Knowledge discovery method based on analysis of multiple co-occurrences in collections of journal papers

Purpose: This paper explores a method of knowledge discovery by visualizing and analyzing co-occurrence relations among three or more entities in collections of journal articles.Design/methodology/approach: A variety of methods such as the model construction, system analysis and experiments are used. The author has improved Morris' crossmapping technique and developed a technique for directly describing, visualizing and analyzing co-occurrence relations among three or more entities in collections of journal articles.Findings: The visualization&nbsp;tools and the knowledge discovery method can efficiently reveal the multiple co-occurrence relations among three entities in collections of journal papers. It can reveal more and in-depth information than analyzing co-occurrence relations between two entities. Therefore, this method can be used for mapping knowledge domain that is manifested in association with the entities from multi-dimensional perspectives and in an all-round way.Research limitations: The technique could only be used to analyze co-occurrence relations of less than three entities at present.Practical implications: This research has expanded the study scope of co-occurrence analysis. The research result has provided a theoretical support for co-occurrence analysis.Originality/value: There has not been a systematic study on co-occurrence relations among multiple entities in collections of journal articles. This research defines multiple co-occurrence and the research scope, develops the visualization analysis tool and designs the analysis model of the knowledge discovery method.Purpose: This paper explores a method of knowledge discovery by visualizing and analyzing co-occurrence relations among three or more entities in collections of journal articles.Design/methodology/approach: A variety of methods such as the model construction, system analysis and experiments are used. The author has improved Morris' crossmapping technique and developed a technique for directly describing, visualizing and analyzing co-occurrence relations among three or more entities in collections of journal articles.Findings: The visualization&nbsp;tools and the knowledge discovery method can efficiently reveal the multiple co-occurrence relations among three entities in collections of journal papers. It can reveal more and in-depth information than analyzing co-occurrence relations between two entities. Therefore, this method can be used for mapping knowledge domain that is manifested in association with the entities from multi-dimensional perspectives and in an all-round way.Research limitations: The technique could only be used to analyze co-occurrence relations of&nbsp;less than three entities at present.Practical implications: This research has expanded the study scope of co-occurrence analysis. The research result has provided a theoretical support for co-occurrence analysis.Originality/value: There has not been a systematic study on co-occurrence relations among multiple entities in collections of journal articles. This research defines multiple co-occurrence and the research scope, develops the visualization analysis tool and designs the analysis model of the knowledge discovery method.</p

Modeling study of knowledge diffusion in scientific collaboration networks based on differential dynamics: A case study in graphene field

Knowledge diffusion based on scientific collaboration is similar to disease propagation through actual contact. Inspired by the disease-spreading model in complex networks, this study classifies the states of research entities during the process of knowledge diffusion in scientific collaboration into four categories. Research entities can transform from one state to another with a certain probability, which results in the evolution rules of knowledge diffusion in scientific collaboration networks. The knowledge diffusion model of differential dynamics in scientific collaboration of non-uniformity networks is formed, and the relationship between the degree distribution and evolution of knowledge diffusion is further discussed, to reveal the dynamic mechanics of knowledge diffusion in scientific collaboration networks. Finally, an empirical analysis is conducted on knowledge diffusion in an institutional scientific collaboration network by taking the graphene field as an example. The results show that the state evolution of research entities in the knowledge diffusion process of scientific collaboration networks is affected not only by the evolution states of adjacent research entities with whom they have certain collaboration relationships, but also by the structural attributes and degree distributions of scientific collaboration networks. The evolution of knowledge diffusion in scientific collaboration entities with different degrees also shows different trends. (C) 2019 Elsevier B.V. All rights reserved

Mapping and Analysis of Technology Roadmap of Stem Cell Industry ─Taking Industrial Planning and Development of Guangdong Province as An Example

As1the most revolutionary technology in cell therapy, stem cell technology will give birth to a series of new biotechnology, drive the development of the pharmaceutical industry, and lead the future of biological economy. Guangdong province has a good foundation for stem cell R&D and has set up a project named "Stem Cell and Tissue Engineering Technology" to make breakthroughs in core technologies of stem cell research. In this paper, it is of great significance to compile the industrial technology roadmap and clarify the key points of stem cell and tissue engineering industry through the research to provide reference for the decision-making in Guangdong province

Overproduction of α-Lipoic Acid by Gene Manipulated <i>Escherichia coli</i>

<div><p>Alpha-lipoic acid (LA) is an important enzyme cofactor widely used by organisms and is also a natural antioxidant for the treatment of pathologies driven by low levels of endogenous antioxidants. In order to establish a safer and more efficient process for LA production, we developed a new biological method for LA synthesis based on the emerging knowledge of lipoic acid biosynthesis. We first cloned the <i>lipD</i> gene, which encodes the lipoyl domain of the E2 subunit of pyruvate dehydrogenase, allowing high levels of LipD production. Plasmids containing genes for the biosynthesis of LA were subsequently constructed utilizing various vectors and promotors to produce high levels of LA. These plasmids were transformed into the <i>Escherichia coli</i> strain BL21. Octanoic acid (OA) was used as the substrate for LA synthesis. One transformant, YS61, which carried <i>lipD</i>, <i>lplA</i>, and <i>lipA</i>, produced LA at levels over 200-fold greater than the wild-type strain, showing that LA could be produced efficiently in <i>E</i>. <i>coli</i> using genetic engineering methods.</p></div

The expression of the apo-lipoyl domain in strains with various vectors.

<p>Indicated strains were cultured in LB medium to OD₆₀₀ = 0.3, and the expression of the apo-lipoyl domain was induced for 3 hours. A dash (-) indicates that neither IPTG nor arabinose was added, while a plus sign (+) indicates IPTG (TM245, YS17 and YS28) or arabinose (YS19) was added for induction. The lipoyl domain was analyzed as described in the Materials and Methods section. The gel assay was conducted using non-denaturing polyacrylamide gel electrophoresis.</p