Model Ⅰ

The main goal of this study is to explore and address the knowledge gaps and unclear research directions in the field of mycobacterial-algal symbiosis technology through bibliometric modeling. By analyzing a large amount of relevant literature, we hope to objectively assess the current state of research in the field and provide strong guidance for future research, as well as insights for decision makers and scientists.

To achieve this goal, we used a bibliometric model that combines the core Web of Science dataset with specialized analytical tools such as VOSviewer and CiteSpace.This comprehensive model is unique in its ability to quantitatively analyze the literature data to reveal the knowledge structure, research hotspots, collaborative networks, and development trends in the field of bacterial and algal symbiosis technology. development trends. This in-depth analysis helps to better understand the academic landscape and innovation dynamics in the field.

First, we used the Web of Science core dataset as a source of information and exported the data for statistical analysis. We preliminarily analyzed the data in terms of the number of publications, discipline distribution, literature sources, and research groups. The data were initially analyzed to obtain information in these four areas.

Our research also has important application prospects. By analyzing large-scale literature data, we expect to reveal key research themes, collaborative networks among researchers, research hotspots, and citation networks in the field of bacterial-algal symbiosis technology. These insights will help researchers better position their work, find partners, and provide direction for future research.

By analyzing the number of publications, it is possible to understand the level of research activity in the field of mycobacterial and algal symbiosis technology. If the number of publications shows an increasing trend, it may indicate that the field has a high level of research enthusiasm and potential. On the contrary, if the number of publications tends to stabilize or decline, the dynamics of the field may need further attention. Examining the distribution of disciplines in the field of mycobacterial-algal symbiosis technology can reveal the multidisciplinary nature of the field. If a large proportion of literature from different disciplines is found in the field, it suggests that mycobacterial-algal symbiotic technology has a wide range of applications in interdisciplinary collaborations.

It also helps to identify the subject areas that dominate the field. Literature source analysis can help identify which journals, conferences or publications are the main sources of information in the field. This helps researchers and policy makers to understand the authority and credibility of the field and which publications to connect with for up-to-date information. Analyzing the collaborative networks of the research community can reveal which institutions, universities, or laboratories are important in the field. This can help to identify potential partners, facilitate cross-institutional or cross-national research collaborations, and promote knowledge sharing and technology exchange. The analysis of bibliometric models can reveal the knowledge structure, research hotspots and trends in the field. This helps to identify current research priorities as well as future research directions. For example, core concepts and key themes in the field can be identified through keyword co-occurrence analysis.

Next, the team focused on the keywords in the literature, and used VOSviewer software to statistically analyze the large amount of retrieved data, from which a number of keywords were extracted, and the keyword co-occurrence network was established as follows, and on the analysis of the co-occurrence network, the team could identify the research hotspots in the field of bacterial and algal symbiosis technology and the current topics of interest. This helps researchers to understand the cutting-edge issues in the field, select appropriate research directions, and identify research priorities. The team can use visualization tools such as keyword co-occurrence network diagrams to show the connections between different keywords, which helps researchers better understand the body of knowledge in the field. For practice groups, keyword analysis can provide guidance for the team's science popularization activities. Based on the research hotspots and keywords, the team can write popular science articles or produce popular science materials to better disseminate the knowledge of synthetic biology and awareness of ecological conservation.

In order to better understand the current status and research direction of algal symbiosis for water purification, CiteSpace was chosen to visualize the data.

The points were automatically categorized into eight broad categories using CiteSpace. The top five categories with the highest relevance and mentions were #0 hydrogen evolution, #1 coronavirus, #2 adsorption, #3 gene, and #4 heart failure. Each broad category is further analyzed next, respectively. Therefore, research in this area is of great significance in understanding the mechanism of algal symbiosis for water purification.

The team then analyzed the patent volume and obtained a total of 268,516 Chinese domestic and foreign patents in the past 11 years (2011-2022), statistics on the volume of patent-related literature in 2012-2022, the top ten countries in terms of the number of applications for patent authorization of mycobacterial symbiosis, the number of applications for patent authorization of mycobacterial symbiosis in the past years, and the trend of mycobacterial patented technology growth rate changes. Its study contributes to the trend of research in the field. The growth in the volume of literature may reflect the continued research and interest in Mycobacterial Algae Symbiosis technology.

By analyzing the trend in the number of patents granted over the years, the team can understand the dynamics of the field. Whether there is a clear trend of growth or decline, and the possible reasons for this. Trends in the growth rate of patented technologies can reflect the rate of technological innovation in the field. If the growth rate is stable or rising, it may indicate that the field is still innovative and dynamic.