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1.
BMC Syst Biol ; 5: 20, 2011 Jan 31.
Artigo em Inglês | MEDLINE | ID: mdl-21276275

RESUMO

BACKGROUND: Recent advances in genomic sequencing have enabled the use of genome sequencing in standard biological and biotechnological research projects. The challenge is how to integrate the large amount of data in order to gain novel biological insights. One way to leverage sequence data is to use genome-scale metabolic models. We have therefore designed and implemented a bioinformatics platform which supports the development of such metabolic models. RESULTS: MEMOSys (MEtabolic MOdel research and development System) is a versatile platform for the management, storage, and development of genome-scale metabolic models. It supports the development of new models by providing a built-in version control system which offers access to the complete developmental history. Moreover, the integrated web board, the authorization system, and the definition of user roles allow collaborations across departments and institutions. Research on existing models is facilitated by a search system, references to external databases, and a feature-rich comparison mechanism. MEMOSys provides customizable data exchange mechanisms using the SBML format to enable analysis in external tools. The web application is based on the Java EE framework and offers an intuitive user interface. It currently contains six annotated microbial metabolic models. CONCLUSIONS: We have developed a web-based system designed to provide researchers a novel application facilitating the management and development of metabolic models. The system is freely available at http://www.icbi.at/MEMOSys.


Assuntos
Biologia Computacional/métodos , Genômica/métodos , Redes e Vias Metabólicas/genética , Modelos Biológicos , Software
2.
BMC Bioinformatics ; 10: 268, 2009 Aug 27.
Artigo em Inglês | MEDLINE | ID: mdl-19712446

RESUMO

BACKGROUND: Since its introduction quantitative real-time polymerase chain reaction (qPCR) has become the standard method for quantification of gene expression. Its high sensitivity, large dynamic range, and accuracy led to the development of numerous applications with an increasing number of samples to be analyzed. Data analysis consists of a number of steps, which have to be carried out in several different applications. Currently, no single tool is available which incorporates storage, management, and multiple methods covering the complete analysis pipeline. RESULTS: QPCR is a versatile web-based Java application that allows to store, manage, and analyze data from relative quantification qPCR experiments. It comprises a parser to import generated data from qPCR instruments and includes a variety of analysis methods to calculate cycle-threshold and amplification efficiency values. The analysis pipeline includes technical and biological replicate handling, incorporation of sample or gene specific efficiency, normalization using single or multiple reference genes, inter-run calibration, and fold change calculation. Moreover, the application supports assessment of error propagation throughout all analysis steps and allows conducting statistical tests on biological replicates. Results can be visualized in customizable charts and exported for further investigation. CONCLUSION: We have developed a web-based system designed to enhance and facilitate the analysis of qPCR experiments. It covers the complete analysis workflow combining parsing, analysis, and generation of charts into one single application. The system is freely available at http://genome.tugraz.at/QPCR.


Assuntos
Biologia Computacional/métodos , Sistemas de Gerenciamento de Base de Dados , Reação em Cadeia da Polimerase/métodos , Software , Algoritmos , Bases de Dados Genéticas , Interface Usuário-Computador
3.
Am Fam Physician ; 79(8): 657-65, 2009 Apr 15.
Artigo em Inglês | MEDLINE | ID: mdl-19405409

RESUMO

Symptoms of childhood attention-deficit/hyperactivity disorder affect cognitive, academic, behavioral, emotional, social, and developmental functioning. Attention-deficit/hyperactivity disorder is the most commonly diagnosed neurodevelopmental disorder in children and adolescents. An estimated 2 to 16 percent of school-aged children have been diagnosed with the disorder. The prevalence of attention-deficit/hyperactivity disorder in the primary care setting is similar to that in the general community, depending on the diagnostic criteria and population studied. The causality of attention-deficit/hyperactivity disorder is relatively unknown. Most recent studies focus on the role of dopamine; norepinephrine; and, most recently, serotonin neurotransmitters. The disorder is classified into three general subtypes: predominantly hyperactive-impulsive, predominantly inattentive, and combined. Screening tools and rating scales have been devised to assist with the diagnosis. Appropriate treatment can dramatically improve the function and quality of life of the patient and family. Pharmacologic treatment includes stimulants, such as methylphenidate and mixed amphetamine salts, or nonstimulants, such as atomoxetine. Behavioral approaches, particularly those that reward desirable behavior, are also effective. A combination of pharmacologic and behavioral therapies is recommended.


