Mia J. Smith

1.4k citations
37 papers · 1.0k indexed · h-index 18

Impact in

Papers in

Mia J. Smith

36 papers receiving 1.0k citations

Peers

Mia J. Smith
Comparison fields: 5 of 101
  • Immunology 469
  • Endocrinology, Diabetes and Metabolism 207
  • Genetics 336
  • Genetics 91
  • Surgery 213
Replace Marı́a-Luisa Gaspar with:
Marı́a-Luisa Gaspar Spain
Gaetano Naselli Australia
Cindy Jacobs United States
Sawako Minami Japan
Christian Klemann Germany
Hisaji Oshima Japan
Ann‐Kari Lefvert Sweden
Giuliana Giardino Italy
D. J. Bowen United Kingdom
T Nakazawa Japan
Mia J. Smith relative to Marı́a-Luisa Gaspar Spain Marı́a-Luisa Gaspar's profile →
Citations per field
00.5×2.5×
Marı́a-Luisa Gaspar · 1×
Citations per year

Countries citing papers authored by Mia J. Smith

Since Specialization
Citations

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

Fields of papers citing papers by Mia J. Smith

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20252
2 20251
3 20242
4 202314
5 20231
6 202216
7 202214
8 202117
9 20218
10 202022
11 201945
12 201820
13 2017118
14 201740
15 201425
16 2011127
17 200421
18 200066
19
Chemokines and matrix metalloproteinase expression in rheumatoid arthritis (RA) patients achieving remission
20000
20 19952

About Mia J. Smith

Mia J. Smith is a scholar working on Immunology, Endocrinology, Diabetes and Metabolism, Genetics, Behavioral Neuroscience and Radiology, Nuclear Medicine and Imaging, having authored 37 papers that have together received 1.0k indexed citations. Recurring topics across this work include Diabetes and associated disorders (16 papers), T-cell and B-cell Immunology (14 papers), Diabetes Management and Research (10 papers), Pancreatic function and diabetes (9 papers), Immune Cell Function and Interaction (7 papers), Monoclonal and Polyclonal Antibodies Research (6 papers), Immunotherapy and Immune Responses (3 papers) and SARS-CoV-2 and COVID-19 Research (2 papers). The work is most often cited by research in Immunology (469 citations), Endocrinology, Diabetes and Metabolism (207 citations), Genetics (336 citations), Genetics (91 citations) and Surgery (213 citations). Mia J. Smith has collaborated with scholars based in United States, Australia and United Kingdom. Frequent co-authors include John C. Cambier, Kimber M. Simmons, Peter A. Gottlieb, Loren Cordain, Andrew Getahun, Shannon O’Neill, Rochelle M. Hinman, Marynette Rihanek, Thomas Packard and Matthew S. Hickey. Their work appears in journals such as Frontiers in Immunology, The Journal of Immunology, Diabetes, The Journal of Experimental Medicine and Journal of Visualized Experiments.

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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