Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
5138961 | Microchemical Journal | 2018 | 6 Pages |
Abstract
In this paper we present a method for evaluating the NOTEL based on anomaly detection: a classifier is built that discriminates between target class instances, i.e., normal cases, and anomalies, i.e., samples with significant transcriptional effects. The strength of this method is that (i) it can be applied to cases in which few samples are available and the space dimension is high and (ii) it makes use of the complete gene expression profiles.
Related Topics
Physical Sciences and Engineering
Chemistry
Analytical Chemistry
Authors
Daniele Quercioli, Andrea Roli, Elena Morandi, Stefania Perdichizzi, Laura Polacchini, Francesca Rotondo, Monica Vaccari, Marco Villani, Roberto Serra, Annamaria Colacci,