Iis--integrated Interactome System: A Web-based Platform For The Annotation, Analysis And Visualization Of Protein-metabolite-gene-drug Interactions By Integrating A Variety Of Data Sources And Tools.

High-throughput screening of physical, genetic and chemical-genetic interactions brings important perspectives in the Systems Biology field, as the analysis of these interactions provides new insights into protein/gene function, cellular metabolic variations and the validation of therapeutic targets and drug design. However, such analysis depends on a pipeline connecting different tools that can automatically integrate data from diverse sources and result in a more comprehensive dataset that can be properly interpreted. We describe here the Integrated Interactome System (IIS), an integrative platform with a web-based interface for the annotation, analysis and visualization of the interaction profiles of proteins/genes, metabolites and drugs of interest. IIS works in four connected modules: (i) Submission module, which receives raw data derived from Sanger sequencing (e.g. two-hybrid system); (ii) Search module, which enables the user to search for the processed reads to be assembled into contigs/singlets, or for lists of proteins/genes, metabolites and drugs of interest, and add them to the project; (iii) Annotation module, which assigns annotations from several databases for the contigs/singlets or lists of proteins/genes, generating tables with automatic annotation that can be manually curated; and (iv) Interactome module, which maps the contigs/singlets or the uploaded lists to entries in our integrated database, building networks that gather novel identified interactions, protein and metabolite expression/concentration levels, subcellular localization and computed topological metrics, GO biological processes and KEGG pathways enrichment. This module generates a XGMML file that can be imported into Cytoscape or be visualized directly on the web. We have developed IIS by the integration of diverse databases following the need of appropriate tools for a systematic analysis of physical, genetic and chemical-genetic interactions. IIS was validated with yeast two-hybrid, proteomics and metabolomics datasets, but it is also extendable to other datasets. IIS is freely available online at: http://www.lge.ibi.unicamp.br/lnbio/IIS/.

Correlation Between The Friedman Staging System And The Upper Airway Volume In Patients With Obstructive Sleep Apnea.

This study was designed to evaluate the correlation between computed tomography findings and data from the physical examination and the Friedman Staging System (FSS) in patients with obstructive sleep apnea (OSA). We performed a retrospective evaluation by reviewing the medical records of 33 patients (19 male and 14 female patients) with a mean body mass index of 30.38 kg/m(2) and mean age of 49.35 years. Among these patients, 14 presented with severe OSA, 7 had moderate OSA, 7 had mild OSA, and 5 were healthy. The patients were divided into 2 groups according to the FSS: Group A comprised patients with FSS stage I or II, and group B comprised patients with FSS stage III. By use of the Fisher exact test, a positive relationship between the FSS stage and apnea-hypopnea index (P = .011) and between the FSS stage and body mass index (P = .012) was found. There was no correlation between age (P = .55) and gender (P = .53) with the FSS stage. The analysis of variance test comparing the upper airway volume between the 2 groups showed P = .018. In this sample the FSS and upper airway volume showed an inverse correlation and were useful in analyzing the mechanisms of airway collapse in patients with OSA.