I‐Ping Tu

30 papers receiving 944 citations

Peers

I‐Ping Tu
Comparison fields: 5 of 61
  • Computational Mathematics 16
  • Structural Biology 37
  • Reproductive Medicine 111
  • Genetics 187
  • Information Systems 61
Replace Jon Mangion with:
Jon Mangion United Kingdom
Meizhuo Zhang United States
Masato Kimura United States
Moira Lee United States
Lora Ziyabari United States
Steve Neuhauser United States
Moshe C. Silverstein United States
Dale A. Begley United States
Terence C. Wong United States
Penny Coulson United Kingdom
I‐Ping Tu relative to Jon Mangion United Kingdom Jon Mangion's profile →
Citations per field
00.5×1.5×2×2.3×
Jon Mangion · 1×
Citations per year

Countries citing papers authored by I‐Ping Tu

Since Specialization
Citations

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

Fields of papers citing papers by I‐Ping Tu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by I‐Ping Tu. 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 I‐Ping Tu. The network helps show where I‐Ping Tu may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2003288
2 2002145
3 199872
4 199971
5 201968
6 199747
7 200043
8 201232
9 200028
10 201027
11 200624
12 199919
13 202015
14 201414
15 200912
16 200411
17 202010
18 20187
19 20237
20 20206

About I‐Ping Tu

I‐Ping Tu is a scholar working on Structural Biology, Computational Mathematics, Genetics, Statistics and Probability and Information Systems, having authored 33 papers that have together received 975 indexed citations. Recurring topics across this work include Genetic Associations and Epidemiology (5 papers), Advanced Electron Microscopy Techniques and Applications (4 papers), Tensor decomposition and applications (3 papers), Blockchain Technology Applications and Security (3 papers), Gastric Cancer Management and Outcomes (1 paper), DNA Repair Mechanisms (1 paper), Gene expression and cancer classification (1 paper) and Statistical Methods and Applications (1 paper). The work is most often cited by research in Computational Mathematics (16 citations), Structural Biology (37 citations), Reproductive Medicine (111 citations), Genetics (187 citations) and Information Systems (61 citations). I‐Ping Tu has collaborated with scholars based in Taiwan, United States and China. Frequent co-authors include Alice S. Whittemore, Shih-Wei Liao, Yujing Lin, Kent‐Man Chu, Siu Tsan Yuen, Samuel K. So, Thomas A. Stamey, Iain M. Johnstone, Raj S. Pruthi and David Botstein. Their work appears in journals such as The American Journal of Human Genetics, The Annals of Applied Statistics, Statistics in Medicine, Advances in Applied Probability and Molecular Biology of the Cell.

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.

Explore authors with similar magnitude of impact