CN: a consensus algorithm for inferring gene regulatory networks using the SORDER algorithm and conditional mutual information test

A model comparison study of the flowering time regulatory network in Arabidopsis

(2014) Charles CN Wang et al.   BMC Systems Biology

IPCA-CMI: An Algorithm for Inferring Gene Regulatory Networks based on a Combination of PCA-CMI and MIT Score

(2014) Rosa Aghdam et al.   PLoS One

Learning high-dimensional directed acyclic graphs with latent and selection variables

(2012) Diego Colombo et al.   ANNALS OF STATISTICS

NARROMI: a noise and redundancy reduction technique improves accuracy of gene regulatory network inference

(2012) Xiujun Zhang et al.   BIOINFORMATICS

Identification of context-specific gene regulatory networks with GEMULA—gene expression modeling using LAsso

(2011) Geert Geeven et al.   BIOINFORMATICS

Inferring gene regulatory networks from gene expression data by path consistency algorithm based on conditional mutual information

(2011) Xiujun Zhang et al.   BIOINFORMATICS

Gene regulatory networks and the role of robustness and stochasticity in the control of gene expression

(2011) L. T. MacNeil et al.   GENOME RESEARCH

Gene Regulatory Network Reconstruction Using Bayesian Networks, the Dantzig Selector, the Lasso and Their Meta-Analysis

(2011) Matthieu Vignes et al.   PLoS One

TimeDelay-ARACNE: Reverse engineering of gene networks from time-course data by an information theoretic approach

(2010) Pietro Zoppoli et al.   BMC BIOINFORMATICS

A Top-Performing Algorithm for the DREAM3 Gene Expression Prediction Challenge

(2010) Jianhua Ruan   PLoS One

DREAM3: Network Inference Using Dynamic Context Likelihood of Relatedness and the Inferelator

(2010) Aviv Madar et al.   PLoS One

Towards a Rigorous Assessment of Systems Biology Models: The DREAM3 Challenges

(2010) Robert J. Prill et al.   PLoS One

Inferring Regulatory Networks from Expression Data Using Tree-Based Methods

(2010) Vân Anh Huynh-Thu et al.   PLoS One

Revealing strengths and weaknesses of methods for gene network inference

(2010) D. Marbach et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Lessons from the DREAM2 Challenges

(2009) Gustavo Stolovitzky et al.   Annals of the New York Academy of Sciences

Generating Realistic In Silico Gene Networks for Performance Assessment of Reverse Engineering Methods

(2009) Daniel Marbach et al.   JOURNAL OF COMPUTATIONAL BIOLOGY

On the completeness of orientation rules for causal discovery in the presence of latent confounders and selection bias

(2008) Jiji Zhang   ARTIFICIAL INTELLIGENCE