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PhenUMA: a tool for integrating the biomedical relationships among genes and diseases.
Rodríguez-López, Rocío; Reyes-Palomares, Armando; Sánchez-Jiménez, Francisca; Medina, Miguel Ángel.
Afiliação
  • Rodríguez-López R; Departamento de Biología Molecular y Bioquímica, Universidad de Málaga, Andalucía Tech, Facultad de Ciencias, and IBIMA (Biomedical Research Institute of Málaga), Málaga, Spain. rorodriguez@uma.es.
  • Reyes-Palomares A; CIBER de Enfermedades Raras (CIBERER), E-29071, Málaga, Spain. rorodriguez@uma.es.
  • Sánchez-Jiménez F; Departamento de Biología Molecular y Bioquímica, Universidad de Málaga, Andalucía Tech, Facultad de Ciencias, and IBIMA (Biomedical Research Institute of Málaga), Málaga, Spain. armando@uma.es.
  • Medina MÁ; CIBER de Enfermedades Raras (CIBERER), E-29071, Málaga, Spain. armando@uma.es.
BMC Bioinformatics ; 15: 375, 2014 Nov 25.
Article em En | MEDLINE | ID: mdl-25420641
ABSTRACT

BACKGROUND:

Several types of genetic interactions in humans can be directly or indirectly associated with the causal effects of mutations. These interactions are usually based on their co-associations to biological processes, coexistence in cellular locations, coexpression in cell lines, physical interactions and so on. In addition, pathological processes can present similar phenotypes that have mutations either in the same genomic location or in different genomic regions. Therefore, integrative resources for all of these complex interactions can help us prioritize the relationships between genes and diseases that are most deserving to be studied by researchers and physicians.

RESULTS:

PhenUMA is a web application that displays biological networks using information from biomedical and biomolecular data repositories. One of its most innovative features is to combine the benefits of semantic similarity methods with the information taken from databases of genetic diseases and biological interactions. More specifically, this tool is useful in studying novel pathological relationships between functionally related genes, merging diseases into clusters that share specific phenotypes or finding diseases related to reported phenotypes.

CONCLUSIONS:

This framework builds, analyzes and visualizes networks based on both functional and phenotypic relationships. The integration of this information helps in the discovery of alternative pathological roles of genes, biological functions and diseases. PhenUMA represents an advancement toward the use of new technologies for genomics and personalized medicine.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Software / Doença / Bases de Dados Factuais / Internet / Genômica / Genes / Modelos Biológicos Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: BMC Bioinformatics Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2014 Tipo de documento: Article País de afiliação: Espanha

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Software / Doença / Bases de Dados Factuais / Internet / Genômica / Genes / Modelos Biológicos Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: BMC Bioinformatics Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2014 Tipo de documento: Article País de afiliação: Espanha