Pei-Chen Peng
Impact in
- Health Informatics top 0.5%
- Artificial Intelligence in Healthcare and Education
- Computer Science Applications top 10%
- Online Learning and Analytics
Papers in
-
- Genomics and Chromatin Dynamics 4
- RNA Research and Splicing 3
- RNA and protein synthesis mechanisms 2
- RNA modifications and cancer 1
-
- Breast Cancer Treatment Studies 2
- Cancer Genomics and Diagnostics 1
- Co-authors
- Kyoung‐Jae Won (1 shared paper)Patrick Martin (1 shared paper)Jesse G. Meyer (1 shared paper)Jason H. Moore (2 shared papers)Ryan J. Urbanowicz (2 shared papers)Karen O’Connor (1 shared paper)Tiffani J Bright (2 shared papers)Ruowang Li (1 shared paper)
- Journals
- Journal of the American Medical Informatics Association (1 paper)Patterns (1 paper)Nucleic Acids Research (1 paper)IEEE/ACM Transactions on Computational Biology and Bioinformatics (1 paper)The American Journal of Human Genetics (1 paper)
- Partner nations
- United StatesUnited KingdomGermany
In The Last Decade
Pei-Chen Peng
10 papers receiving 429 citations
Pei-Chen Peng's Hit Papers
Peers
Comparison fields: 5 of 93
- Health Informatics 168
- Computer Science Applications 52
- Artificial Intelligence 154
- Safety Research 31
- Family Practice 4
Countries citing papers authored by Pei-Chen Peng
This map shows the geographic impact of Pei-Chen Peng'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 Pei-Chen Peng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pei-Chen Peng more than expected).
Fields of papers citing papers by Pei-Chen Peng
This network shows the impact of papers produced by Pei-Chen Peng. 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 Pei-Chen Peng. The network helps show where Pei-Chen Peng may publish in the future.
Co-authors
The 25 scholars most cited alongside Pei-Chen Peng, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | ChatGPT and large language models in academia: opportunities and challenges Hit paper breakdown → | 2023 | 340 |
| 2 | 2017 | 34 | |
| 3 | 2020 | 18 | |
| 4 | 2013 | 14 | |
| 5 | 2016 | 14 | |
| 6 | 2019 | 12 | |
| 7 | 2015 | 8 | |
| 8 | 2024 | 2 | |
| 9 | 2025 | 1 | |
| 10 | 2024 | 1 | |
| 11 | 2024 | 0 | |
| 12 | 2024 | 0 | |
| 13 | 2025 | 0 | |
| 14 | 2026 | 0 |
About Pei-Chen Peng
Pei-Chen Peng is a scholar working on Molecular Biology, Cancer Research, Health Informatics, Genetics and Plant Science, having authored 14 papers that have together received 444 indexed citations. Recurring topics across this work include Genomics and Chromatin Dynamics (4 papers), RNA Research and Splicing (3 papers), Plant Molecular Biology Research (2 papers), Artificial Intelligence in Healthcare and Education (2 papers), Breast Cancer Treatment Studies (2 papers), RNA and protein synthesis mechanisms (2 papers), RNA modifications and cancer (1 paper) and Cancer Genomics and Diagnostics (1 paper). The work is most often cited by research in Health Informatics (168 citations), Computer Science Applications (52 citations), Artificial Intelligence (154 citations), Safety Research (31 citations) and Family Practice (4 citations). Pei-Chen Peng has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include Kyoung‐Jae Won, Patrick Martin, Jesse G. Meyer, Jason H. Moore, Ryan J. Urbanowicz, Karen O’Connor, Tiffani J Bright, Ruowang Li, Nicholas P. Tatonetti and Graciela Gonzalez‐Hernandez. Their work appears in journals such as Journal of the American Medical Informatics Association, Patterns, Nucleic Acids Research, IEEE/ACM Transactions on Computational Biology and Bioinformatics and The American Journal of Human Genetics.
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.