Jinming Song
- Hematology top 5%
- Molecular Biology
- Genetics top 10%
- Computer Vision and Pattern Recognition top 10%
- Artificial Intelligence top 10%
- Co-authors
- Mohammad HussainiAlina FloreaGene GulatiJerald Z. GongEric PadronShuai LiuRami S. KomrokjiJeffrey E. Lancet
- Topics
- Acute Myeloid Leukemia Research (31 papers)Myeloproliferative Neoplasms: Diagnosis and Treatment (21 papers)Chronic Myeloid Leukemia Treatments (8 papers)
- Journals
- Journal of the American Chemical SocietyAngewandte Chemie International EditionSHILAP Revista de lepidopterología
- Partner nations
- United StatesChinaSouth Korea
In The Last Decade
Jinming Song
50 papers receiving 490 citations
Peers
Comparison fields: 5 of 77
- Hematology 231
- Molecular Biology 122
- Genetics 111
- Computer Vision and Pattern Recognition 111
- Artificial Intelligence 95
Countries citing papers authored by Jinming Song
This map shows the geographic impact of Jinming 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 Jinming Song with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jinming Song more than expected).
Fields of papers citing papers by Jinming Song
This network shows the impact of papers produced by Jinming 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 Jinming Song. The network helps show where Jinming Song may publish in the future.
Co-authorship network of co-authors of Jinming Song
This figure shows the co-authorship network connecting the top 25 collaborators of Jinming Song. A scholar is included among the top collaborators of Jinming 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 Jinming Song. Jinming 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 | 1 | |
| 4 | 1 | |
| 5 | 2 | |
| 6 | 1 | |
| 7 | 0 | |
| 8 | 16 | |
| 9 | 7 | |
| 10 | 14 | |
| 11 | 12 | |
| 12 | 3 | |
| 13 | 14 | |
| 14 | 5 | |
| 15 | 15 | |
| 16 | 12 | |
| 17 | 3 | |
| 18 | 25 | |
| 19 | 2 | |
| 20 | 46 |
About Jinming Song
Jinming Song is a scholar working on Hematology, Genetics and Emergency Medicine, having authored 59 papers that have together received 506 indexed citations. Recurring topics across this work include Acute Myeloid Leukemia Research (31 papers), Myeloproliferative Neoplasms: Diagnosis and Treatment (21 papers) and Chronic Myeloid Leukemia Treatments (8 papers). The work is most often cited by research in Hematology (231 citations), Genetics (111 citations) and Computer Vision and Pattern Recognition (111 citations). Jinming Song has collaborated with scholars based in United States, China and South Korea. Frequent co-authors include Mohammad Hussaini, Alina Florea, Gene Gulati, Jerald Z. Gong, Eric Padron, Shuai Liu, Rami S. Komrokji, Jeffrey E. Lancet, Haipeng Shao and David A. Sallman. Their work appears in journals such as Journal of the American Chemical Society, Angewandte Chemie International Edition and SHILAP Revista de lepidopterología.
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.