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What is Evaluating Gene Regulatory Network Inference about?

This document summarizes and compares different methods for inferring gene regulatory networks from gene expression data. It finds that unsupervised methods generally have low prediction accuracy, except for the Z-SCORE method on knockout data. Supervised methods, which use known interaction data for training, achieve the highest accuracy. Even semi-supervised methods, which require only a small number of known positive samples, outperform unsupervised techniques. The document provides a comprehensive evalu

Author

Jagat Rath

Language

EN