Kenneth D. Greis

8.1k total citations
95 papers, 3.7k citations indexed

About

Kenneth D. Greis is a scholar working on Molecular Biology, Spectroscopy and Immunology. According to data from OpenAlex, Kenneth D. Greis has authored 95 papers receiving a total of 3.7k indexed citations (citations by other indexed papers that have themselves been cited), including 58 papers in Molecular Biology, 15 papers in Spectroscopy and 15 papers in Immunology. Recurrent topics in Kenneth D. Greis's work include Mass Spectrometry Techniques and Applications (12 papers), Glycosylation and Glycoproteins Research (9 papers) and Acute Myeloid Leukemia Research (8 papers). Kenneth D. Greis is often cited by papers focused on Mass Spectrometry Techniques and Applications (12 papers), Glycosylation and Glycoproteins Research (9 papers) and Acute Myeloid Leukemia Research (8 papers). Kenneth D. Greis collaborates with scholars based in United States, United Kingdom and New Zealand. Kenneth D. Greis's co-authors include Gerald W. Hart, Verónica Sánchez, Elizabeth Sztul, William J. Britt, Pankaj Dwivedi, Bradley K. Hayes, Joseph A. Loo, Jeff B. Smaill, William A. Denny and Frank I. Comer and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Journal of Clinical Investigation.

In The Last Decade

Kenneth D. Greis

92 papers receiving 3.6k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kenneth D. Greis United States 33 2.1k 579 499 498 490 95 3.7k
Matthew B. Renfrow United States 34 2.9k 1.4× 281 0.5× 1.2k 2.4× 360 0.7× 410 0.8× 80 5.3k
Brian L. Hood United States 38 2.7k 1.3× 577 1.0× 389 0.8× 365 0.7× 154 0.3× 105 4.4k
Makoto Takeuchi Japan 37 2.7k 1.3× 395 0.7× 1.2k 2.4× 211 0.4× 751 1.5× 189 4.6k
Haichao Zhang United States 31 3.7k 1.8× 1.1k 1.8× 525 1.1× 292 0.6× 431 0.9× 90 5.0k
Francis P. Gasparro United States 30 1.2k 0.6× 451 0.8× 881 1.8× 426 0.9× 493 1.0× 94 4.3k
Kerri Mowen United States 25 2.5k 1.2× 864 1.5× 2.4k 4.8× 283 0.6× 416 0.8× 33 5.3k
John M. Sanders United States 37 1.6k 0.8× 501 0.9× 835 1.7× 448 0.9× 402 0.8× 71 4.0k
Moulay A. Alaoui‐Jamali Canada 42 3.1k 1.5× 1.3k 2.3× 244 0.5× 378 0.8× 332 0.7× 138 4.8k
Colin Reily United States 17 1.7k 0.8× 149 0.3× 616 1.2× 188 0.4× 349 0.7× 29 2.8k
Kohji Noguchi Japan 29 2.0k 1.0× 1.0k 1.8× 318 0.6× 302 0.6× 137 0.3× 108 3.3k

Countries citing papers authored by Kenneth D. Greis

Since Specialization
Citations

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

Fields of papers citing papers by Kenneth D. Greis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kenneth D. Greis. 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 Kenneth D. Greis. The network helps show where Kenneth D. Greis may publish in the future.

