GenCLiP: A Tool for Clustering Gene Lists by Literature Profiling
Author Information
Author(s): Huang Zhong-Xi, Tian Hui-Yong, Hu Zhen-Fu, Zhou Yi-Bo, Zhao Jin, Yao Kai-Tai
Primary Institution: Southern Medical University
Hypothesis
Can GenCLiP effectively identify functional clusters of genes related to specific keywords through literature profiling?
Conclusion
GenCLiP allows researchers to quickly identify pathways involving abnormally expressed genes related to keloids.
Supporting Evidence
- GenCLiP was used to analyze a list of 247 differentially expressed genes.
- The program identified 41 curated keywords related to keloid pathogenesis.
- The probability of finding keloid-related genes among the analyzed genes was significantly low, indicating a non-random association.
Takeaway
GenCLiP is a computer program that helps scientists find groups of genes related to diseases by looking at research papers.
Methodology
GenCLiP clusters genes based on literature profiling and allows manual curation of keywords.
Potential Biases
Some pathways inferred may already be well established, which could lead to trivial findings.
Limitations
The process of literature retrieval and keyword extraction can be time-consuming.
Statistical Information
P-Value
0.00003
Statistical Significance
p<0.05
Digital Object Identifier (DOI)
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