Sentence examples for multiple functional networks from inspiring English sources

In this paper, we study how to integrate multiple functional networks for accurate protein function prediction and propose a method called MNet.

This paper presents a novel, alternative methodology of identifying multiple functional networks via sparse representation of whole-brain task-based fMRI signals.

Our extensive experimental results have shown that this novel methodology can uncover multiple functional networks that can be well characterized and interpreted in spatial, temporal and frequency domains based on current brain science knowledge.

A statistically more sophisticated analysis applying PCA to activation condition images also implicated multiple functional networks in a cognitive task [ 19].

Our aim was to confirm the connectivity pattern observed in the group analysis, establish its reproducibility within and among subjects and explore the involvement of multiple functional networks.

Indeed, recent experiments support the hypothesis that intersubject variance reflects recruitment of multiple functional networks involved in task execution [ 15, 18].

Following the framework of Mostafavi et al. (2008), our approach for predicting gene function from multiple networks consists of two steps: (i) it constructs a composite network from multiple functional association networks and (ii) it predicts gene function from a single composite network.

An important step in predicting gene function is the construction of a composite network from multiple functional association networks.

The approaches closest to those presented in this article are methods for integrating multiple functional association networks into one composite network with the goal of predicting gene function from the composite network.

Motivation: Many algorithms that integrate multiple functional association networks for predicting gene function construct a composite network as a weighted sum of the individual networks and then use the composite network to predict gene function.

High throughput techniques produce multiple functional association networks.