Assuntos
Transtorno do Deficit de Atenção com Hiperatividade/diagnóstico , Transtorno do Deficit de Atenção com Hiperatividade/terapia , Adolescente , Transtorno do Deficit de Atenção com Hiperatividade/psicologia , Terapia Comportamental , Estimulantes do Sistema Nervoso Central/uso terapêutico , Criança , Terapia Combinada , Humanos , Neurotransmissores/uso terapêutico
4.
BMC Bioinformatics ; 10: 32, 2009 Jan 24.
Artigo em Inglês | MEDLINE | ID: mdl-19166624

RESUMO

BACKGROUND: Structural data from crystallographic analyses contain a vast amount of information on protein-protein contacts. Knowledge on protein-protein interactions is essential for understanding many processes in living cells. The methods to investigate these interactions range from genetics to biophysics, crystallography, bioinformatics and computer modeling. Also crystal contact information can be useful to understand biologically relevant protein oligomerisation as they rely in principle on the same physico-chemical interaction forces. Visualization of crystal and biological contact data including different surface properties can help to analyse protein-protein interactions. RESULTS: VASCo is a program package for the calculation of protein surface properties and the visualization of annotated surfaces. Special emphasis is laid on protein-protein interactions, which are calculated based on surface point distances. The same approach is used to compare surfaces of two aligned molecules. Molecular properties such as electrostatic potential or hydrophobicity are mapped onto these surface points. Molecular surfaces and the corresponding properties are calculated using well established programs integrated into the package, as well as using custom developed programs. The modular package can easily be extended to include new properties for annotation. The output of the program is most conveniently displayed in PyMOL using a custom-made plug-in. CONCLUSION: VASCo supplements other available protein contact visualisation tools and provides additional information on biological interactions as well as on crystal contacts. The tool provides a unique feature to compare surfaces of two aligned molecules based on point distances and thereby facilitates the visualization and analysis of surface differences.


Assuntos
Proteínas/química , Software , Sítios de Ligação , Bases de Dados de Proteínas , Interações Hidrofóbicas e Hidrofílicas , Modelos Moleculares , Conformação Proteica
5.
BMC Bioinformatics ; 8: 197, 2007 Jun 13.
Artigo em Inglês | MEDLINE | ID: mdl-17567892

RESUMO

BACKGROUND: The advancements of proteomics technologies have led to a rapid increase in the number, size and rate at which datasets are generated. Managing and extracting valuable information from such datasets requires the use of data management platforms and computational approaches. RESULTS: We have developed the MAss SPECTRometry Analysis System (MASPECTRAS), a platform for management and analysis of proteomics LC-MS/MS data. MASPECTRAS is based on the Proteome Experimental Data Repository (PEDRo) relational database schema and follows the guidelines of the Proteomics Standards Initiative (PSI). Analysis modules include: 1) import and parsing of the results from the search engines SEQUEST, Mascot, Spectrum Mill, X! Tandem, and OMSSA; 2) peptide validation, 3) clustering of proteins based on Markov Clustering and multiple alignments; and 4) quantification using the Automated Statistical Analysis of Protein Abundance Ratios algorithm (ASAPRatio). The system provides customizable data retrieval and visualization tools, as well as export to PRoteomics IDEntifications public repository (PRIDE). MASPECTRAS is freely available at http://genome.tugraz.at/maspectras CONCLUSION: Given the unique features and the flexibility due to the use of standard software technology, our platform represents significant advance and could be of great interest to the proteomics community.


Assuntos
Cromatografia Líquida/métodos , Sistemas de Gerenciamento de Base de Dados , Bases de Dados de Proteínas , Espectrometria de Massas/métodos , Mapeamento de Peptídeos/métodos , Proteoma/química , Software , Sequência de Aminoácidos , Armazenamento e Recuperação da Informação/métodos , Dados de Sequência Molecular , Proteoma/metabolismo , Análise de Sequência de Proteína/métodos , Design de Software , Integração de Sistemas , Interface Usuário-Computador
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