P. Mêda

108 papers receiving 5.2k citations

P. Mêda's Hit Papers

Establishment of 2-mercaptoethanol-dependent differentiated insulin-secreting cell lines. 1992 · 1.0k citations
1.0k0+11+22Years since publication2505007501000

Peers

P. Mêda
Comparison fields: 5 of 156
  • Endocrine and Autonomic Systems 363
  • Surgery 2.4k
  • Endocrinology, Diabetes and Metabolism 854
  • Molecular Biology 3.2k
  • Cell Biology 729
Replace Kyoung‐Jae Won with:
Kyoung‐Jae Won United States
Bin Zheng United States
Zhiping Chen China
Alexander Rabinovitch Canada
Bin Lü China
Yasuhiro Watanabe Japan
Guangyu Wu United States
Tom A. Gardiner United Kingdom
Huizhen Wang China
Massimo De Felici Italy
P. Mêda relative to Kyoung‐Jae Won United States Kyoung‐Jae Won's profile →
Citations per field
00.5×3.3×
Kyoung‐Jae Won · 1×
Citations per year

Countries citing papers authored by P. Mêda

Since Specialization
Citations

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

Fields of papers citing papers by P. Mêda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 114 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Establishment of 2-mercaptoethanol-dependent differentiated insulin-secreting cell lines.
Hit paper breakdown →
19921002
2 2000222
3 2000202
4 1981190
5 1993166
6 1991150
7 1987134
8 2000133
9 1979123
10 1994117
11 200798
12 199598
13 198998
14 199096
15 200793
16 199289
17 199289
18 200586
19 198880
20 199680

About P. Mêda

P. Mêda is a scholar working on Surgery, Molecular Biology, Building and Construction, Genetics and Physiology, having authored 114 papers that have together received 5.3k indexed citations. Recurring topics across this work include Pancreatic function and diabetes (47 papers), Connexins and lens biology (29 papers), BIM and Construction Integration (22 papers), Diabetes and associated disorders (14 papers), Diabetes Management and Research (8 papers), Erythrocyte Function and Pathophysiology (8 papers), Digital Transformation in Industry (7 papers) and Occupational Health and Safety Research (6 papers). The work is most often cited by research in Endocrine and Autonomic Systems (363 citations), Surgery (2.4k citations), Endocrinology, Diabetes and Metabolism (854 citations), Molecular Biology (3.2k citations) and Cell Biology (729 citations). P. Mêda has collaborated with scholars based in Switzerland, Portugal and United States. Frequent co-authors include Lelio Orci, Philippe A. Halban, Claes B. Wollheim, D. Janjic, Maryam Asfari, Geng Li, Domenico Bosco, Alain Perrelet, Michael S. Pepper and Marc Chanson. Their work appears in journals such as Diabetes, Diabetologia, American Journal of Physiology-Cell Physiology, Journal of Clinical Investigation and The Journal of Cell Biology.

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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