Quantitative assessment and validation of network inference methods in bioinformatics.

Untangling statistical and biological models to understand network inference: the need for a genomics network ontology. Front Genet (2014) 0.76

Creating, generating and comparing random network models with Network Randomizer. F1000Res (2016) 0.75

Local network-based measures to assess the inferability of different regulatory networks. IET Syst Biol (2010) 1.12

Current composite-feature classification methods do not outperform simple single-genes classifiers in breast cancer prognosis. Front Genet (2013) 0.99

Network Assessor: an automated method for quantitative assessment of a network's potential for gene function prediction. Front Genet (2014) 0.92

Genetic interaction networks: better understand to better predict. Front Genet (2013) 0.92

Validation of gene regulatory network inference based on controllability. Front Genet (2013) 0.87

On protocols and measures for the validation of supervised methods for the inference of biological networks. Front Genet (2013) 0.86

Experimental assessment of static and dynamic algorithms for gene regulation inference from time series expression data. Front Genet (2013) 0.84

B-cell lymphoma gene regulatory networks: biological consistency among inference methods. Front Genet (2013) 0.83

A bayesian framework that integrates heterogeneous data for inferring gene regulatory networks. Front Bioeng Biotechnol (2014) 0.83

Utility of network integrity methods in therapeutic target identification. Front Genet (2014) 0.82

Interactive exploration of integrated biological datasets using context-sensitive workflows. Front Genet (2014) 0.81

Joint conditional Gaussian graphical models with multiple sources of genomic data. Front Genet (2013) 0.81

Relevance of different prior knowledge sources for inferring gene interaction networks. Front Genet (2014) 0.80

Network statistics of genetically-driven gene co-expression modules in mouse crosses. Front Genet (2013) 0.80

Modular network construction using eQTL data: an analysis of computational costs and benefits. Front Genet (2014) 0.79

On the underlying assumptions of threshold Boolean networks as a model for genetic regulatory network behavior. Front Genet (2013) 0.78

Relevance of different prior knowledge sources for inferring gene interaction networks. Front Genet (2014) 0.80