S. Kelly

754 citations
12 papers · 541 indexed · h-index 5

S. Kelly

12 papers receiving 518 citations

Peers

S. Kelly
Comparison fields: 5 of 74
  • Rheumatology 351
  • Immunology 225
  • Radiology, Nuclear Medicine and Imaging 160
  • Hematology 76
  • Genetics 49
Replace Kalle Aaltonen with:
Kalle Aaltonen Finland
Jeffrey D. Greenberg United States
Ehab Mahgoub United States
Kenichiro Matoba Japan
Aleksandra Djoković Serbia
Е. Л. Насонов Russia
Mirit Amit-Vazina Israel
Jacqueline R. Chipping United Kingdom
Adam Young United Kingdom
Antonio G. Tristano Venezuela
S. Kelly relative to Kalle Aaltonen Finland Kalle Aaltonen's profile →
Citations per field
00.5×4.6×
Kalle Aaltonen · 1×
Citations per year

Countries citing papers authored by S. Kelly

Since Specialization
Citations

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

Fields of papers citing papers by S. Kelly

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside S. Kelly, 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 S. Kelly Line = papers co-authored together S. Kelly links everyone, so they are left out of the graph.

All Works

12 of 12 papers shown
#Work
1 20241
2 20172
3
De-Convolution of Whole Blood Transcriptomic Data From a Phase Jib, Randomized, Double-Blind, Placebo-Controlled Trial of Abatacept in Systemic Lupus Erythematosus
20161
4 20164
5 20162
6
De-Convolution of Whole Blood Transcriptomic Data from a Phase IIb, Randomized, Double-Blind, Placebo-Controlled Trial of Abatacept in Systemic Lupus Erythematosus
20151
7 20132
8 2010274
9 200977
10
The Efficacy and Safety of Abatacept in SLE: Results of a 12-month Exploratory Study
200815
11 2008123
12 199639

About S. Kelly

S. Kelly is a scholar working on Rheumatology, Radiology, Nuclear Medicine and Imaging and Pathology and Forensic Medicine, having authored 12 papers that have together received 541 indexed citations. Recurring topics across this work include Systemic Lupus Erythematosus Research (6 papers), Rheumatoid Arthritis Research and Therapies (5 papers), Monoclonal and Polyclonal Antibodies Research (4 papers), Lymphoma Diagnosis and Treatment (3 papers), Immunodeficiency and Autoimmune Disorders (2 papers), Chemokine receptors and signaling (2 papers), Cytokine Signaling Pathways and Interactions (2 papers) and Chronic Lymphocytic Leukemia Research (1 paper). The work is most often cited by research in Rheumatology (351 citations), Immunology (225 citations) and Radiology, Nuclear Medicine and Imaging (160 citations). S. Kelly has collaborated with scholars based in United States, Sweden and United Kingdom. Frequent co-authors include Sylvia Mitchell, Ian Lockhart, Peter Nash, René Westhovens, Andrew Chalmers, Leonard H. Sigal, Rubén Burgos‐Vargas, David D’Cruz, Sang‐Cheol Bae and Kartik Raghupathi. Their work appears in journals such as Annals of the Rheumatic Diseases, Clinical and Experimental Rheumatology, Dementia and Geriatric Cognitive Disorders, Queensland's institutional digital repository (The University of Queensland) and Arthritis & Rheumatism.

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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