Wei Sha

47 papers receiving 841 citations

Peers

Wei Sha
Comparison fields: 5 of 84
  • Endocrinology, Diabetes and Metabolism 329
  • Developmental Neuroscience 37
  • Endocrine and Autonomic Systems 48
  • Behavioral Neuroscience 24
  • Biological Psychiatry 14
Replace Petra Popovics with:
Petra Popovics United States
Tomasz Wietecha United States
Agnieszka Siejka Poland
Wanfu Wu United States
C. Dall’Osso United States
Roberta Buono Italy
Rosemeire M. Kanashiro‐Takeuchi United States
Shintaro Iwama Japan
Ellen R. Lubbers United States
Wei Sha relative to Petra Popovics United States Petra Popovics's profile →
Citations per field
00.5×1.5×1.9×
Petra Popovics · 1×
Citations per year

Countries citing papers authored by Wei Sha

Since Specialization
Citations

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

Fields of papers citing papers by Wei Sha

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 49 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201194
2 201368
3 201359
4 201754
5 201540
6 202039
7 201235
8 201832
9 201931
10 201831
11 201631
12 201829
13 201529
14 202123
15 202417
16 202115
17 202115
18 201415
19 201114
20 202213

About Wei Sha

Wei Sha is a scholar working on Endocrinology, Diabetes and Metabolism, Radiology, Nuclear Medicine and Imaging, Surgery, Pulmonary and Respiratory Medicine and Epidemiology, having authored 49 papers that have together received 847 indexed citations. Recurring topics across this work include Growth Hormone and Insulin-like Growth Factors (16 papers), Medical Imaging Techniques and Applications (7 papers), Pituitary Gland Disorders and Treatments (5 papers), Neuroendocrine Tumor Research Advances (5 papers), Pancreatic function and diabetes (4 papers), Cancer-related Molecular Pathways (4 papers), Stress Responses and Cortisol (3 papers) and Neurogenesis and neuroplasticity mechanisms (2 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (329 citations), Developmental Neuroscience (37 citations), Endocrine and Autonomic Systems (48 citations), Behavioral Neuroscience (24 citations) and Biological Psychiatry (14 citations). Wei Sha has collaborated with scholars based in United States, Italy and Germany. Frequent co-authors include Andrew V. Schally, Renzhi Cai, K.P. Wong, Petra Popovics, Sung-Cheng Huang, Xiaoli Zhang, Andrew Leask, Tengjiao Cui, Ferenc G. Rick and Xianyang Zhang. Their work appears in journals such as Proceedings of the National Academy of Sciences, Peptides, International Journal of Molecular Sciences, Scientific Reports and Nature Reviews Endocrinology.

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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