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Navigating the Mass Spectrometry-Based Proteomic Data Using Free Computational Tools
Published on: August 19, 2025
Guilt-By-Association feature selection applied to simulated proteomic data
Hyunjin Shin1, Bryan Sheu, Mia K Markey
1Department of Electrical and Computer Engineering, The University of Texas at Austin, TX, USA.
AMIA ... Annual Symposium Proceedings. AMIA Symposium
|June 17, 2006
Abstract:
We propose a new feature selection algorithm, Guilt-By-Association (GBA), which uses hierarchical clustering based on feature correlations to eliminate redundant features. GBA can be used in conjunction with other algorithms to produce a feature selection routine that explicitly considers both the similarities between features and their individual discriminatory powers. In this preliminary study, a simple form of GBA was investigated on simulated proteomic data.

