Michael R. Weist

489 total citations
8 papers, 352 citations indexed

About

Michael R. Weist is a scholar working on Oncology, Biomedical Engineering and Immunology. According to data from OpenAlex, Michael R. Weist has authored 8 papers receiving a total of 352 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Oncology, 4 papers in Biomedical Engineering and 2 papers in Immunology. Recurrent topics in Michael R. Weist's work include CAR-T cell therapy research (5 papers), Nanowire Synthesis and Applications (3 papers) and Advancements in Semiconductor Devices and Circuit Design (2 papers). Michael R. Weist is often cited by papers focused on CAR-T cell therapy research (5 papers), Nanowire Synthesis and Applications (3 papers) and Advancements in Semiconductor Devices and Circuit Design (2 papers). Michael R. Weist collaborates with scholars based in United States. Michael R. Weist's co-authors include Christine E. Brown, Darya Alizadeh, David Akhavan, Dongrui Wang, Jennifer Kelly Shepphird, David Colcher, John E. Shively, Erasmus Poku, Junie Chea and Ethan Gerdts and has published in prestigious journals such as PLoS ONE, Cancer Research and Immunological Reviews.

In The Last Decade

Michael R. Weist

6 papers receiving 350 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Michael R. Weist United States	6	215	123	95	94	60	8	352
Akane Yamamichi Japan	12	221 1.0×	90 0.7×	147 1.5×	108 1.1×	100 1.7×	25	400
Maxim A. Moroz United States	11	275 1.3×	146 1.2×	190 2.0×	84 0.9×	52 0.9×	19	558
Vanesa Alonso-Camino Spain	10	158 0.7×	72 0.6×	135 1.4×	51 0.5×	62 1.0×	16	296
Shruthi Prasad Germany	5	242 1.1×	63 0.5×	80 0.8×	130 1.4×	45 0.8×	7	337
Víctor A. Arrieta United States	10	179 0.8×	151 1.2×	118 1.2×	167 1.8×	164 2.7×	27	510
Maria Ormhøj Denmark	7	231 1.1×	74 0.6×	124 1.3×	97 1.0×	18 0.3×	14	382
Monica Epstein United States	3	330 1.5×	131 1.1×	72 0.8×	149 1.6×	99 1.6×	5	395
Axel Hyrenius‐Wittsten Sweden	7	277 1.3×	124 1.0×	249 2.6×	117 1.2×	31 0.5×	11	621
Ashwini Balakrishnan United States	5	347 1.6×	116 0.9×	202 2.1×	114 1.2×	26 0.4×	7	448
Shivem B. Shah United States	11	129 0.6×	129 1.0×	121 1.3×	86 0.9×	26 0.4×	13	344

Countries citing papers authored by Michael R. Weist

Since Specialization

Citations

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

Fields of papers citing papers by Michael R. Weist

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael R. Weist. 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 Michael R. Weist. The network helps show where Michael R. Weist may publish in the future.

Co-authorship network of co-authors of Michael R. Weist

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

All Works

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8 of 8 papers shown

Weinberger, Leehee, Jason Yi, Michael R. Weist, et al.. (2023). HER2 and HLA-A*02 dual CAR-T cells utilize LOH in a NOT logic gate to address on-target off-tumor toxicity. Journal for ImmunoTherapy of Cancer. 11(12). e007426–e007426. 16 indexed citations

Weist, Michael R., Leehee Weinberger, Jason Yi, et al.. (2022). 316 Next generation CAR-T incorporating an inhibitory CAR (iCAR) for increased safety in solid tumors. Regular and Young Investigator Award Abstracts. A332–A332.

Yi, Jason, Sarit Tabak, Leehee Weinberger, et al.. (2022). Abstract 2848: Incorporation of inhibitory signaling domains into chimeric antigen receptors (iCAR) designed for self-regulation of canonical CAR-T to treat solid tumors. Cancer Research. 82(12_Supplement). 2848–2848.

Akhavan, David, Darya Alizadeh, Dongrui Wang, et al.. (2019). CAR T cells for brain tumors: Lessons learned and road ahead. Immunological Reviews. 290(1). 60–84. 164 indexed citations

Weist, Michael R., Renate Starr, Brenda Aguilar, et al.. (2018). PET of Adoptively Transferred Chimeric Antigen Receptor T Cells with ⁸⁹Zr-Oxine. Journal of Nuclear Medicine. 59(10). 1531–1537. 105 indexed citations

Li, Lin, Junie Chea, Erasmus Poku, et al.. (2017). Diagnostic PET Imaging of Mammary Microcalcifications Using ⁶⁴Cu-DOTA-Alendronate in a Rat Model of Breast Cancer. Journal of Nuclear Medicine. 58(9). 1373–1379. 11 indexed citations

Maria, Naomi S. Sta, Samuel Barnes, Michael R. Weist, et al.. (2015). Low Dose Focused Ultrasound Induces Enhanced Tumor Accumulation of Natural Killer Cells. PLoS ONE. 10(11). e0142767–e0142767. 26 indexed citations

Weist, Michael R., et al.. (2012). TGF-β1 enhances contractility in engineered skeletal muscle. Journal of Tissue Engineering and Regenerative Medicine. 7(7). 562–571. 30 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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