ProbFAST: Probabilistic Functional Analysis System Tool

Background  

The post-genomic era has brought new challenges regarding the understanding of the organization and function of the human genome. Many of these challenges are centered on the meaning of differential gene regulation under distinct biological conditions and can be performed by analyzing the Multiple Differential Expression (MDE) of genes associated with normal and abnormal biological processes. Currently MDE analyses are limited to usual methods of differential expression initially designed for paired analysis.     

BayGO: Bayesian analysis of ontology term enrichment in microarray data

Background  

The search for enriched (aka over-represented or enhanced) ontology terms in a list of genes obtained from microarray experiments is becoming a standard procedure for a system-level analysis. This procedure tries to summarize the information focussing on classification designs such as Gene Ontology, KEGG pathways, and so on, instead of focussing on individual genes. Although it is well known in statistics that association and significance are distinct concepts, only the former approach has been used to deal with the ontology term enrichment problem.     

ProbCD: enrichment analysis accounting for categorization uncertainty

Background  

As in many other areas of science, systems biology makes extensive use of statistical association and significance estimates in contingency tables, a type of categorical data analysis known in this field as enrichment (also over-representation or enhancement) analysis. In spite of efforts to create probabilistic annotations, especially in the Gene Ontology context, or to deal with uncertainty in high throughput-based datasets, current enrichment methods largely ignore this probabilistic information since they are mainly based on variants of the Fisher Exact Test.     

Rapid and sensitive static headspace gas chromatography-mass spectrometry method for the analysis of ethanol and abused inhalants in blood

A sensitive and specific method using static headspace gas chromatography coupled with mass spectrometry (GC/MS) has been developed for the quantitative determination of ethanol in biological fluids using n-propanol as internal standard. Gas chromatography was performed in isothermal mode with a GC run time of 2.6 min. The quantification was performed using scan mode abstracting a quantitative ion and a qualifier ion for ethanol and for the internal standard. The method was linear (r(2), 0.999, in the concentration range of 5-200 mg/dl), specific (no interference from methanol acetaldehyde, acetone or from endogenous materials), sensitive (limit of quantification and limit of detection of 0.2 and 0.02 mg/dl, respectively) and robust (less than 5% inter- and intra-assay coefficient of variation). A slightly modified method was also developed for the quantification of five commonly abused inhalants (dichloromethane, ethyl acetate, benzene, toluene and xylene) in blood. The method used a gradient GC program with a run time of 8 min. The quantification was performed using scan mode and integrating the area under the peak using trichloroethane as an internal standard. Without optimization, the method was linear (from 5 to 100 mg/l) and sensitive.