Stephen Kacir

576 total citations
9 papers, 400 citations indexed

About

Stephen Kacir is a scholar working on Genetics, Hematology and Pathology and Forensic Medicine. According to data from OpenAlex, Stephen Kacir has authored 9 papers receiving a total of 400 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Genetics, 6 papers in Hematology and 5 papers in Pathology and Forensic Medicine. Recurrent topics in Stephen Kacir's work include Coagulation, Bradykinin, Polyphosphates, and Angioedema (6 papers), Platelet Disorders and Treatments (5 papers) and Autoimmune Bullous Skin Diseases (5 papers). Stephen Kacir is often cited by papers focused on Coagulation, Bradykinin, Polyphosphates, and Angioedema (6 papers), Platelet Disorders and Treatments (5 papers) and Autoimmune Bullous Skin Diseases (5 papers). Stephen Kacir collaborates with scholars based in United States, Japan and South Korea. Stephen Kacir's co-authors include Don L. Siegel, Aimee Payne, John R. Stanley, Ken Ishii, Chenyan Lin, Yasushi Hanakawa, Masayuki Amagai, Kazuyuki Tsunoda, Hong Li and Jun Yamagami and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Clinical Investigation and Blood.

In The Last Decade

Stephen Kacir

9 papers receiving 394 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Stephen Kacir United States 7 264 227 184 97 89 9 400
Mong-Shang Lin United States 10 231 0.9× 164 0.7× 164 0.9× 44 0.5× 33 0.4× 17 308
Marie-Laure Golinski France 8 96 0.4× 49 0.2× 66 0.4× 19 0.2× 97 1.1× 18 234
H. Yesid Estupiñán Colombia 8 138 0.5× 206 0.9× 14 0.1× 65 0.7× 90 1.0× 18 314
Nancy L. Farner United States 7 46 0.2× 56 0.2× 62 0.3× 27 0.3× 268 3.0× 7 355
Amy Goodrich United States 7 397 1.5× 386 1.7× 11 0.1× 82 0.8× 206 2.3× 14 561
Haowei Wang United States 9 26 0.1× 33 0.1× 100 0.5× 19 0.2× 258 2.9× 11 354
Miriam E. Thomas Australia 6 87 0.3× 135 0.6× 10 0.1× 40 0.4× 192 2.2× 10 344
D. Janson United States 7 180 0.7× 260 1.1× 6 0.0× 75 0.8× 131 1.5× 9 336
Angelina Bisconte United States 8 98 0.4× 129 0.6× 12 0.1× 76 0.8× 50 0.6× 12 240
Rozenn Le Corre France 11 28 0.1× 23 0.1× 80 0.4× 28 0.3× 174 2.0× 21 304

Countries citing papers authored by Stephen Kacir

Since Specialization
Citations

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

Fields of papers citing papers by Stephen Kacir

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Stephen Kacir

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

All Works

9 of 9 papers shown
1.
Ostertag, Eric, Khalil Bdeir, Stephen Kacir, et al.. (2016). ADAMTS13 autoantibodies cloned from patients with acquired thrombotic thrombocytopenic purpura: 2. Pathogenicity in an animal model. Transfusion. 56(7). 1775–1785. 16 indexed citations
2.
3.
Hu, Wenbing, Jian‐Hua Mao, Ruinan Lu, et al.. (2015). High-resolution epitope mapping by HX MS reveals the pathogenic mechanism and a possible therapy for autoimmune TTP syndrome. Proceedings of the National Academy of Sciences. 112(31). 9620–9625. 46 indexed citations
4.
Hammers, Christoph M., Jing Chen, Chenyan Lin, et al.. (2014). Persistence of Anti-Desmoglein 3 IgG+ B-Cell Clones in Pemphigus Patients over Years. Journal of Investigative Dermatology. 135(3). 742–749. 65 indexed citations
5.
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Yamagami, Jun, Aimee Payne, Stephen Kacir, et al.. (2010). Homologous regions of autoantibody heavy chain complementarity-determining region 3 (H-CDR3) in patients with pemphigus cause pathogenicity. Journal of Clinical Investigation. 120(11). 4111–4117. 42 indexed citations
7.
Yamagami, Jun, Stephen Kacir, Ken Ishii, et al.. (2009). Antibodies to the Desmoglein 1 Precursor Proprotein but Not to the Mature Cell Surface Protein Cloned from Individuals without Pemphigus. The Journal of Immunology. 183(9). 5615–5621. 25 indexed citations
8.
Payne, Aimee, Ken Ishii, Stephen Kacir, et al.. (2005). Genetic and functional characterization of human pemphigus vulgaris monoclonal autoantibodies isolated by phage display. Journal of Clinical Investigation. 115(4). 888–899. 173 indexed citations
9.
Payne, Aimee, Ken J. Ishii, Stephen Kacir, et al.. (2005). Genetic and functional characterization of human pemphigus vulgaris monoclonal autoantibodies isolated by phage display. Journal of Clinical Investigation. 115(4). 888–899. 4 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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