Yu-Shi Lin
- Artificial Intelligence top 10%
- Molecular Biology
- Biophysics top 10%
- Computer Science Applications top 10%
- Computer Vision and Pattern Recognition
- Co-authors
- Chun‐Nan HsuYu-Ming ChangCheng-Ju KuoI‐Fang ChungChung‐Chih LinShou-De LinYi‐Hung HuangYuh‐Show Tsai
- Topics
- Cell Image Analysis Techniques (5 papers)Biomedical Text Mining and Ontologies (4 papers)Topic Modeling (4 papers)
- Journals
- BioinformaticsExpert Systems with ApplicationsACM Transactions on Intelligent Systems and Technology
- Partner nations
- TaiwanItalyUnited States
In The Last Decade
Yu-Shi Lin
12 papers receiving 240 citations
Peers
Comparison fields: 5 of 53
- Artificial Intelligence 148
- Molecular Biology 123
- Biophysics 42
- Computer Science Applications 32
- Computer Vision and Pattern Recognition 30
Countries citing papers authored by Yu-Shi Lin
This map shows the geographic impact of Yu-Shi Lin'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 Yu-Shi Lin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yu-Shi Lin more than expected).
Fields of papers citing papers by Yu-Shi Lin
This network shows the impact of papers produced by Yu-Shi Lin. 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 Yu-Shi Lin. The network helps show where Yu-Shi Lin may publish in the future.
Co-authorship network of co-authors of Yu-Shi Lin
This figure shows the co-authorship network connecting the top 25 collaborators of Yu-Shi Lin. A scholar is included among the top collaborators of Yu-Shi Lin based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Yu-Shi Lin. Yu-Shi Lin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 8 | |
| 3 | Feature Engineering and Classifier Ensemble for KDD Cup 2010 | 89 |
| 4 | 6 | |
| 5 | Automated cell phenotype image classification combining different methods. | 1 |
| 6 | 3 | |
| 7 | 15 | |
| 8 | Re-weighting Graph Links for Quantifying Difference. | 1 |
| 9 | 63 | |
| 10 | Rich Feature Set, Unification of Bidirectional Parsing and Dictionary Filtering for High F-Score Gene Mention Tagging. | 28 |
| 11 | 28 | |
| 12 | Analysis and Enhancement of Conditional Random Fields Gene Mention Taggers in BioCreative II Challenge Evaluation. | 5 |
| 13 | Exploring Match Scores to Boost Precision of Gene Normalization. | 3 |
About Yu-Shi Lin
Yu-Shi Lin is a scholar working on Biophysics, Media Technology and Artificial Intelligence, having authored 13 papers that have together received 250 indexed citations. Recurring topics across this work include Cell Image Analysis Techniques (5 papers), Biomedical Text Mining and Ontologies (4 papers) and Topic Modeling (4 papers). The work is most often cited by research in Biophysics (42 citations), Computer Science Applications (32 citations) and Artificial Intelligence (148 citations). Yu-Shi Lin has collaborated with scholars based in Taiwan, Italy and United States. Frequent co-authors include Chun‐Nan Hsu, Yu-Ming Chang, Cheng-Ju Kuo, I‐Fang Chung, Chung‐Chih Lin, Shou-De Lin, Yi‐Hung Huang, Yuh‐Show Tsai, Chih‐Jen Lin and Che‐Wei Chang. Their work appears in journals such as Bioinformatics, Expert Systems with Applications and ACM Transactions on Intelligent Systems and Technology.
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.