Abstract
BackgroundOur increasing use of genetic and genomic strategies to understand human prostate cancer means that we need access to simplified and integrated information present in the associated biomedical literature. In particular, microarray gene expression studies and associated genetic mapping studies in prostate cancer would benefit from a generalized understanding of the prior work associated with this disease. This would allow us to focus subsequent laboratory studies to genomic regions already related to prostate cancer by other scientific methods. We have developed a database of prostate cancer related chromosomal information from the existing biomedical literature. The input material was based on a broad literature search with subsequent hand annotation of information relevant to prostate cancer.DescriptionThe database was then analyzed for identifiable trends in the whole scale literature. We have used this database, named ChromSorter PC, to present graphical summaries of chromosomal regions associated with prostate cancer broken down by age, ethnicity and experimental method. In addition we have placed the database information on the human genome using the Generic Genome Browser tool that allows the visualization of the data with respect to user generated datasets.ConclusionsWe have used this database as an additional dataset for the filtering of genes identified through genetics and genomics studies as warranting follow-up validation studies. We would like to make this dataset publicly available for use by other groups. Using the Genome Browser allows for the graphical analysis of the associated data . Additional material from the database can be obtained by contacting the authors (mdatta@mcw.edu).
Highlights
BackgroundThe biomedical literature is an incredibly rich resource for researchers. Information obtained from previous scientific studies helps researchers focus their own efforts
Our increasing use of genetic and genomic strategies to understand human prostate cancer means that we need access to simplified and integrated information present in the associated biomedical literature
We have used this database as an additional dataset for the filtering of genes identified through genetics and genomics studies as warranting follow-up validation studies
Summary
The biomedical literature is an incredibly rich resource for researchers. Information obtained from previous scientific studies helps researchers focus their own efforts. Graphical summaries of literature citations across four categories; Ethnicity, Age, Method and Chromosome are summarized in two ways: first by merely counting the number of times a region is identified, and second by adding the citation index score to determine the relative "significance" or importance of CFihgruormeo5somal citation data by ethnicity Chromosomal citation data by ethnicity. The general results are similar when the data is analyzed with respect to ethnicity, where chromosome 1 seems to have both the highest reference count and combined citation index score. On the combined citation index score chart, we find that chromosome 1 has the highest age-related score, meaning the largest number of references that studied specific age groups (figure 7). This was followed by chromosome 8 and chromosome X.
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