Dana Krämer

672 total citations
9 papers, 419 citations indexed

About

Dana Krämer is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Physiology. According to data from OpenAlex, Dana Krämer has authored 9 papers receiving a total of 419 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 4 papers in Cellular and Molecular Neuroscience and 2 papers in Physiology. Recurrent topics in Dana Krämer's work include Signaling Pathways in Disease (3 papers), Cancer, Hypoxia, and Metabolism (2 papers) and Adipose Tissue and Metabolism (2 papers). Dana Krämer is often cited by papers focused on Signaling Pathways in Disease (3 papers), Cancer, Hypoxia, and Metabolism (2 papers) and Adipose Tissue and Metabolism (2 papers). Dana Krämer collaborates with scholars based in Italy, United Kingdom and United States. Dana Krämer's co-authors include Liliana Minichiello, Ning Dai, Ari Waisman, Thorsten Buch, George Kollias, Joseph Avruch, Hans Lassmann, Nadine Hövelmeyer, George Kassiotis and Friederike Frommer and has published in prestigious journals such as Journal of Biological Chemistry, Nature Communications and The Journal of Immunology.

In The Last Decade

Dana Krämer

9 papers receiving 410 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Dana Krämer Italy	7	226	91	70	70	64	9	419
Cécile Couriaud France	8	368 1.6×	65 0.7×	67 1.0×	48 0.7×	74 1.2×	8	531
Andreas Lipski Germany	7	332 1.5×	64 0.7×	52 0.7×	34 0.5×	67 1.0×	10	500
Baole Zhang China	13	240 1.1×	98 1.1×	73 1.0×	72 1.0×	58 0.9×	29	436
Hannelore Burkhardt Germany	12	350 1.5×	35 0.4×	64 0.9×	67 1.0×	24 0.4×	14	514
Kyoungjoo Cho South Korea	10	149 0.7×	47 0.5×	90 1.3×	36 0.5×	79 1.2×	25	340
Guanrong Huang China	10	246 1.1×	37 0.4×	38 0.5×	38 0.5×	22 0.3×	16	453
Shengyi Peng China	10	379 1.7×	53 0.6×	47 0.7×	50 0.7×	50 0.8×	11	608
Tantai Zhao China	9	191 0.8×	45 0.5×	58 0.8×	24 0.3×	37 0.6×	18	396
Xiaofeng Zhao United States	11	154 0.7×	35 0.4×	88 1.3×	109 1.6×	161 2.5×	24	458

Countries citing papers authored by Dana Krämer

Since Specialization

Citations

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

Fields of papers citing papers by Dana Krämer

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dana Krämer

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

All Works

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9 of 9 papers shown

Regué, Laura, Fei Ji, Daniel Flicker, et al.. (2019). IMP2 Increases Mouse Skeletal Muscle Mass and Voluntary Activity by Enhancing Autocrine Insulin-Like Growth Factor 2 Production and Optimizing Muscle Metabolism. Molecular and Cellular Biology. 39(7). 11 indexed citations

Dai, Ning, Liping Zhao, Diedra M. Wrighting, et al.. (2015). IGF2BP2/IMP2-Deficient Mice Resist Obesity through Enhanced Translation of Ucp1 mRNA and Other mRNAs Encoding Mitochondrial Proteins. Cell Metabolism. 21(4). 609–621. 142 indexed citations

Besusso, Dario, Dana Krämer, Tomasz Schneider, et al.. (2013). BDNF–TrkB signaling in striatopallidal neurons controls inhibition of locomotor behavior. Nature Communications. 4(1). 2031–2031. 36 indexed citations

Krämer, Dana & Liliana Minichiello. (2010). Cell Culture of Primary Cerebellar Granule Cells. Methods in molecular biology. 633. 233–239. 37 indexed citations

Hövelmeyer, Nadine, Zhenyue Hao, Ksanthi Kranidioti, et al.. (2005). Apoptosis of Oligodendrocytes via Fas and TNF-R1 Is a Key Event in the Induction of Experimental Autoimmune Encephalomyelitis. The Journal of Immunology. 175(9). 5875–5884. 137 indexed citations

Krämer, Dana, Alessandra Caruso, Ferdinando Nicoletti, & Armando A. Genazzani. (2005). Somatostatin and the somatostatin receptor 2 are reciprocally controlled by calcineurin during cerebellar granule cell maturation. Journal of Neurochemistry. 94(5). 1374–1383. 4 indexed citations

Krämer, Dana, et al.. (2003). Calcineurin controls the expression of numerous genes in cerebellar granule cells. Molecular and Cellular Neuroscience. 23(2). 325–330. 25 indexed citations

Sanna, Bastiano, Dana Krämer, & Armando A. Genazzani. (2002). The Expression of the PDZ Protein MALS-1/Velis Is Regulated by Calcium and Calcineurin in Cerebellar Granule Cells. Journal of Biological Chemistry. 277(51). 49585–49590. 1 indexed citations

Mixner, J.P., et al.. (1962). Effects of Breed, Stage of Lactation, and Season of Year on Thyroid Secretion Rate of Dairy Cows as Determined by the Chemical Thyroxine Turnover Method. Journal of Dairy Science. 45(8). 999–1002. 26 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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