Jayashree Shanker

767 total citations
38 papers, 604 citations indexed

About

Jayashree Shanker is a scholar working on Immunology, Epidemiology and Molecular Biology. According to data from OpenAlex, Jayashree Shanker has authored 38 papers receiving a total of 604 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Immunology, 10 papers in Epidemiology and 9 papers in Molecular Biology. Recurrent topics in Jayashree Shanker's work include Atherosclerosis and Cardiovascular Diseases (10 papers), Adipokines, Inflammation, and Metabolic Diseases (8 papers) and Diabetes, Cardiovascular Risks, and Lipoproteins (7 papers). Jayashree Shanker is often cited by papers focused on Atherosclerosis and Cardiovascular Diseases (10 papers), Adipokines, Inflammation, and Metabolic Diseases (8 papers) and Diabetes, Cardiovascular Risks, and Lipoproteins (7 papers). Jayashree Shanker collaborates with scholars based in United Kingdom, India and United States. Jayashree Shanker's co-authors include Vijay V. Kakkar, Veena S. Rao, Shibu John, Madankumar Ghatge, Veena Rao, Debabrata Dash, Manjarí Mukherjee, Lakshmi Mundkur, Armen Yuri Gasparyan and George D. Kitas and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Thrombosis and Haemostasis.

In The Last Decade

Jayashree Shanker

38 papers receiving 567 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jayashree Shanker United Kingdom 17 169 137 135 125 109 38 604
Xiaoxi Zhang China 13 136 0.8× 126 0.9× 105 0.8× 76 0.6× 72 0.7× 19 572
Hitoshi Abiru Japan 10 136 0.8× 75 0.5× 190 1.4× 114 0.9× 132 1.2× 32 620
Ashley Beecham United States 17 174 1.0× 164 1.2× 74 0.5× 156 1.2× 80 0.7× 48 723
Jon Peter Durda United States 8 189 1.1× 133 1.0× 192 1.4× 78 0.6× 127 1.2× 11 602
Tetsuo Fujimaki Japan 16 333 2.0× 257 1.9× 89 0.7× 100 0.8× 126 1.2× 65 864
Natalia Wawrusiewicz‐Kurylonek Poland 20 194 1.1× 243 1.8× 136 1.0× 273 2.2× 148 1.4× 73 991
Eric Boerwinkle United States 8 91 0.5× 129 0.9× 72 0.5× 64 0.5× 197 1.8× 10 502
Nike Müller Germany 11 209 1.2× 50 0.4× 115 0.9× 95 0.8× 118 1.1× 15 571
Zhan Lü China 13 210 1.2× 67 0.5× 90 0.7× 38 0.3× 133 1.2× 26 617
Pelayo González Spain 16 211 1.2× 88 0.6× 63 0.5× 128 1.0× 95 0.9× 23 698

Countries citing papers authored by Jayashree Shanker

Since Specialization
Citations

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

Fields of papers citing papers by Jayashree Shanker

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jayashree Shanker

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

All Works

20 of 20 papers shown
1.
Wright, Paul, Dejana Pejak Simunec, Jayashree Shanker, et al.. (2024). A comprehensive study on the biodegradability, biocompatibility, and antibacterial properties of additively manufactured PLA-ZnO nanocomposites. SHILAP Revista de lepidopterología. 3. 100069–100069. 4 indexed citations
2.
3.
Shanker, Jayashree & Vijay V. Kakkar. (2016). Contribution of classical and emerging risk factors to coronary artery disease in Asian Indians. International Journal of Cardiology. 214. 97–106. 7 indexed citations
4.
5.
Shanker, Jayashree, et al.. (2015). Genetic epidemiology of coronary artery disease: an Asian Indian perspective. Journal of Genetics. 94(3). 539–549. 23 indexed citations
6.
Kakkar, Vijay V., et al.. (2014). CELSR2–PSRC1–SORT1 gene expression and association with coronary artery disease and plasma lipid levels in an Asian Indian cohort. Journal of Cardiology. 64(5). 339–346. 47 indexed citations
7.
Shanker, Jayashree, et al.. (2014). Expression Analysis of Leukotriene-Inflammatory Gene Interaction Network in Patients with Coronary Artery Disease. Journal of Atherosclerosis and Thrombosis. 21(4). 329–345. 15 indexed citations
8.
Ghatge, Madankumar, et al.. (2014). Network Analysis of Inflammatory Genes and Their Transcriptional Regulators in Coronary Artery Disease. PLoS ONE. 9(4). e94328–e94328. 48 indexed citations
9.
Shanker, Jayashree, Armen Yuri Gasparyan, George D. Kitas, & Vijay V. Kakkar. (2011). Platelet Function and Antiplatelet Therapy in Cardiovascular Disease: Implications of Genetic Polymorphisms. Current Vascular Pharmacology. 9(4). 479–489. 23 indexed citations
10.
Shanker, Jayashree, et al.. (2011). Role of vitamin D levels and vitamin D receptor polymorphisms in relation to coronary artery disease. Coronary Artery Disease. 22(5). 324–332. 26 indexed citations
11.
Shanker, Jayashree, et al.. (2011). Understanding the expression of Toll-like receptors in Asian Indians predisposed to coronary artery disease. Archives of Medical Science. 5(5). 781–787. 3 indexed citations
12.
Shanker, Jayashree, et al.. (2010). Polymorphisms in the pituitary growth hormone gene and its receptor associated with coronary artery disease in a predisposed cohort from India. Journal of Genetics. 89(4). 437–447. 4 indexed citations
13.
Rao, Veena S., et al.. (2010). Usefulness of C-Reactive Protein as a Marker for Prediction of Future Coronary Events in the Asian Indian Population: Indian Atherosclerosis Research Study. International Journal of Vascular Medicine. 2010. 1–8. 14 indexed citations
14.
Shanker, Jayashree & Vijay V. Kakkar. (2009). Role of Periodontal Infection in Cardiovascular Disease: a Current Perspective. Archives of Medical Science. 5(2). 125–134. 11 indexed citations
15.
16.
Dash, Debabrata, et al.. (2009). A common variant in chromosome 9p21 associated with coronary artery disease in Asian Indians. Journal of Genetics. 88(1). 113–118. 20 indexed citations
17.
Shanker, Jayashree, et al.. (2008). Clinical research Association of metabolic syndrome with atherothrombotic blood phenotypes in Asian Indian families with premature coronary artery disease. Archives of Medical Science. 4(2). 145–151. 3 indexed citations
18.
Shanker, Jayashree, et al.. (2008). Polymorphisms in the IL6 gene in Asian Indian families with premature coronary artery disease – The Indian Atherosclerosis Research Study. Thrombosis and Haemostasis. 99(11). 944–950. 48 indexed citations
19.
Shanker, Jayashree, et al.. (2008). Genetic studies on the APOA1-C3-A5 gene cluster in Asian Indians with premature coronary artery disease. Lipids in Health and Disease. 7(1). 33–33. 36 indexed citations
20.
Shanker, Jayashree, et al.. (2007). Adult nontwin sib concordance rates for type 2 diabetes, hypertension and metabolic syndrome among Asian Indians: the Indian Atherosclerosis Research Study.. PubMed. 3(6). 1063–8. 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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