmacokinetic study of ixabepilone in adult patients with recurrent high-grade gliomas. Journal of Neuro-Oncology. 100(2). 261–268. 18 indexed citations

5.

Gilbert, Mark R., Ken Aldape, Andrew B. Lassman, et al.. (2009). RTOG 0625: A phase II study of bevacizumab with irinotecan in recurrent glioblastoma (GBM). Journal of Clinical Oncology. 27(15_suppl). 2011–2011. 32 indexed citations

6.

Shaw, Edward, Tom Mikkelson, Lawrence Kleinberg, et al.. (2001). The gliasite radiation therapy system (RTS): a novel approach to brain brachytherapy for recurrent malignant glioma. International Journal of Radiation Oncology*Biology*Physics. 51(3). 203–203. 1 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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