Michael Schuler

1.2k total citations
18 papers, 778 citations indexed

About

Michael Schuler is a scholar working on Molecular Biology, Genetics and Immunology. According to data from OpenAlex, Michael Schuler has authored 18 papers receiving a total of 778 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 5 papers in Genetics and 4 papers in Immunology. Recurrent topics in Michael Schuler's work include CRISPR and Genetic Engineering (4 papers), Virus-based gene therapy research (3 papers) and Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis (3 papers). Michael Schuler is often cited by papers focused on CRISPR and Genetic Engineering (4 papers), Virus-based gene therapy research (3 papers) and Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis (3 papers). Michael Schuler collaborates with scholars based in Germany, France and United Kingdom. Michael Schuler's co-authors include Daniel Metzger, Pierre Chambon, Dirk Pette, Jean‐Marc Bornert, Béatrice Desvergne, Walter Wahli, Céline Chambon, Delphine Duteil, Heidemarie Peuker and Frank Jaschinski and has published in prestigious journals such as Cell Metabolism, Scientific Reports and The FASEB Journal.

In The Last Decade

Michael Schuler

18 papers receiving 769 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michael Schuler Germany 12 508 295 104 97 68 18 778
Sabrina Ben Larbi France 10 558 1.1× 145 0.5× 59 0.6× 65 0.7× 26 0.4× 17 854
Luca Mendler Hungary 18 708 1.4× 161 0.5× 149 1.4× 29 0.3× 140 2.1× 28 903
Sigrun Ressler Austria 11 305 0.6× 282 1.0× 86 0.8× 52 0.5× 20 0.3× 19 798
Paul Kogut United States 16 511 1.0× 268 0.9× 137 1.3× 168 1.7× 82 1.2× 21 918
Lucia Latella Italy 16 1.2k 2.3× 264 0.9× 108 1.0× 35 0.4× 36 0.5× 27 1.3k
Amir Aghajanian United States 11 295 0.6× 130 0.4× 82 0.8× 76 0.8× 61 0.9× 15 627
Nora Yucel United States 9 418 0.8× 158 0.5× 75 0.7× 22 0.2× 59 0.9× 11 578
Yukiko Kitase United States 16 513 1.0× 224 0.8× 87 0.8× 22 0.2× 34 0.5× 27 802
Hanzhou Wang China 17 503 1.0× 98 0.3× 92 0.9× 67 0.7× 22 0.3× 57 820
Anne Rochat France 12 566 1.1× 87 0.3× 89 0.9× 127 1.3× 48 0.7× 14 735

Countries citing papers authored by Michael Schuler

Since Specialization
Citations

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

Fields of papers citing papers by Michael Schuler

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael Schuler

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

All Works

18 of 18 papers shown
1.
Kasmi, Karim C. El, et al.. (2023). Application of human iPSC-derived macrophages in a miniaturized high-content-imaging-based efferocytosis assay. SLAS DISCOVERY. 28(4). 149–162. 4 indexed citations
2.
Garrido‐Martín, Eva M., Łukasz M. Boryń, Praveen Baskaran, et al.. (2023). Complementary CRISPR screen highlights the contrasting role of membrane-bound and soluble ICAM-1 in regulating antigen-specific tumor cell killing by cytotoxic T cells. eLife. 12. 8 indexed citations
3.
Weinmann, Jonas, Gudrun Zimmermann, Christine Mayer, et al.. (2022). Identification of Broadly Applicable Adeno-Associated Virus Vectors by Systematic Comparison of Commonly Used Capsid Variants In Vitro. Human Gene Therapy. 33(21-22). 1197–1212. 3 indexed citations
4.
Schönberger, Tanja, Benjamin Strobel, Birgit Stierstorfer, et al.. (2022). Rosa26-LSL-dCas9-VPR: a versatile mouse model for tissue specific and simultaneous activation of multiple genes for drug discovery. Scientific Reports. 12(1). 19268–19268. 2 indexed citations
5.
Garrido‐Martín, Eva M., et al.. (2021). A genome-wide CRISPR/Cas9 screen to identify phagocytosis modulators in monocytic THP-1 cells. Scientific Reports. 11(1). 12973–12973. 14 indexed citations
6.
Schuler, Michael, et al.. (2020). Phagocytosis Assays with Different pH-Sensitive Fluorescent Particles and Various Readouts. BioTechniques. 68(5). 245–250. 27 indexed citations
7.
Schruf, Eva, Huy Quang Le, Tanja Schönberger, et al.. (2020). Recapitulating idiopathic pulmonary fibrosis related alveolar epithelial dysfunction in a human iPSC‐derived air‐liquid interface model. The FASEB Journal. 34(6). 7825–7846. 31 indexed citations
8.
Nan, Xinsheng, Pedro Chacón, Lothar Kußmaul, et al.. (2019). A New Mouse Line Reporting the Translation of Brain-Derived Neurotrophic Factor Using Green Fluorescent Protein. eNeuro. 7(1). ENEURO.0462–19.2019. 9 indexed citations
9.
Schruf, Eva, Christian A. Kuttruff, Tom Bretschneider, et al.. (2019). Human lung fibroblast-to-myofibroblast transformation is not driven by an LDH5-dependent metabolic shift towards aerobic glycolysis. Respiratory Research. 20(1). 87–87. 32 indexed citations
10.
Garrido‐Martín, Eva M., et al.. (2019). Primary cell-based phenotypic assays to pharmacologically and genetically study fibrotic diseases in vitro. Journal of Biological Methods. 6(2). 1–1. 14 indexed citations
11.
Strobel, Benjamin, et al.. (2017). Comparative analysis of lysyl oxidase (like) family members in pulmonary fibrosis. Scientific Reports. 7(1). 149–149. 99 indexed citations
12.
Schuler, Michael, Céline Chambon, Delphine Duteil, et al.. (2006). PGC1α expression is controlled in skeletal muscles by PPARβ, whose ablation results in fiber-type switching, obesity, and type 2 diabetes. Cell Metabolism. 4(5). 407–414. 303 indexed citations
13.
Schuler, Michael, et al.. (2005). Temporally controlled targeted somatic mutagenesis in skeletal muscles of the mouse. genesis. 41(4). 165–170. 80 indexed citations
14.
Weber, Philipp, Michael Schuler, Christelle Gérard, et al.. (2003). Temporally Controlled Site-Specific Mutagenesis in the Germ Cell Lineage of the Mouse Testis1. Biology of Reproduction. 68(2). 553–559. 19 indexed citations
15.
Schuler, Michael, et al.. (1999). Effects of contractile activity and hypothyroidism on nuclear hormone receptor mRNA isoforms in rat skeletal muscle. European Journal of Biochemistry. 264(3). 982–988. 6 indexed citations
17.
Jaschinski, Frank, Michael Schuler, Heidemarie Peuker, & Dirk Pette. (1998). Changes in myosin heavy chain mRNA and protein isoforms of rat muscle during forced contractile activity. American Journal of Physiology-Cell Physiology. 274(2). C365–C370. 84 indexed citations
18.
Schuler, Michael & Dirk Pette. (1996). Fiber transformation and replacement in low-frequency stimulated rabbit fast-twitch muscles. Cell and Tissue Research. 285(2). 297–303. 27 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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