Maya Ram

58 papers receiving 2.2k citations

Peers

Maya Ram
Comparison fields: 5 of 108
  • Rheumatology 548
  • Gastroenterology 182
  • Parasitology 173
  • Hepatology 173
  • Immunology 488
Replace P. J. Sinnott with:
P. J. Sinnott United Kingdom
A Tiilikainen Finland
Yehuda Shoenfeld Israel
Fiona Graeme‐Cook United States
Paul A. Blair United Kingdom
J F Colombel United States
Wolfgang Schlumberger Germany
Sílvia Vidal Spain
Mark Lazarus United Kingdom
Eduardo D. Ruchelli United States
Maya Ram relative to P. J. Sinnott United Kingdom P. J. Sinnott's profile →
Citations per field
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P. J. Sinnott · 1×
Citations per year

Countries citing papers authored by Maya Ram

Since Specialization
Citations

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

Fields of papers citing papers by Maya Ram

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 61 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2006249
2 2007165
3
The mosaic of autoimmunity: hormonal and environmental factors involved in autoimmune diseases--2008.
2008153
4 2007125
5
The mosaic of autoimmunity: prediction, autoantibodies, and therapy in autoimmune diseases--2008.
2008107
6
The mosaic of autoimmunity: genetic factors involved in autoimmune diseases--2008.
2008104
7 200885
8 200980
9 200978
10 201276
11 200869
12 200964
13 201163
14 200956
15 201256
16 201253
17 201147
18
The mosaic of autoimmunity: genetic factors involved in autoimmune diseases—2008. Isr Med Assoc J
200846
19 200942
20 200942

About Maya Ram

Maya Ram is a scholar working on Obstetrics and Gynecology, Immunology, Epidemiology, Rheumatology and Genetics, having authored 61 papers that have together received 2.3k indexed citations. Recurring topics across this work include Systemic Lupus Erythematosus Research (9 papers), Pregnancy and preeclampsia studies (6 papers), Cytomegalovirus and herpesvirus research (6 papers), Diabetes and associated disorders (5 papers), Gestational Diabetes Research and Management (5 papers), Parvovirus B19 Infection Studies (4 papers), Celiac Disease Research and Management (4 papers) and T-cell and B-cell Immunology (4 papers). The work is most often cited by research in Rheumatology (548 citations), Gastroenterology (182 citations), Parasitology (173 citations), Hepatology (173 citations) and Immunology (488 citations). Maya Ram has collaborated with scholars based in Israel, United States and Colombia. Frequent co-authors include Yehuda Shoenfeld, Ori Barzilai, Yaniv Sherer, Juan‐Manuel Anaya, Nicola Bizzaro, Miri Blank, David Izhaky, Nancy Agmon‐Levin, Yackov Berkun and Gisele Zandman‐Goddard. Their work appears in journals such as Annals of the New York Academy of Sciences, Archives of Gynecology and Obstetrics, American Journal of Obstetrics and Gynecology, Autoimmunity Reviews and Clinical Reviews in Allergy & Immunology.

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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