Inferring Pathway Activity toward Precise Disease Classification
Korea Institute of Brain Science · Korea Advanced Institute of Science and Technology · +3 more institutions
Abstract
The advent of microarray technology has made it possible to classify disease states based on gene expression profiles of patients. Typically, marker genes are selected by measuring the power of their expression profiles to discriminate among patients of different disease states. However, expression-based classification can be challenging in complex diseases due to factors such as cellular heterogeneity within a tissue sample and genetic heterogeneity across patients. A promising technique for coping with these challenges is to incorporate pathway information into the disease classification procedure in order to classify disease based on the activity of entire signaling pathways or protein complexes rather than…
Citation impact
- FWCI
- 10.67
- Percentile
- 100%
- References
- 45
Authors
5- ELEunjung Lee
Korea Institute of Brain Science, Korea Advanced Institute of Science and Technology
- HCHan‐Yu Chuang
University of California, San Diego
- JKJong‐Won Kim
Samsung Medical Center, Sungkyunkwan University
- TITrey IdekerCorresponding
University of California, San Diego
- DLDoheon LeeCorresponding
Korea Institute of Brain Science, Korea Advanced Institute of Science and Technology
Topics & keywords
- Computational biology
- Subtyping
- Phenotype
- Disease
- Biology
- Gene
- Gene expression
- Discriminative model
- Reduced inequalities