R Pullmann

3.4k citations
47 papers · 2.6k · h-index 21

Impact in

Papers in

R Pullmann

47 papers receiving 2.6k citations

Peers

R Pullmann
Comparison fields: 5 of 102
  • Cancer Research 650
  • Geriatrics and Gerontology 146
  • Molecular Biology 1.7k
  • Immunology 396
  • Aging 31
Replace Xudong Liao with:
Xudong Liao United States
Vanessa Byles United States
Alessandro Cama Italy
Jessica L. Yecies United States
Xueyuan Bai China
Beixue Gao United States
Qihuang Jin China
Fawzia Bardag‐Gorce United States
Sophie Nadaud France
R Pullmann relative to Xudong Liao United States Xudong Liao's profile →
Citations per field
00.5×1.5×2.4×
Xudong Liao · 1×
Citations per year

Countries citing papers authored by R Pullmann

Since Specialization
Citations

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

Fields of papers citing papers by R Pullmann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside R Pullmann, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with R Pullmann Line = papers co-authored together R Pullmann links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 47 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2007462
2 2007243
3 2008227
4 2008186
5 2008178
6 2007176
7 2002158
8 2006110
9 2009105
10 200996
11 200683
12 200767
13 200565
14 200662
15
Cytotoxic T lymphocyte antigen 4 (CTLA-4) dimorphism in patients with systemic lupus erythematosus.
200052
16 200551
17 200845
18 200638
19
Association between systemic lupus erythematosus and insertion/deletion polymorphism of the angiotensin converting enzyme (ACE) gene.
199937
20 201226

About R Pullmann

R Pullmann is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine, Physiology, Endocrine and Autonomic Systems and Rheumatology, having authored 47 papers that have together received 2.6k indexed citations. Recurring topics across this work include RNA Research and Splicing (12 papers), RNA modifications and cancer (6 papers), Systemic Lupus Erythematosus Research (5 papers), Neuroscience of respiration and sleep (5 papers), Respiratory Support and Mechanisms (4 papers), RNA regulation and disease (4 papers), Neonatal Respiratory Health Research (3 papers) and Pediatric health and respiratory diseases (2 papers). The work is most often cited by research in Cancer Research (650 citations), Geriatrics and Gerontology (146 citations), Molecular Biology (1.7k citations), Immunology (396 citations) and Aging (31 citations). R Pullmann has collaborated with scholars based in Slovakia, United States and Hungary. Frequent co-authors include Myriam Gorospe, Kotb Abdelmohsen, Xiaoling Yang, Ashish Lal, Hyeon Ho Kim, Jennifer L. Martindale, Stefanie Galbán, Yuki Kuwano, Justin D. Blethrow and Paul E. M. Phillips. Their work appears in journals such as Molecular and Cellular Biology, Journal of Biological Chemistry, Molecular Cell, Clinical Rheumatology and Advances in experimental medicine and biology.

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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