Baoshan Ma
Impact in
- Infectious Diseases top 10%
- COVID-19 Clinical Research Studies
- SARS-CoV-2 and COVID-19 Research
- Health Information Management top 10%
Papers in
-
- Machine Learning in Bioinformatics 5
- Bioinformatics and Genomic Networks 4
- Fractal and DNA sequence analysis 4
- RNA and protein synthesis mechanisms 3
- Epigenetics and DNA Methylation 3
- Gene Regulatory Network Analysis 3
- Genetics 6
- Co-authors
- Liming Liang (8 shared papers)Fengju Song (7 shared papers)Zhaozhong Zhu (2 shared papers)Kohei Hasegawa (2 shared papers)Michimasa Fujiogi (2 shared papers)Carlos A. Camargo (2 shared papers)Yan Ge (2 shared papers)Fanyu Meng (2 shared papers)
- Journals
- Bioinformatics (3 papers)Mathematical Biosciences & Engineering (2 papers)Metabolism (1 paper)Carcinogenesis (1 paper)Marine Pollution Bulletin (1 paper)
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Baoshan Ma
31 papers receiving 769 citations
Peers
Comparison fields: 5 of 117
- Infectious Diseases 124
- Health Information Management 21
- Cancer Research 61
- Molecular Biology 268
- Neurology 44
Countries citing papers authored by Baoshan Ma
This map shows the geographic impact of Baoshan Ma'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 Baoshan Ma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Baoshan Ma more than expected).
Fields of papers citing papers by Baoshan Ma
This network shows the impact of papers produced by Baoshan Ma. 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 Baoshan Ma. The network helps show where Baoshan Ma may publish in the future.
Co-authors
The 25 scholars most cited alongside Baoshan Ma, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 151 | |
| 2 | 2020 | 148 | |
| 3 | 2014 | 84 | |
| 4 | 2020 | 68 | |
| 5 | 2020 | 55 | |
| 6 | 2020 | 44 | |
| 7 | 2019 | 42 | |
| 8 | 2021 | 36 | |
| 9 | 2013 | 27 | |
| 10 | 2022 | 26 | |
| 11 | 2020 | 15 | |
| 12 | 2019 | 10 | |
| 13 | 2022 | 9 | |
| 14 | 2019 | 9 | |
| 15 | 2022 | 7 | |
| 16 | 2014 | 7 | |
| 17 | 2013 | 5 | |
| 18 | 2010 | 5 | |
| 19 | 2011 | 5 | |
| 20 | 2023 | 4 |
About Baoshan Ma
Baoshan Ma is a scholar working on Molecular Biology, Genetics, Infectious Diseases, Pulmonary and Respiratory Medicine and Signal Processing, having authored 33 papers that have together received 779 indexed citations. Recurring topics across this work include Machine Learning in Bioinformatics (5 papers), Bioinformatics and Genomic Networks (4 papers), Fractal and DNA sequence analysis (4 papers), Ferroptosis and cancer prognosis (3 papers), Blind Source Separation Techniques (3 papers), RNA and protein synthesis mechanisms (3 papers), Epigenetics and DNA Methylation (3 papers) and Gene Regulatory Network Analysis (3 papers). The work is most often cited by research in Infectious Diseases (124 citations), Health Information Management (21 citations), Cancer Research (61 citations), Molecular Biology (268 citations) and Neurology (44 citations). Baoshan Ma has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Liming Liang, Fengju Song, Zhaozhong Zhu, Kohei Hasegawa, Michimasa Fujiogi, Carlos A. Camargo, Yan Ge, Fanyu Meng, Haowen Yan and Xiaoyu Hou. Their work appears in journals such as Bioinformatics, Mathematical Biosciences & Engineering, Metabolism, Carcinogenesis and Marine Pollution Bulletin.
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.