I‐Ping Tu

1.5k citations
31 papers · 858 · h-index 13

Impact in

Papers in

    • Gene expression and cancer classification 4
    • Genetic Associations and Epidemiology 6
    • Genetic Mapping and Diversity in Plants and Animals 5

I‐Ping Tu

28 papers receiving 841 citations

Peers

I‐Ping Tu
Comparison fields: 5 of 116
  • Structural Biology 33
  • Transplantation 46
  • Computational Mathematics 11
  • Genetics 203
  • Surgery 247
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Anthony Sisk United States
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Yannick Pouliot United States
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Andrey Kartashov United States
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Citations per field
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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 31 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Risk factors for the development of obliterative bronchiolitis after lung transplantation.
1996237
2 2002136
3 199971
4 199869
5 199748
6 201946
7 200041
8 201228
9 200027
10 200625
11 201024
12 199917
13 200914
14 202012
15 200411
16 20209
17 20237
18 20187
19 20215
20 20205

About I‐Ping Tu

I‐Ping Tu is a scholar working on Molecular Biology, Genetics, Structural Biology, Artificial Intelligence and Signal Processing, having authored 31 papers that have together received 858 indexed citations. Recurring topics across this work include Genetic Associations and Epidemiology (6 papers), Advanced Electron Microscopy Techniques and Applications (5 papers), Genetic Mapping and Diversity in Plants and Animals (5 papers), Gene expression and cancer classification (4 papers), Blind Source Separation Techniques (4 papers), Blockchain Technology Applications and Security (3 papers), Electron and X-Ray Spectroscopy Techniques (3 papers) and Statistical Methods and Bayesian Inference (3 papers). The work is most often cited by research in Structural Biology (33 citations), Transplantation (46 citations), Computational Mathematics (11 citations), Genetics (203 citations) and Surgery (247 citations). I‐Ping Tu has collaborated with scholars based in Taiwan, United States and Hong Kong. Frequent co-authors include Alice S. Whittemore, I B Johnstone, James Theodore, Gerald J. Berry, Reda E. Girgis, Vincent G. Valentine, Janet M. Miller, B. A. Reitz, H. Reichenspurner and R.C. Robbins. Their work appears in journals such as The American Journal of Human Genetics, Advances in Applied Probability, Nature Communications, Modern Pathology 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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