Co-authorship network of co-authors of Kenneth D. Greis

This figure shows the co-authorship network connecting the top 25 collaborators of Kenneth D. Greis. A scholar is included among the top collaborators of Kenneth D. Greis 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 Kenneth D. Greis. Kenneth D. Greis 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.
Choi, Issac, Courtnee Clough, Aishlin Hassan, et al.. (2026). Scaffolding-dependent CASP1 constrains excessive cell-intrinsic inflammatory signaling in leukemia. Cell chemical biology. 33(1). 59–73.e10.
2.
Wyder, Michael A., et al.. (2025). Functional compartmentalization of hepatic mitochondrial subpopulations during MASH progression. Communications Biology. 8(1). 258–258. 6 indexed citations
3.
Hassan, Aishlin, Kwangmin Choi, Courtnee Clough, et al.. (2025). Targeting of IRAK4 and GSPT1 enhances therapeutic efficacy in AML via c-Myc destabilization. Leukemia. 39(9). 2163–2173. 2 indexed citations
4.
5.
Setayesh, Tahereh, Masahide Sakabe, Katie Seu, et al.. (2025). A novel mouse model of hemoglobin SC disease reveals mechanisms underlying beneficial effects of hydroxyurea. Blood. 146(1). 13–28. 1 indexed citations
6.
Chutipongtanate, Somchai, Xiang Zhang, Damaris Kuhnell, et al.. (2025). Prenatal SARS-CoV-2 Infection Alters Human Milk-Derived Extracellular Vesicles. Cells. 14(4). 284–284. 1 indexed citations
7.
Barreyro, Laura, Kathleen Hueneman, Issac Choi, et al.. (2025). Ubiquitin-conjugating enzyme UBE2N modulates proteostasis in immunoproteasome-positive acute myeloid leukemia. Journal of Clinical Investigation. 135(10). 4 indexed citations
8.
Zhu, Xiaoqin, Michael A. Wyder, Nathan Salomonis, et al.. (2023). Repression of TRIM13 by chromatin assembly factor CHAF1B is critical for AML development. Blood Advances. 7(17). 4822–4837. 4 indexed citations
9.
Agarwal, Puneet, Jennifer Yeung, Lyndsey Bolanos, et al.. (2023). Paralog-specific signaling by IRAK1/4 maintains MyD88-independent functions in MDS/AML. Blood. 142(11). 989–1007. 27 indexed citations
10.
Chutipongtanate, Somchai & Kenneth D. Greis. (2018). Multiplex Biomarker Screening Assay for Urinary Extracellular Vesicles Study: A Targeted Label-Free Proteomic Approach. Scientific Reports. 8(1). 15039–15039. 40 indexed citations
11.
Kirley, Terence L., Kenneth D. Greis, & Andrew B. Norman. (2018). Domain unfolding of monoclonal antibody fragments revealed by non-reducing SDS-PAGE. Biochemistry and Biophysics Reports. 16. 138–144. 12 indexed citations
12.
Smith, Eric A., Anil G. Jegga, Ferdinand Kappes, et al.. (2017). The nuclear DEK interactome supports multi‐functionality. Proteins Structure Function and Bioinformatics. 86(1). 88–97. 17 indexed citations
13.
Kirley, Terence L., Kenneth D. Greis, & Andrew B. Norman. (2016). Selective disulfide reduction for labeling and enhancement of Fab antibody fragments. Biochemical and Biophysical Research Communications. 480(4). 752–757. 24 indexed citations
14.
Orsborn, Kris I., Minlu Zhang, Kenneth D. Greis, et al.. (2013). Heparin-Binding Motifs and Biofilm Formation by Candida albicans. The Journal of Infectious Diseases. 208(10). 1695–1704. 30 indexed citations
15.
Kattamuri, Chandramohan, Kristof Nolan, Scott A. Rankin, et al.. (2012). Members of the DAN Family Are BMP Antagonists That Form Highly Stable Noncovalent Dimers. Journal of Molecular Biology. 424(5). 313–327. 44 indexed citations
16.
Piyaphanee, Nuntawan, Qing Ma, Kimberly A. Czech, et al.. (2011). Discovery and initial validation of α 1‐B glycoprotein fragmentation as a differential urinary biomarker in pediatric steroid‐resistant nephrotic syndrome. PROTEOMICS - CLINICAL APPLICATIONS. 5(5-6). 334–342. 36 indexed citations
17.
Thompson, Larry J., et al.. (2003). Proteome analysis of the rat cornea during angiogenesis. PROTEOMICS. 3(11). 2258–2266. 21 indexed citations
18.
Isfort, Robert J., Kenneth D. Greis, Yiping Sun, et al.. (2002). Proteomic analysis of rat soleus muscle undergoing hindlimb suspension-induced atrophy and reweighting hypertrophy. PROTEOMICS. 2(5). 543–550. 68 indexed citations
19.
20.
Fry, David W., Alexander J. Bridges, William A. Denny, et al.. (1998). Specific, irreversible inactivation of the epidermal growth factor receptor and erbB2, by a new class of tyrosine kinase inhibitor. Proceedings of the National Academy of Sciences. 95(20). 12022–12027. 344 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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