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2023-03-07

This is Maëlle's DBGI daily open-notebook.

Today is 2023.03.07

TODO

CODE

NOTES

  • Worked on implementing the GNPS dashboard in our dashboard

TODO NEXT

Important for redaction

Asked help from chatgpt to create the thesis outline:

I. Introduction

  • Background and motivation for the project (Presentation of DBGI / LOTUS?)
  • Brief overview of the research problem and objectives

II. Literature Review

  • (Overview of the relevant literature related to plant metabolites, LCMS profiles, and knowledge graphs)
  • Discussion of existing research on creating data dashboards and using SPARQL queries for data visualization

III. Methodology

  • Description of the data sources and how they were collected and processed (LOTUS + DBGI)
  • (Details on the development of the knowledge graph and how it will be used to feed the dashboard)
  • Discussion of the software tools and programming languages used to build the dashboard and interface with the knowledge graph and LCMS profiles

IV. Dashboard Development

  • Presentation of the dashboard interface and its various features and components
  • Discussion of the key statistics and visualizations displayed on the dashboard, and how they relate to the research objectives
  • (Examples of SPARQL queries used to extract information from the knowledge graph and visualize it on the dashboard)

V. Code Optimization

  • Discussion of how the code was optimized for efficiency and speed
  • Overview of the methods and techniques used to improve code performance, such as caching, parallelization, and algorithmic improvements
  • Presentation of performance benchmarks and comparisons to demonstrate the improvements achieved

VI. Discussion

  • Interpretation of the results and their implications for plant metabolite research and data visualization
  • Comparison of the proposed dashboard to existing tools and methods
  • Limitations of the study and potential avenues for future research

VII. Conclusion

  • Summary of the key findings and contributions of the thesis
  • Implications for the field of plant metabolite research and data visualization
  • Suggestions for future research

VIII. References

  • List of all references cited in the thesis

IX. Appendices

  • Additional technical details on the development of the dashboard and knowledge graph, as well as sample SPARQL queries and LCMS profiles used in the study