Peiran Song
- Molecular Biology
- Electrical and Electronic Engineering
- Computer Networks and Communications top 10%
- Biomedical Engineering
- Computational Mechanics top 10%
- Co-authors
- Gesualdo ScutariFrancisco FacchineiDaniel P. PalomarJong‐Shi PangJiacan SuZhongmin ShiSicheng WangYingying Jing
- Topics
- Chronic Lymphocytic Leukemia Research (6 papers)Lymphoma Diagnosis and Treatment (5 papers)Advanced MIMO Systems Optimization (4 papers)
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Peiran Song
30 papers receiving 831 citations
Hit Papers
Peers
Comparison fields: 5 of 109
- Molecular Biology 221
- Electrical and Electronic Engineering 210
- Computer Networks and Communications 155
- Biomedical Engineering 126
- Computational Mechanics 84
Countries citing papers authored by Peiran Song
This map shows the geographic impact of Peiran 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 Peiran Song with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peiran Song more than expected).
Fields of papers citing papers by Peiran Song
This network shows the impact of papers produced by Peiran 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 Peiran Song. The network helps show where Peiran Song may publish in the future.
Co-authorship network of co-authors of Peiran Song
This figure shows the co-authorship network connecting the top 25 collaborators of Peiran Song. A scholar is included among the top collaborators of Peiran 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 Peiran Song. Peiran 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 | 6 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | Boosting cartilage repair with silk fibroin-DNA hydrogel-based cartilage organoid precursorbreakdown → | 98 |
| 6 | Synthetic biology‐based bacterial extracellular vesicles displaying BMP‐2 and CXCR4 to ameliorate osteoporosisbreakdown → | 59 |
| 7 | 23 | |
| 8 | Dual-network DNA–silk fibroin hydrogels with controllable surface rigidity for regulating chondrogenic differentiationbreakdown → | 61 |
| 9 | 27 | |
| 10 | 1 | |
| 11 | Diets intervene osteoporosis via gut-bone axisbreakdown → | 86 |
| 12 | 2 | |
| 13 | 2 | |
| 14 | 30 | |
| 15 | 2 | |
| 16 | 0 | |
| 17 | 21 | |
| 18 | 5 | |
| 19 | 4 | |
| 20 | Distributed Methods for Constrained Nonconvex Multi-Agent Optimization-Part I: Theory. | 16 |
About Peiran Song
Peiran Song is a scholar working on Genetics, Oncology and Pathology and Forensic Medicine, having authored 35 papers that have together received 840 indexed citations. Recurring topics across this work include Chronic Lymphocytic Leukemia Research (6 papers), Lymphoma Diagnosis and Treatment (5 papers) and Advanced MIMO Systems Optimization (4 papers). The work is most often cited by research in Computer Networks and Communications (155 citations), Computational Mathematics (4 citations) and Biomaterials (73 citations). Peiran Song has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Gesualdo Scutari, Francisco Facchinei, Daniel P. Palomar, Jong‐Shi Pang, Jiacan Su, Zhongmin Shi, Sicheng Wang, Yingying Jing, Lorenzo Lampariello and Yuan‐Wei Zhang. Their work appears in journals such as Advanced Materials, Nano Letters and Analytical Chemistry.
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.