Link-based quantitative methods to identify differentially coexpressed genes and gene Pairs
Published 2011 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Link-based quantitative methods to identify differentially coexpressed genes and gene Pairs
Authors
Keywords
-
Journal
BMC BIOINFORMATICS
Volume 12, Issue 1, Pages 315
Publisher
Springer Nature
Online
2011-08-03
DOI
10.1186/1471-2105-12-315
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- DCGL: an R package for identifying differentially coexpressed genes and links from gene expression microarray data
- (2010) Bao-Hong Liu et al. BIOINFORMATICS
- From ‘differential expression’ to ‘differential networking’ – identification of dysfunctional regulatory networks in diseases
- (2010) Alberto de la Fuente TRENDS IN GENETICS
- Statistical methods for gene set co-expression analysis
- (2009) YounJeong Choi et al. BIOINFORMATICS
- Identifying set-wise differential co-expression in gene expression microarray data
- (2009) Sung Cho et al. BMC BIOINFORMATICS
- Dissecting the dynamics of dysregulation of cellular processes in mouse mammary gland tumor
- (2009) Wieslawa I Mentzen et al. BMC GENOMICS
- Signed weighted gene co-expression network analysis of transcriptional regulation in murine embryonic stem cells
- (2009) Mike J Mason et al. BMC GENOMICS
- Role for Kruppel-Like Factor 4 in Determining the Outcome of p53 Response to DNA Damage
- (2009) Q. Zhou et al. CANCER RESEARCH
- DBH2H: vertebrate head-to-head gene pairs annotated at genomic and post-genomic levels
- (2009) Hui Yu et al. Database-The Journal of Biological Databases and Curation
- A Differential Wiring Analysis of Expression Data Correctly Identifies the Gene Containing the Causal Mutation
- (2009) Nicholas J. Hudson et al. PLoS Computational Biology
- Aging Mice Show a Decreasing Correlation of Gene Expression within Genetic Modules
- (2009) Lucinda K. Southworth et al. PLoS Genetics
- Differential dependency network analysis to identify condition-specific topological changes in biological networks
- (2008) Bai Zhang et al. BIOINFORMATICS
- Association Testing of Novel Type 2 Diabetes Risk Alleles in the JAZF1, CDC123/CAMK1D, TSPAN8, THADA, ADAMTS9, and NOTCH2 Loci With Insulin Release, Insulin Sensitivity, and Obesity in a Population-Based Sample of 4,516 Glucose-Tolerant Middle-Aged Danes
- (2008) N. Grarup et al. DIABETES
- TGF-β-induced Foxp3 inhibits TH17 cell differentiation by antagonizing RORγt function
- (2008) Liang Zhou et al. NATURE
- Adaptations to Climate in Candidate Genes for Common Metabolic Disorders
- (2008) Angela M. Hancock et al. PLoS Genetics
- Type 2 diabetes: new genes, new understanding
- (2008) Inga Prokopenko et al. TRENDS IN GENETICS
Add your recorded webinar
Do you already have a recorded webinar? Grow your audience and get more views by easily listing your recording on Peeref.
Upload NowAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started