Maurice H. J. Selman

This paper introduces a cutoff selection algorithm for correlation networks that uses prior knowledge to improve network reconstruction, showing better performance than statistical cutoffs across multiple datasets.

The paper evaluates normalization methods for glycomics data by assessing how well they enable accurate reconstruction of known glycosylation pathway reactions using Gaussian Graphical Models.