Jim Olson

1.8k total citations
10 papers, 1.4k citations indexed

About

Jim Olson is a scholar working on Genetics, Biomaterials and Biomedical Engineering. According to data from OpenAlex, Jim Olson has authored 10 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Genetics, 4 papers in Biomaterials and 4 papers in Biomedical Engineering. Recurrent topics in Jim Olson's work include Nanoparticle-Based Drug Delivery (4 papers), Glioma Diagnosis and Treatment (4 papers) and Nanoplatforms for cancer theranostics (4 papers). Jim Olson is often cited by papers focused on Nanoparticle-Based Drug Delivery (4 papers), Glioma Diagnosis and Treatment (4 papers) and Nanoplatforms for cancer theranostics (4 papers). Jim Olson collaborates with scholars based in United States, South Africa and Australia. Jim Olson's co-authors include Omid Veiseh, Conroy Sun, Miqin Zhang, Richard G. Ellenbogen, Jonathan Gunn, Donghoon Lee, Fang Chen, Raymond W. Sze, Narayan Bhattarai and Stacey Hansen and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nano Letters and Cancer Research.

In The Last Decade

Jim Olson

8 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jim Olson United States	7	707	649	554	274	169	10	1.4k
Heather Kalish United States	18	672 1.0×	855 1.3×	594 1.1×	446 1.6×	329 1.9×	34	2.1k
Holly A. Zywicke United States	10	715 1.0×	737 1.1×	631 1.1×	303 1.1×	393 2.3×	12	2.0k
Donghoon Lee United States	8	530 0.7×	513 0.8×	313 0.6×	233 0.9×	48 0.3×	9	962
Emilia S. Olson United States	14	485 0.7×	853 1.3×	1.3k 2.3×	239 0.9×	53 0.3×	20	2.4k
Valerie A. Longo United States	22	533 0.8×	670 1.0×	656 1.2×	320 1.2×	92 0.5×	33	2.0k
David T Scadden United States	8	519 0.7×	518 0.8×	935 1.7×	271 1.0×	157 0.9×	9	2.1k
François Hindré France	26	719 1.0×	489 0.8×	584 1.1×	267 1.0×	144 0.9×	49	1.8k
Gabi Hanna United States	16	363 0.5×	542 0.8×	579 1.0×	118 0.4×	156 0.9×	22	1.4k
Jessica Ngai United States	8	911 1.3×	1.0k 1.6×	699 1.3×	265 1.0×	131 0.8×	11	1.8k
Giulio Fracasso Italy	30	395 0.6×	695 1.1×	749 1.4×	312 1.1×	78 0.5×	81	2.3k

Countries citing papers authored by Jim Olson

Since Specialization

Citations

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

Fields of papers citing papers by Jim Olson

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jim Olson

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

All Works

Sort: Min cites: Since: Top N: Style:

10 of 10 papers shown

1.

Mishra, Deepak Kumar, Shelli M. Morris, Shiva Senthil Kumar, et al.. (2023). IMMU-11. PRECLINICAL HIGH-RISK PEDIATRIC BRAIN TUMOR MODELS FOR IMMUNOTHERAPY: HURDLES AND THE WAY FORWARD. Neuro-Oncology. 25(Supplement_1). i51–i52. 1 indexed citations

2.

Olson, Jim. (2014). Project Violet. Oncology Issues. 29(3). 64–65.

3.

Veiseh, Omid, Conroy Sun, Fang Chen, et al.. (2009). Specific Targeting of Brain Tumors with an Optical/Magnetic Resonance Imaging Nanoprobe across the Blood-Brain Barrier. Cancer Research. 69(15). 6200–6207. 290 indexed citations

4.

Sun, Conroy, Omid Veiseh, Jonathan Gunn, et al.. (2008). In Vivo MRI Detection of Gliomas by Chlorotoxin‐Conjugated Superparamagnetic Nanoprobes. Small. 4(3). 372–379. 249 indexed citations

5.

Sun, Conroy, Fang Chen, Zachary R. Stephen, et al.. (2008). Tumor-Targeted Drug Delivery and MRI Contrast Enhancement by Chlorotoxin-Conjugated Iron Oxide Nanoparticles. Nanomedicine. 3(4). 495–505. 166 indexed citations

6.

Veiseh, Omid, Conroy Sun, Jonathan Gunn, et al.. (2005). Optical and MRI Multifunctional Nanoprobe for Targeting Gliomas. Nano Letters. 5(6). 1003–1008. 460 indexed citations

7.

Gilbertson, Richard J., D. Ashley Hill, Roberto Hernán, et al.. (2003). ERBB1 is amplified and overexpressed in high-grade diffusely infiltrative pediatric brain stem glioma.. PubMed. 9(10 Pt 1). 3620–4. 92 indexed citations

8.

Rostomily, Robert, Olivia Bermingham‐McDonogh, Mitchel S. Berger, et al.. (1997). Expression of neurogenic basic helix-loop-helix genes in primitive neuroectodermal tumors.. PubMed. 57(16). 3526–31. 73 indexed citations

9.

Tapscott, Stephen J., A. Dusty Miller, Jim Olson, et al.. (1994). Gene therapy of rat 9L gliosarcoma tumors by transduction with selectable genes does not require drug selection.. Proceedings of the National Academy of Sciences. 91(17). 8185–8189. 87 indexed citations

10.

Olson, Jim, et al.. (1976). Effects of Halothane on the Metabolism of Human Adipose Tissue. Acta Anaesthesiologica Scandinavica. 20(4). 327–333. 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.

Explore authors with similar magnitude of impact