Statistics – Machine Learning
Scientific paper
2010-04-08
Statistics
Machine Learning
Scientific paper
The outcome of a functional genomics pipeline is usually a partial list of genomic features, ranked by their relevance in modelling biological phenotype in terms of a classification or regression model. Due to resampling protocols or just within a meta-analysis comparison, instead of one list it is often the case that sets of alternative feature lists (possibly of different lengths) are obtained. Here we introduce a method, based on the algebraic theory of symmetric groups, for studying the variability between lists ("list stability") in the case of lists of unequal length. We provide algorithms evaluating stability for lists embedded in the full feature set or just limited to the features occurring in the partial lists. The method is demonstrated first on synthetic data in a gene filtering task and then for finding gene profiles on a recent prostate cancer dataset.
Furlanello Cesare
Jurman Giuseppe
Riccadonna Samantha
Visintainer Roberto
No associations
LandOfFree
Algebraic Comparison of Partial Lists in Bioinformatics does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Algebraic Comparison of Partial Lists in Bioinformatics, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Algebraic Comparison of Partial Lists in Bioinformatics will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-713389