C. Dall’Osso

1.6k total citations · 1 hit paper
8 papers, 1.2k citations indexed

About

C. Dall’Osso is a scholar working on Molecular Biology, Genetics and Pathology and Forensic Medicine. According to data from OpenAlex, C. Dall’Osso has authored 8 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 2 papers in Genetics and 2 papers in Pathology and Forensic Medicine. Recurrent topics in C. Dall’Osso's work include Muscle Physiology and Disorders (2 papers), Adipokines, Inflammation, and Metabolic Diseases (1 paper) and Cardiac Fibrosis and Remodeling (1 paper). C. Dall’Osso is often cited by papers focused on Muscle Physiology and Disorders (2 papers), Adipokines, Inflammation, and Metabolic Diseases (1 paper) and Cardiac Fibrosis and Remodeling (1 paper). C. Dall’Osso collaborates with scholars based in United States, Italy and Austria. C. Dall’Osso's co-authors include Amy J. Wagers, Manisha Sinha, Jennifer L. Shadrach, Britta Swebilius Singer, Pratyusha Yalamanchi, James R. Pancoast, Robert E. Gerszten, Mi‐Jeong Kim, Danika Khong and Christine M. Miller and has published in prestigious journals such as Cell, Cell Metabolism and Endocrinology.

In The Last Decade

C. Dall’Osso

8 papers receiving 1.1k citations

Hit Papers

Growth Differentiation Factor 11 Is a Circulating Factor ... 2013 2026 2017 2021 2013 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
C. Dall’Osso United States 8 653 349 172 157 132 8 1.2k
Angelika Meyer Switzerland 7 1.1k 1.6× 716 2.1× 127 0.7× 214 1.4× 125 0.9× 9 1.6k
Johanne V. Pastor United States 8 800 1.2× 552 1.6× 71 0.4× 153 1.0× 287 2.2× 10 2.7k
Shephali Bhatnagar United States 19 1.2k 1.9× 525 1.5× 119 0.7× 111 0.7× 100 0.8× 23 1.7k
Shingo Koyama Japan 22 424 0.6× 254 0.7× 122 0.7× 48 0.3× 224 1.7× 58 1.6k
Pascale Lause Belgium 20 1.1k 1.6× 662 1.9× 146 0.8× 121 0.8× 122 0.9× 35 1.6k
Bingwen Jin United States 14 1.2k 1.9× 448 1.3× 170 1.0× 54 0.3× 86 0.7× 17 1.6k
Shuichi Yatsuga Japan 18 1.5k 2.4× 442 1.3× 47 0.3× 290 1.8× 63 0.5× 50 2.0k
Scott M. MacDonnell United States 16 698 1.1× 177 0.5× 539 3.1× 97 0.6× 130 1.0× 28 1.2k
Shahriar Salamat United States 14 545 0.8× 230 0.7× 79 0.5× 33 0.2× 86 0.7× 48 1.2k
Ellen R. Lubbers United States 16 468 0.7× 867 2.5× 223 1.3× 29 0.2× 98 0.7× 22 1.5k

Countries citing papers authored by C. Dall’Osso

Since Specialization
Citations

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

Fields of papers citing papers by C. Dall’Osso

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by C. Dall’Osso. 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 C. Dall’Osso. The network helps show where C. Dall’Osso may publish in the future.

Co-authorship network of co-authors of C. Dall’Osso

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

All Works

8 of 8 papers shown
1.
Papaioannou, Garyfallia, Hengguang Zhao, Hilary F. Luderer, et al.. (2016). The Vitamin D Receptor Regulates Tissue Resident Macrophage Response to Injury. Endocrinology. 157(10). 4066–4075. 23 indexed citations
2.
Paraboschi, Elvezia Maria, Valeria Rimoldi, Giulia Soldà, et al.. (2014). Functional variations modulating PRKCA expression and alternative splicing predispose to multiple sclerosis. Human Molecular Genetics. 23(25). 6746–6761. 31 indexed citations
3.
Hettmer, Simone, Lisa A. Teot, Paul Van Hummelen, et al.. (2013). Mutations in Hedgehog pathway genes in fetal rhabdomyomas. The Journal of Pathology. 231(1). 44–52. 22 indexed citations
4.
Loffredo, Francesco S., Matthew L. Steinhauser, Steven M. Jay, et al.. (2013). Growth Differentiation Factor 11 Is a Circulating Factor that Reverses Age-Related Cardiac Hypertrophy. Cell. 153(4). 828–839. 699 indexed citations breakdown →
5.
Gemmati, Donato, Elisa Orioli, Fabrizio Salvi, et al.. (2012). Polymorphisms in the genes coding for iron binding and transporting proteins are associated with disability, severity, and early progression in multiple sclerosis. BMC Medical Genetics. 13(1). 70–70. 40 indexed citations
6.
Jang, Young C., Manisha Sinha, Massimiliano Cerletti, C. Dall’Osso, & Amy J. Wagers. (2011). Skeletal Muscle Stem Cells: Effects of Aging and Metabolism on Muscle Regenerative Function. Cold Spring Harbor Symposia on Quantitative Biology. 76(0). 101–111. 107 indexed citations
7.
Rask‐Madsen, Christian, Qian Li, I‐Hsien Wu, et al.. (2010). Loss of Insulin Signaling in Vascular Endothelial Cells Accelerates Atherosclerosis in Apolipoprotein E Null Mice. Cell Metabolism. 11(5). 379–389. 231 indexed citations
8.
Dall’Osso, C., Ilaria Guella, Stefano Duga, et al.. (2008). Molecular characterization of three novel splicing mutations causing factor V deficiency and analysis of the F5 gene splicing pattern. Haematologica. 93(10). 1505–1513. 16 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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