Matthew J. Schipma

2.7k total citations
53 papers, 1.7k citations indexed

About

Matthew J. Schipma is a scholar working on Molecular Biology, Immunology and Cancer Research. According to data from OpenAlex, Matthew J. Schipma has authored 53 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Molecular Biology, 12 papers in Immunology and 9 papers in Cancer Research. Recurrent topics in Matthew J. Schipma's work include Vibrio bacteria research studies (4 papers), Erythrocyte Function and Pathophysiology (3 papers) and MicroRNA in disease regulation (3 papers). Matthew J. Schipma is often cited by papers focused on Vibrio bacteria research studies (4 papers), Erythrocyte Function and Pathophysiology (3 papers) and MicroRNA in disease regulation (3 papers). Matthew J. Schipma collaborates with scholars based in United States, France and Philippines. Matthew J. Schipma's co-authors include Edward B. Thorp, Navdeep S. Chandel, Samuel E. Weinberg, Issam Ben‐Sahra, Anastasiia Gainullina, Shuang Zhang, Jason M. Kinchen, Matthew DeBerge, Laurent Yvan‐Charvet and David Gius and has published in prestigious journals such as Nature, Science and Proceedings of the National Academy of Sciences.

In The Last Decade

Matthew J. Schipma

51 papers receiving 1.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Matthew J. Schipma United States 22 653 376 355 231 166 53 1.7k
Isabel Pintelon Belgium 29 804 1.2× 327 0.9× 262 0.7× 295 1.3× 322 1.9× 129 2.5k
Jun Udagawa Japan 21 464 0.7× 221 0.6× 273 0.8× 260 1.1× 313 1.9× 67 1.6k
Sergio González Chile 23 789 1.2× 745 2.0× 239 0.7× 159 0.7× 194 1.2× 60 1.9k
Zbigniew Zasłona United States 23 798 1.2× 446 1.2× 786 2.2× 314 1.4× 146 0.9× 44 2.1k
Christiane Guillermet France 13 448 0.7× 277 0.7× 271 0.8× 178 0.8× 106 0.6× 14 1.4k
Harold W. Davis United States 18 621 1.0× 488 1.3× 232 0.7× 479 2.1× 188 1.1× 41 1.7k
Andrea Mesaros Germany 11 371 0.6× 470 1.3× 256 0.7× 325 1.4× 125 0.8× 17 1.3k
Dong‐Ming Su United States 27 832 1.3× 278 0.7× 909 2.6× 133 0.6× 148 0.9× 49 2.3k
Li Ding China 24 548 0.8× 172 0.5× 169 0.5× 87 0.4× 157 0.9× 86 1.3k
Paul Potter United Kingdom 25 572 0.9× 404 1.1× 543 1.5× 79 0.3× 95 0.6× 64 2.0k

Countries citing papers authored by Matthew J. Schipma

Since Specialization
Citations

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

Fields of papers citing papers by Matthew J. Schipma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matthew J. Schipma. 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 Matthew J. Schipma. The network helps show where Matthew J. Schipma may publish in the future.

