Michael Zaidinski

572 total citations · 1 hit paper
5 papers, 418 citations indexed

About

Michael Zaidinski is a scholar working on Pulmonary and Respiratory Medicine, Pathology and Forensic Medicine and Oncology. According to data from OpenAlex, Michael Zaidinski has authored 5 papers receiving a total of 418 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Pulmonary and Respiratory Medicine, 2 papers in Pathology and Forensic Medicine and 2 papers in Oncology. Recurrent topics in Michael Zaidinski's work include HER2/EGFR in Cancer Research (2 papers), Sarcoma Diagnosis and Treatment (2 papers) and Monoclonal and Polyclonal Antibodies Research (2 papers). Michael Zaidinski is often cited by papers focused on HER2/EGFR in Cancer Research (2 papers), Sarcoma Diagnosis and Treatment (2 papers) and Monoclonal and Polyclonal Antibodies Research (2 papers). Michael Zaidinski collaborates with scholars based in United States. Michael Zaidinski's co-authors include Sinchita Roy‐Chowdhuri, Khédoudja Nafa, Mark G. Kris, Maria E. Arcila, Paul K. Paik, Christopher Lau, Marc Ladanyi, Maureen F. Zakowski, Jamie E. Chaft and Laura J. Tafe and has published in prestigious journals such as Clinical Cancer Research, American Journal of Clinical Pathology and Histopathology.

In The Last Decade

Michael Zaidinski

3 papers receiving 406 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.

Prevalence, Clinicopathologic Associations, and Molecular Spectrum of ERBB2 ( HER2 ) Tyrosine Kinase Mutations in Lung Adenocarcinomas

2012 366 citations Maria E. Arcila, Jamie E. Chaft et al. Clinical Cancer Research profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Michael Zaidinski United States	2	345	307	132	91	90	5	418
Kuntal Majmudar United States	2	408 1.2×	387 1.3×	212 1.6×	100 1.1×	94 1.0×	3	522
G. Groth Germany	5	279 0.8×	264 0.9×	102 0.8×	73 0.8×	50 0.6×	7	375
Penelope Ann Bradbury Canada	9	304 0.9×	227 0.7×	87 0.7×	45 0.5×	116 1.3×	39	375
Severine Kako United States	4	216 0.6×	196 0.6×	112 0.8×	48 0.5×	64 0.7×	6	290
Alessandro Gamboni Italy	7	363 1.1×	267 0.9×	103 0.8×	34 0.4×	155 1.7×	12	453
She-Juan An China	6	362 1.0×	281 0.9×	138 1.0×	31 0.3×	139 1.5×	7	453
Seol Bong Yoo South Korea	10	338 1.0×	261 0.9×	155 1.2×	80 0.9×	114 1.3×	15	481
Changli Wang China	13	450 1.3×	346 1.1×	89 0.7×	26 0.3×	114 1.3×	29	522
Pamela Trillo Aliaga Italy	9	139 0.4×	209 0.7×	69 0.5×	66 0.7×	83 0.9×	26	291
D. Chu China	5	430 1.2×	358 1.2×	127 1.0×	27 0.3×	108 1.2×	6	507

Countries citing papers authored by Michael Zaidinski

Since Specialization

Citations

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

Fields of papers citing papers by Michael Zaidinski

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael Zaidinski

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

All Works

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5 of 5 papers shown

1.

Chu, Ying‐Hsia, Nora Katabi, Purvil Sukhadia, et al.. (2024). Targeted RNA sequencing in diagnostically challenging head and neck carcinomas identifies novel MON2::STAT6, NFATC2::NUTM2B, POC5::RAF1, and NSD3::NCOA2 gene fusions. Histopathology. 86(5). 728–741. 1 indexed citations

2.

Stuver, Robert, Ting Zhou, Michael Zaidinski, et al.. (2024). A Novel JAK2 Fusion in T‐Cell Prolymphocytic Leukemia. Genes Chromosomes and Cancer. 63(6). e23252–e23252.

3.

Hosseini, Hossein, Oana Vele, Pamela D. Unger, et al.. (2022). Uterine Leiomyosarcoma with a Novel RAB2A-PLAG1 Gene Fusion. American Journal of Clinical Pathology. 158(Supplement_1). S88–S89.

4.

Arcila, Maria E., Jamie E. Chaft, Khédoudja Nafa, et al.. (2012). Prevalence, Clinicopathologic Associations, and Molecular Spectrum of ERBB2 ( HER2 ) Tyrosine Kinase Mutations in Lung Adenocarcinomas. Clinical Cancer Research. 18(18). 4910–4918. 366 indexed citations breakdown →

5.

Tafe, Laura J., Yelena Y. Janjigian, Michael Zaidinski, et al.. (2011). Human Epidermal Growth Factor Receptor 2 Testing in Gastroesophageal Cancer: Correlation Between Immunohistochemistry and Fluorescence In Situ Hybridization. Archives of Pathology & Laboratory Medicine. 135(11). 1460–1465. 51 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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