The development of integrative methods is one of the main challenges in bioinformatics.
Network-based methods for the analysis of multiple gene-centered datasets take into …

The advancement of high‐throughput measurement techniques has enabled rapid and cost‐
efficient generation of omics data. However, the analysis of omics data is complex because …

A relation exists between network proximity of molecular entities in interaction networks,
functional similarity and association with diseases. The identification of network regions …

Network propagation has been used as the state-of-the-art network analysis method which
can overcome the limitations of the existing methods. The area where network propagation …

Modeling networks for single samples can facilitate discoveries in biology that go beyond
those found when analyzing an “aggregate” network, ie, one that merges information across …

High-throughput '-omics' technologies have given rise to an increasing abundance of
genome-scale data detailing human biology at the molecular level. Although these datasets …

Diffusion Component Analysis: Unraveling Functional Topology in Biological Networks Page 1
Diffusion Component Analysis: Unraveling Functional Topology in Biological Networks …

Since the dawn of the post-genomic era a myriad of novel high-throughput technologies
have been developed that are capable of measuring thousands of biological molecules at …

Improved methods for integrated analysis of heterogeneous large-scale omic data are direly
needed. Here, we take a network-based approach to this challenge. Given two networks …

MicroRNAs (miRNAs) are small non-coding RNA molecules whose primary function is to
regulate the expression of gene products via hybridization to mRNA transcripts, resulting in …