RESUMO
The increasing size and complexity of high-throughput datasets pose a growing challenge for researchers. Often very different (cross-omics) techniques with individual data analysis pipelines are employed making a unified biomarker discovery strategy and a direct comparison of different experiments difficult and time consuming. Here we present the comprehensive web-based application ProfileDB. The application is designed to integrate data from different high-throughput 'omics' data types (Transcriptomics, Proteomics, Metabolomics) with clinical parameters and prior knowledge on pathways and ontologies. Beyond data storage, ProfileDB provides a set of dedicated tools for study inspection and data visualization. The user can gain insights into a complex experiment with just a few mouse clicks. We will demonstrate the application by presenting typical use cases for the identification of proteomics biomarkers. All presented analyses can be reproduced using the public ProfileDB web server. The ProfileDB application is available by standard browser (Firefox 18+, Internet Explorer Version 9+) technology via http://profileDB.-microdiscovery.de/ (login and pass-word: profileDB). The installation contains several public datasets including different cross-'omics' experiments. This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge.
Assuntos
Biomarcadores Tumorais/análise , Neoplasias da Mama/diagnóstico , Metabolômica , Proteínas de Neoplasias/análise , Proteômica , Software , Transcriptoma , Animais , Neoplasias da Mama/genética , Neoplasias da Mama/metabolismo , Bases de Dados Factuais , Feminino , Humanos , CamundongosRESUMO
BrainProfileDB is a database system for integrating large sets of high throughput functional genomics data of the Human Brain Proteome Project (HBPP). Within HBPP (http://www.smp-proteomics.de/) the molecular pathology of neurodegenerative diseases is investigated, using complementary methods from transcriptomics, proteomics, toponomics and interaction measurements. Aim of the database system is to provide a broad spectrum of scientific users joined in the consortium with a practical integrated view on their data. Employing appropriate mapping techniques and levels of data representation the user is relieved from technical details of gene identification or experimental measurement technique.
Assuntos
Encéfalo/metabolismo , Bases de Dados Genéticas , Genômica/métodos , Proteoma/análise , Proteômica/métodos , Biologia Computacional/métodos , Sistemas de Gerenciamento de Base de Dados , Humanos , Doenças Neurodegenerativas/genética , Doenças Neurodegenerativas/metabolismo , Doenças Neurodegenerativas/patologia , Proteoma/genéticaRESUMO
Personalized medicine is promising a revolution for medicine and human biology in the 21st century. The scientific foundation for this revolution is accomplished by analyzing biological high-throughput data sets from genomics, transcriptomics, proteomics, and metabolomics. Currently, access to these data has been limited to either rather simple Web-based tools, which do not grant much insight or analysis by trained specialists, without firsthand involvement of the physician. Here, we present the novel Web-based tool "BioMiner," which was developed within the scope of an international and interdisciplinary project (SYSTHER) and gives access to a variety of high-throughput data sets. It provides the user with convenient tools to analyze complex cross-omics data sets and grants enhanced visualization abilities. BioMiner incorporates transcriptomic and cross-omics high-throughput data sets, with a focus on cancer. A public instance of BioMiner along with the database is available at http://systherDB.microdiscovery.de/, login and password: "systher"; a tutorial detailing the usage of BioMiner can be found in the Supplementary File.