Co-authorship network of co-authors of Matthew J. Schipma

This figure shows the co-authorship network connecting the top 25 collaborators of Matthew J. Schipma. A scholar is included among the top collaborators of Matthew J. Schipma 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 Matthew J. Schipma. Matthew J. Schipma 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.
Tiwari, Ratnakar, Rajni Sharma, Ganeshkumar Rajendran, et al.. (2024). Postischemic inactivation of HIF prolyl hydroxylases in endothelium promotes maladaptive kidney repair by inducing glycolysis. Journal of Clinical Investigation. 135(3). 8 indexed citations
2.
Cannon, Mark, et al.. (2024). Whole-Genome Deep Sequencing of the Healthy Adult Nasal Microbiome. Microorganisms. 12(7). 1407–1407.
3.
Schipma, Matthew J., et al.. (2024). Uterine pathology and microbiome among patients with endometrial polyps and fibroids. PubMed. 6(1). 107–116. 1 indexed citations
4.
Shapiro, Jason, Yihan Chen, Matthew J. Schipma, et al.. (2023). DNA Damage and Nuclear Morphological Changes in Cardiac Hypertrophy Are Mediated by SNRK Through Actin Depolymerization. Circulation. 148(20). 1582–1592. 4 indexed citations
5.
Tiwari, Ratnakar, Prashant Bommi, Peng Gao, et al.. (2022). Chemical inhibition of oxygen-sensing prolyl hydroxylases impairs angiogenic competence of human vascular endothelium through metabolic reprogramming. iScience. 25(10). 105086–105086. 4 indexed citations
6.
Dodiya, Hemraj B., Holly L. Lutz, Priyam Patel, et al.. (2021). Gut microbiota–driven brain Aβ amyloidosis in mice requires microglia. The Journal of Experimental Medicine. 219(1). 77 indexed citations
7.
Wong, Winifred P.S., et al.. (2021). Cadmium-mediated pancreatic islet transcriptome changes in mice and cultured mouse islets. Toxicology and Applied Pharmacology. 433. 115756–115756. 9 indexed citations
8.
Jung, Seung Ho, Matthew J. Schipma, Patrick H. Lim, et al.. (2020). Strain Differences in Responsiveness to Repeated Restraint Stress Affect Remote Contextual Fear Memory and Blood Transcriptomics. Neuroscience. 444. 76–91. 7 indexed citations
9.
10.
Murmann, Andrea E., et al.. (2019). 6mer Seed Toxicity in Viral microRNAs. iScience. 23(2). 100737–100737. 9 indexed citations
11.
Zhang, Shuang, Samuel E. Weinberg, Matthew DeBerge, et al.. (2018). Efferocytosis Fuels Requirements of Fatty Acid Oxidation and the Electron Transport Chain to Polarize Macrophages for Tissue Repair. Cell Metabolism. 29(2). 443–456.e5. 319 indexed citations
12.
Zhao, Baobing, Yang Mei, Lan Cao, et al.. (2017). Loss of pleckstrin-2 reverts lethality and vascular occlusions in JAK2V617F-positive myeloproliferative neoplasms. Journal of Clinical Investigation. 128(1). 125–140. 30 indexed citations
13.
Zhao, Baobing, Yang Mei, Matthew J. Schipma, et al.. (2016). Nuclear Condensation during Mouse Erythropoiesis Requires Caspase-3-Mediated Nuclear Opening. Developmental Cell. 36(5). 498–510. 74 indexed citations
14.
Chowdhury, Basudev, Elizabeth G. Porter, Jane C. Stewart, et al.. (2016). PBRM1 Regulates the Expression of Genes Involved in Metabolism and Cell Adhesion in Renal Clear Cell Carcinoma. PLoS ONE. 11(4). e0153718–e0153718. 70 indexed citations
15.
Jia, Yuzhi, Hsiang‐Chun Chang, Matthew J. Schipma, et al.. (2016). Cardiomyocyte-Specific Ablation of Med1 Subunit of the Mediator Complex Causes Lethal Dilated Cardiomyopathy in Mice. PLoS ONE. 11(8). e0160755–e0160755. 28 indexed citations
16.
Perelis, Mark, Biliana Marcheva, Kathryn Moynihan Ramsey, et al.. (2015). Pancreatic β cell enhancers regulate rhythmic transcription of genes controlling insulin secretion. Science. 350(6261). aac4250–aac4250. 291 indexed citations
17.
Manzano, Mark, Eleonora Forte, Archana N. Raja, Matthew J. Schipma, & Eva Gottwein. (2015). Divergent target recognition by coexpressed 5′-isomiRs of miR-142-3p and selective viral mimicry. RNA. 21(9). 1606–1620. 32 indexed citations
18.
Zhao, Baobing, et al.. (2014). Nuclear Condensation during Mouse Erythropoiesis Requires Caspase-3 Mediated Nuclear Opening Formation. Blood. 124(21). 448–448. 1 indexed citations
19.
Belmadani, Abdelhak, et al.. (2004). Inhibition of amyloid-β-induced neurotoxicity and apoptosis by moderate ethanol preconditioning. Neuroreport. 15(13). 2093–2096. 48 indexed citations
20.

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

Breakdown of academic impact, for papers by Isabel Pintelon Breakdown of academic impact, for papers by Jun Udagawa Breakdown of academic impact, for papers by Sergio González Breakdown of academic impact, for papers by Zbigniew Zasłona Breakdown of academic impact, for papers by Christiane Guillermet Breakdown of academic impact, for papers by Harold W. Davis Breakdown of academic impact, for papers by Andrea Mesaros Breakdown of academic impact, for papers by Dong‐Ming Su Breakdown of academic impact, for papers by Li Ding Breakdown of academic impact, for papers by Paul Potter
Rankless by CCL
2026