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'Multi-omic' data analysis using O-miner.
Sangaralingam, Ajanthah; Dayem Ullah, Abu Z; Marzec, Jacek; Gadaleta, Emanuela; Nagano, Ai; Ross-Adams, Helen; Wang, Jun; Lemoine, Nicholas R; Chelala, Claude.
Afiliação
  • Sangaralingam A; Barts Cancer Institute, Queen Mary University of London.
  • Dayem Ullah AZ; Barts Cancer Institute, Queen Mary University of London.
  • Marzec J; Barts Cancer Institute, Queen Mary University of London.
  • Gadaleta E; Barts Cancer Institute, Queen Mary University of London.
  • Nagano A; Barts Cancer Institute, Queen Mary University of London.
  • Ross-Adams H; Barts Cancer Institute, Queen Mary University of London.
  • Wang J; Barts Cancer Institute, Queen Mary University of London.
  • Lemoine NR; Barts Cancer Institute, Queen Mary University of London.
  • Chelala C; Barts Cancer Institute, co-Lead of the Computational Biology Centre at the Life Science Initiative, Queen Mary University of London.
Brief Bioinform ; 20(1): 130-143, 2019 01 18.
Article em En | MEDLINE | ID: mdl-28981577
ABSTRACT
Innovations in -omics technologies have driven advances in biomedical research. However, integrating and analysing the large volumes of data generated from different high-throughput -omics technologies remain a significant challenge to basic and clinical scientists without bioinformatics skills or access to bioinformatics support. To address this demand, we have significantly updated our previous O-miner analytical suite, to incorporate several new features and data types to provide an efficient and easy-to-use Web tool for the automated analysis of data from '-omics' technologies. Created from a biologist's perspective, this tool allows for the automated analysis of large and complex transcriptomic, genomic and methylomic data sets, together with biological/clinical information, to identify significantly altered pathways and prioritize novel biomarkers/targets for biological validation. Our resource can be used to analyse both in-house data and the huge amount of publicly available information from array and sequencing platforms. Multiple data sets can be easily combined, allowing for meta-analyses. Here, we describe the analytical pipelines currently available in O-miner and present examples of use to demonstrate its utility and relevance in maximizing research output. O-miner Web server is free to use and is available at http//www.o-miner.org.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Software / Genômica / Análise de Dados Limite: Humans Idioma: En Revista: Brief Bioinform Assunto da revista: BIOLOGIA / INFORMATICA MEDICA Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Software / Genômica / Análise de Dados Limite: Humans Idioma: En Revista: Brief Bioinform Assunto da revista: BIOLOGIA / INFORMATICA MEDICA Ano de publicação: 2019 Tipo de documento: Article