Differential Expression
Selection of lists of genes (here gene can represent either a ‘real’ gene or a methylation locus or even surface antigen from cytometry experiments) differentially expressed over some contrasts of interest (e.g. sick vs healthy). This can be useful to discover specific biomarker for the disease under investigation.
Functional Analysis and Gene Set Enrichment Analysis
Characterization of list of genes taking advantage of the huge amount of on-line biological knowledge.
Class Discovery
Building of a classifier capable of predict unknown samples on the bases of the expression profiles of characterized samples.
Survival Analysis based on gene expression profiling
Using a Cox proportional hazard model, we aim to detect a list of significant covariates depicting the different survival profiles of collections of patients.
Integration of different sources of high-throughput data
Integration of different sources of high-throughput data in order to perform more robust and reliable downstream analysis. For example: train a classifier on a list of features based on both gene expression and methylation data.
The service is available for public entities, companies and interdisciplinary research groups. CBM offers competitive prices and fast execution. Rates and prices are available upon request.
The staff is at customer’s disposal to ensure that all expectations are met.
