DocumentCode
3273200
Title
Mapping Medline papers, genes, and proteins related to melanoma research
Author
Boyack, Kevin W. ; Mane, Ketan ; Borner, Katy
Author_Institution
VisWave LLC, Albuquerque, NM, USA
fYear
2004
fDate
14-16 July 2004
Firstpage
965
Lastpage
971
Abstract
What is the structure of the research reported on melanoma? How has it evolved over the last 40 years? Which parts of this research field are correlated with the study of genes and proteins? Are there sudden increases in the number of occurrences of certain gene or protein names, reflecting a surge of interest? How are genes, protein and papers interconnected via co-occurrence patterns? This paper aims to provide answers to these questions by analyzing a data set consisting of papers from Medline, genes from the Entrez Gene database, and proteins from UniProt. Word burst detection and co-occurrence analyses were both performed. The spatial layout algorithm VxOrd was applied to create the very first map that shows papers, genes, and proteins and their co-occurrence relationships. The results were validated by five domain experts leading to a number of interesting facts pertaining to structure and dynamics of the melanoma research field.
Keywords
cancer; data analysis; genetics; medical computing; proteins; skin; Entrez Gene database; Medline papers; UniProt; cooccurrence analysis; cooccurrence patterns; data set analysis; genes; melanoma research; proteins; Malignant tumors; Proteins;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Visualisation, 2004. IV 2004. Proceedings. Eighth International Conference on
ISSN
1093-9547
Print_ISBN
0-7695-2177-0
Type
conf
DOI
10.1109/IV.2004.1320258
Filename
1320258
Link To Document