J. Shan

473 total citations
11 papers, 332 citations indexed

About

J. Shan is a scholar working on Hematology, Genetics and Equine. According to data from OpenAlex, J. Shan has authored 11 papers receiving a total of 332 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Hematology, 6 papers in Genetics and 4 papers in Equine. Recurrent topics in J. Shan's work include Acute Myeloid Leukemia Research (5 papers), Chronic Lymphocytic Leukemia Research (4 papers) and Veterinary Equine Medical Research (4 papers). J. Shan is often cited by papers focused on Acute Myeloid Leukemia Research (5 papers), Chronic Lymphocytic Leukemia Research (4 papers) and Veterinary Equine Medical Research (4 papers). J. Shan collaborates with scholars based in United States, China and New Zealand. J. Shan's co-authors include Jörge E. Cortes, William G. Wierda, Hagop M. Kantarjian, Elihu H. Estey, Gautam Borthakur, Xuelin Huang, Guillermo Garcia‐Manero, S. Faderl, Farhad Ravandi and Sherry Pierce and has published in prestigious journals such as Journal of Clinical Oncology, Leukemia and Haematologica.

In The Last Decade

J. Shan

11 papers receiving 326 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
J. Shan United States 5 312 173 59 58 37 11 332
Barbara Rocca Italy 9 274 0.9× 127 0.7× 52 0.9× 86 1.5× 19 0.5× 21 310
Marilena Caresana Italy 10 276 0.9× 131 0.8× 53 0.9× 89 1.5× 18 0.5× 20 314
Seo Ej South Korea 5 277 0.9× 68 0.4× 153 2.6× 23 0.4× 35 0.9× 5 297
Ann Figes United Kingdom 4 290 0.9× 127 0.7× 20 0.3× 52 0.9× 32 0.9× 5 331
DA Galton United Kingdom 6 395 1.3× 262 1.5× 78 1.3× 41 0.7× 91 2.5× 11 431
D. Snyder United States 6 302 1.0× 100 0.6× 102 1.7× 65 1.1× 44 1.2× 10 350
Adriano Salaroli Italy 11 182 0.6× 130 0.8× 12 0.2× 36 0.6× 26 0.7× 29 251
Bernardine Favre France 8 129 0.4× 73 0.4× 26 0.4× 72 1.2× 31 0.8× 14 187
Carmen Sanzo Spain 5 166 0.5× 84 0.5× 48 0.8× 48 0.8× 7 0.2× 5 211
Kristina Schilling Germany 7 228 0.7× 109 0.6× 15 0.3× 55 0.9× 20 0.5× 14 267

Countries citing papers authored by J. Shan

Since Specialization
Citations

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

Fields of papers citing papers by J. Shan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of J. Shan

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

All Works

11 of 11 papers shown
1.
Gedye, Kristene, et al.. (2024). Evaluation of Two Commercial ELISA Kits for Measuring Equine Serum Gastrin Compared to Radioimmunoassay. Animals. 14(20). 2937–2937. 1 indexed citations
3.
4.
Shan, J., et al.. (2021). Stress fracture of the palmar, distal cortex of the third metacarpal bone: A diagnostic challenge with a good prognosis. Equine Veterinary Journal. 54(1). 74–81. 2 indexed citations
5.
Kantarjian, Hagop, J. Shan, Alfonso Quintás‐Cardama, et al.. (2012). Analysis of outcomes in adolescents and young adults with chronic myelogenous leukemia treated with upfront tyrosine kinase inhibitor therapy. Haematologica. 97(7). 1029–1035. 63 indexed citations
6.
Becker, Pamela S., Hagop M. Kantarjian, Frederick R. Appelbaum, et al.. (2012). Retrospective comparison of clofarabine versus fludarabine in combination with high-dose cytarabine with or without granulocyte colony-stimulating factor as salvage therapies for acute myeloid leukemia. Haematologica. 98(1). 114–118. 16 indexed citations
7.
Quintás‐Cardama, Alfonso, Hagop M. Kantarjian, S O'Brien, et al.. (2011). Outcome of patients with chronic myeloid leukemia with multiple ABL1 kinase domain mutations receiving tyrosine kinase inhibitor therapy. Haematologica. 96(6). 918–924. 16 indexed citations
8.
O’Brien, Susan, Farhad Ravandi, Jörge E. Cortes, et al.. (2008). Proposal for a new risk model in myelodysplastic syndrome (MDS) that accounts for events not considered in the original International Prognostic Scoring System (IPSS). Journal of Clinical Oncology. 26(15_suppl). 7029–7029. 1 indexed citations
9.
Garcia‐Manero, Guillermo, J. Shan, S. Faderl, et al.. (2007). A prognostic score for patients with lower risk myelodysplastic syndrome. Leukemia. 22(3). 538–543. 222 indexed citations
10.
Issa, Jean‐Pierre J., et al.. (2007). Decitabine in older patients with acute myelogenous leukemia (AML). Journal of Clinical Oncology. 25(18_suppl). 7021–7021. 2 indexed citations
11.
Solh, Melhem, Hagop M. Kantarjian, Stephen J. O’Brien, et al.. (2007). Central nervous system (CNS) leukemia after imatinib mesylate therapy for chronic myelogenous leukemia (CML). Journal of Clinical Oncology. 25(18_suppl). 7042–7042. 1 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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