Matthew T. Patrick

46 papers receiving 916 citations

Peers

Matthew T. Patrick
Comparison fields: 5 of 109
  • Dermatology 212
  • Immunology 263
  • Periodontics 51
  • Software 44
  • Rheumatology 146
Replace Roberto Alfano with:
Roberto Alfano Italy
Anupam Mitra United States
Yiling Yang China
Qian Yu China
Shirong Li China
Tsung‐Lin Cheng Taiwan
Ignazio Stanganelli Italy
Ibrahim O. Bello Saudi Arabia
Wei‐Fan Chiang Taiwan
Sophie Glatt United Kingdom
Matthew T. Patrick relative to Roberto Alfano Italy Roberto Alfano's profile →
Citations per field
00.5×6.4×
Roberto Alfano · 1×
Citations per year

Countries citing papers authored by Matthew T. Patrick

Since Specialization
Citations

This map shows the geographic impact of Matthew T. Patrick'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 Matthew T. Patrick with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthew T. Patrick more than expected).

Fields of papers citing papers by Matthew T. Patrick

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matthew T. Patrick. 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 Matthew T. Patrick. The network helps show where Matthew T. Patrick may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 47 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019121
2 201973
3 202160
4 201755
5 201954
6 202245
7 201845
8 202143
9 202240
10 202037
11 202037
12 201934
13 201730
14 202328
15 202225
16 202325
17 201820
18 202115
19 202113
20 202412

About Matthew T. Patrick

Matthew T. Patrick is a scholar working on Immunology, Dermatology, Molecular Biology, Software and Information Systems, having authored 47 papers that have together received 936 indexed citations. Recurring topics across this work include Software Testing and Debugging Techniques (7 papers), Dermatology and Skin Diseases (7 papers), Psoriasis: Treatment and Pathogenesis (6 papers), Software Engineering Research (6 papers), Cytokine Signaling Pathways and Interactions (5 papers), Software Reliability and Analysis Research (5 papers), IL-33, ST2, and ILC Pathways (3 papers) and Systemic Lupus Erythematosus Research (3 papers). The work is most often cited by research in Dermatology (212 citations), Immunology (263 citations), Periodontics (51 citations), Software (44 citations) and Rheumatology (146 citations). Matthew T. Patrick has collaborated with scholars based in United States, United Kingdom and China. Frequent co-authors include Lam C. Tsoi, Jóhann E. Guðjónsson, James T. Elder, Kalpana Raja, J. Michelle Kahlenberg, Céline C. Berthier, Rachael Wasikowski, Kevin He, Xianying Xing and Allison C. Billi. Their work appears in journals such as Journal of Allergy and Clinical Immunology, Journal of Investigative Dermatology, British Journal of Dermatology, Nature Communications and JCI Insight.

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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