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Large-scale gene function analysis with the PANTHER classification system.
Mi, Huaiyu; Muruganujan, Anushya; Casagrande, John T; Thomas, Paul D.
Afiliação
  • Mi H; Department of Preventive Medicine, Division of Bioinformatics, Keck School of Medicine, University of Southern California, Los Angeles, California, USA. huaiyumi@usc.edu
Nat Protoc ; 8(8): 1551-66, 2013 Aug.
Article em En | MEDLINE | ID: mdl-23868073
ABSTRACT
The PANTHER (protein annotation through evolutionary relationship) classification system (http//www.pantherdb.org/) is a comprehensive system that combines gene function, ontology, pathways and statistical analysis tools that enable biologists to analyze large-scale, genome-wide data from sequencing, proteomics or gene expression experiments. The system is built with 82 complete genomes organized into gene families and subfamilies, and their evolutionary relationships are captured in phylogenetic trees, multiple sequence alignments and statistical models (hidden Markov models or HMMs). Genes are classified according to their function in several different ways families and subfamilies are annotated with ontology terms (Gene Ontology (GO) and PANTHER protein class), and sequences are assigned to PANTHER pathways. The PANTHER website includes a suite of tools that enable users to browse and query gene functions, and to analyze large-scale experimental data with a number of statistical tests. It is widely used by bench scientists, bioinformaticians, computer scientists and systems biologists. In the 2013 release of PANTHER (v.8.0), in addition to an update of the data content, we redesigned the website interface to improve both user experience and the system's analytical capability. This protocol provides a detailed description of how to analyze genome-wide experimental data with the PANTHER classification system.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Filogenia / Software / Proteínas / Anotação de Sequência Molecular Tipo de estudo: Risk_factors_studies Idioma: En Revista: Nat Protoc Ano de publicação: 2013 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Filogenia / Software / Proteínas / Anotação de Sequência Molecular Tipo de estudo: Risk_factors_studies Idioma: En Revista: Nat Protoc Ano de publicação: 2013 Tipo de documento: Article País de afiliação: Estados Unidos