Microarray gene expression profiling analysis combined with bioinformatics in multiple sclerosis

Link-based quantitative methods to identify differentially coexpressed genes and gene Pairs

(2011) Hui Yu et al.   BMC BIOINFORMATICS

Association of NCF2, IKZF1, IRF8, IFIH1, and TYK2 with Systemic Lupus Erythematosus

(2011) Deborah S. Cunninghame Graham et al.   PLoS Genetics

DCGL: an R package for identifying differentially coexpressed genes and links from gene expression microarray data

(2010) Bao-Hong Liu et al.   BIOINFORMATICS

Regulatory impact factors: unraveling the transcriptional regulation of complex traits from expression data

(2010) Antonio Reverter et al.   BIOINFORMATICS

From ‘differential expression’ to ‘differential networking’ – identification of dysfunctional regulatory networks in diseases

(2010) Alberto de la Fuente   TRENDS IN GENETICS

Pathway and network-based analysis of genome-wide association studies in multiple sclerosis

(2009) S. E. Baranzini et al.   HUMAN MOLECULAR GENETICS

Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources

(2009) Da Wei Huang et al.   Nature Protocols

Multiple sclerosis

(2008) Alastair Compston et al.   LANCET