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1.
Nucleic Acids Res ; 44(W1): W98-W104, 2016 07 08.
Artigo em Inglês | MEDLINE | ID: mdl-27150809

RESUMO

We present KeyPathwayMinerWeb, the first online platform for de novo pathway enrichment analysis directly in the browser. Given a biological interaction network (e.g. protein-protein interactions) and a series of molecular profiles derived from one or multiple OMICS studies (gene expression, for instance), KeyPathwayMiner extracts connected sub-networks containing a high number of active or differentially regulated genes (proteins, metabolites) in the molecular profiles. The web interface at (http://keypathwayminer.compbio.sdu.dk) implements all core functionalities of the KeyPathwayMiner tool set such as data integration, input of background knowledge, batch runs for parameter optimization and visualization of extracted pathways. In addition to an intuitive web interface, we also implemented a RESTful API that now enables other online developers to integrate network enrichment as a web service into their own platforms.


Assuntos
Biologia Computacional/métodos , Redes Reguladoras de Genes , Proteína Huntingtina/genética , Doença de Huntington/genética , Interface Usuário-Computador , Estudos de Casos e Controles , Biologia Computacional/estatística & dados numéricos , Conjuntos de Dados como Assunto , Perfilação da Expressão Gênica , Regulação da Expressão Gênica , Humanos , Doença de Huntington/diagnóstico , Internet , Mapeamento de Interação de Proteínas
2.
F1000Res ; 5: 1531, 2016.
Artigo em Inglês | MEDLINE | ID: mdl-27540470

RESUMO

Identifying functional modules or novel active pathways, recently termed de novo pathway enrichment, is a computational systems biology challenge that has gained much attention during the last decade. Given a large biological interaction network, KeyPathwayMiner extracts connected subnetworks that are enriched for differentially active entities from a series of molecular profiles encoded as binary indicator matrices. Since interaction networks constantly evolve, an important question is how robust the extracted results are when the network is modified. We enable users to study this effect through several network perturbation techniques and over a range of perturbation degrees. In addition, users may now provide a gold-standard set to determine how enriched extracted pathways are with relevant genes compared to randomized versions of the original network.

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