Gene Regulatory Networks

Predictability of human differential gene expression

Differential expression (DE) is commonly used to explore molecular mechanisms of biological conditions. While many studies report significant results between their groups of interest, the degree to which results are specific to the question at hand …

EGAD: ultra-fast functional analysis of gene networks

Summary: Evaluating gene networks with respect to known biology is a common task but often a computationally costly one. Many computational experiments are difficult to apply exhaustively in network analysis due to run-times. To permit …

Exploiting single-cell expression to characterize co-expression replicability

BACKGROUND: Co-expression networks have been a useful tool for functional genomics, providing important clues about the cellular and biochemical mechanisms that are active in normal and disease processes. However, co-expression analysis is often …

Ligand Similarity Complements Sequence, Physical Interaction, and Co-Expression for Gene Function Prediction

The expansion of protein-ligand annotation databases has enabled large-scale networking of proteins by ligand similarity. These ligand-based protein networks, which implicitly predict the ability of neighboring proteins to bind related ligands, may …

Positive and negative forms of replicability in gene network analysis

MOTIVATION: Gene networks have become a central tool in the analysis of genomic data but are widely regarded as hard to interpret. This has motivated a great deal of comparative evaluation and research into best practices. We explore the possibility …

Guidance for RNA-seq co-expression network construction and analysis: safety in numbers

MOTIVATION: RNA-seq co-expression analysis is in its infancy and reasonable practices remain poorly defined. We assessed a variety of RNA-seq expression data to determine factors affecting functional connectivity and topology in co-expression …

Measuring the wisdom of the crowds in network-based gene function inference

MOTIVATION: Network-based gene function inference methods have proliferated in recent years, but measurable progress remains elusive. We wished to better explore performance trends by controlling data and algorithm implementation, with a particular …

Comparison of automated candidate gene prediction systems using genes implicated in type 2 diabetes by genome-wide association studies

BACKGROUND: Automated candidate gene prediction systems allow geneticists to hone in on disease genes more rapidly by identifying the most probable candidate genes linked to the disease phenotypes under investigation. Here we assessed the ability of …