Minghu Song
- Molecular Biology
- Computational Theory and Mathematics top 5%
- Computer Vision and Pattern Recognition top 10%
- Artificial Intelligence top 10%
- Spectroscopy top 10%
- Co-authors
- Curt M. BrenemanKristin P. BennettJinbo BiMark J. EmbrechtsMatthew ClarkN. SukumarNihal TugçuSteven M. Cramer
- Topics
- Computational Drug Discovery Methods (4 papers)Spectroscopy and Quantum Chemical Studies (2 papers)Analytical Chemistry and Chromatography (2 papers)
- Cited by
- Computational Theory and MathematicsAnalytical ChemistryComputer Vision and Pattern Recognition
- Partner nations
- United StatesChinaSouth Korea
In The Last Decade
Minghu Song
12 papers receiving 640 citations
Peers
Comparison fields: 5 of 119
- Molecular Biology 271
- Computational Theory and Mathematics 162
- Computer Vision and Pattern Recognition 142
- Artificial Intelligence 140
- Spectroscopy 92
Countries citing papers authored by Minghu Song
This map shows the geographic impact of Minghu Song'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 Minghu Song with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Minghu Song more than expected).
Fields of papers citing papers by Minghu Song
This network shows the impact of papers produced by Minghu Song. 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 Minghu Song. The network helps show where Minghu Song may publish in the future.
Co-authorship network of co-authors of Minghu Song
This figure shows the co-authorship network connecting the top 25 collaborators of Minghu Song. A scholar is included among the top collaborators of Minghu Song 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 Minghu Song. Minghu Song 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 | 0 | |
| 3 | 11 | |
| 4 | 20 | |
| 5 | 27 | |
| 6 | 9 | |
| 7 | 32 | |
| 8 | 84 | |
| 9 | 22 | |
| 10 | Dimensionality reduction via sparse support vector machines | 279 |
| 11 | 29 | |
| 12 | 30 | |
| 13 | 2 | |
| 14 | 133 |
About Minghu Song
Minghu Song is a scholar working on Computational Mathematics, Computational Theory and Mathematics and Virology, having authored 14 papers that have together received 678 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (4 papers), Spectroscopy and Quantum Chemical Studies (2 papers) and Analytical Chemistry and Chromatography (2 papers). The work is most often cited by research in Computational Theory and Mathematics (162 citations), Analytical Chemistry (72 citations) and Computer Vision and Pattern Recognition (142 citations). Minghu Song has collaborated with scholars based in United States, China and South Korea. Frequent co-authors include Curt M. Breneman, Kristin P. Bennett, Jinbo Bi, Mark J. Embrechts, Matthew Clark, N. Sukumar, Nihal Tugçu, Steven M. Cramer, Fu‐Gen Wu and Zhan Chen. Their work appears in journals such as Analytical Chemistry, Langmuir and Biochemical and Biophysical Research Communications.
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.