Mapping Medline Papers, Genes and Proteins Related to Melanoma Research
A combination of data consisting of 40 years of literature data from Medline, genes data from Entrez-Gene and protein data from Uniprot were used for this analysis. Techniques like Burst detection were applied to identify highly researched genes and proteins. Co-sine similarity measure was used to identify association between genes, proteins and papers. Data layout was done using VxOrd and VxInsight.
Description of Unique Features: The graph provides a global view of the melanoma domain.
Data Used: Literature data from Medline (1960 – 2004), Gene data from Entrez-gene and protein data from Uniprot.
Data Analysis Techniques Applied: Kleinberg’s burst detection algorithm was used to identify the top researched melanoma related genes and proteins. Co-sine similarity was used to obtain similarity measures between papers, genes and proteins.
Spatial Layout Techniques Applied: VxOrd (force-directed graph layout). VxInsight for interactive exploration
Boyack, Kevin W., Mane, Ketan and Börner, Katy. (2004). Mapping Medline Papers, Genes, and Proteins Related to Melanoma Research. IV2004 Conference, London, UK, pp. 965-971.