Baishan Fang
- Molecular Biology top 5%
- Microbial Metabolic Engineering and Bioproduction 44
- Enzyme Catalysis and Immobilization 35
- Machine Learning in Bioinformatics 11
- Metabolomics and Mass Spectrometry Studies 7
- Biomedical Engineering top 5%
- Biofuel production and bioconversion 20
- Electrochemistry top 10%
- Biotechnology top 10%
- Enzyme Production and Characterization 7
- Biochemistry top 10%
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- Enzyme Structure and Function 9
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- Electrochemical sensors and biosensors 8
- Co-authors
- Guangya ZhangGuo ChenShizhen WangDianhui LuoWei JiangAihui ZhangHongchun LiFei Liu
- Partner nations
- ChinaUnited KingdomMalaysia
In The Last Decade
Baishan Fang
98 papers receiving 2.1k citations
Peers
Comparison fields: 5 of 130
- Molecular Biology 1.4k
- Biomedical Engineering 631
- Electrochemistry 77
- Biotechnology 91
- Biochemistry 73
Countries citing papers authored by Baishan Fang
This map shows the geographic impact of Baishan Fang'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 Baishan Fang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Baishan Fang more than expected).
Fields of papers citing papers by Baishan Fang
This network shows the impact of papers produced by Baishan Fang. 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 Baishan Fang. The network helps show where Baishan Fang may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Baishan Fang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2023 | 9 | |
| 3 | 2023 | 33 | |
| 4 | 2021 | 44 | |
| 5 | 2018 | 7 | |
| 6 | 2016 | 34 | |
| 7 | 2016 | 74 | |
| 8 | 2016 | 25 | |
| 9 | 2016 | 19 | |
| 10 | 2015 | 11 | |
| 11 | 2014 | 6 | |
| 12 | Effect of Glycerol Feeding Strategy on Metabolism Characteristics of Lactobacillus reuteri | 2012 | 1 |
| 13 | Chemical Modification of the Glycerol Dehydrogenase by Divalent Metal Ions | 2011 | 3 |
| 14 | Recent Progress in Research of NADH Oxidase | 2011 | 1 |
| 15 | 2010 | 205 | |
| 16 | Research advance in biohydrogen mechanism | 2007 | 1 |
| 17 | 2007 | 4 | |
| 18 | 2007 | 8 | |
| 19 | 2006 | 52 | |
| 20 | [A model for amino acid composition and optimum pH in G/11 xylanase based on neural networks]. | 2005 | 1 |
About Baishan Fang
Baishan Fang is a scholar working on Molecular Biology, Biotechnology and Structural Biology, having authored 102 papers that have together received 2.2k indexed citations. Recurring topics across this work include Microbial Metabolic Engineering and Bioproduction (44 papers), Enzyme Catalysis and Immobilization (35 papers), Biofuel production and bioconversion (20 papers), Machine Learning in Bioinformatics (11 papers), Enzyme Structure and Function (9 papers), Electrochemical sensors and biosensors (8 papers), Metabolomics and Mass Spectrometry Studies (7 papers) and Enzyme Production and Characterization (7 papers). The work is most often cited by research in Molecular Biology (1.4k citations), Biomedical Engineering (631 citations) and Electrochemistry (77 citations). Baishan Fang has collaborated with scholars based in China, United Kingdom and Malaysia. Frequent co-authors include Guangya Zhang, Guo Chen, Shizhen Wang, Dianhui Luo, Wei Jiang, Aihui Zhang, Hongchun Li, Wei Jiang, Fei Liu and Chunjie Zhu. Their work appears in journals such as PLoS ONE, Bioresource Technology and Scientific Reports.
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.