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Pathway perturbations in signaling networks: Linking genotype to phenotype.
Li, Yongsheng; McGrail, Daniel J; Latysheva, Natasha; Yi, Song; Babu, M Madan; Sahni, Nidhi.
Afiliação
  • Li Y; Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.
  • McGrail DJ; Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.
  • Latysheva N; Medical Research Council Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge, CB2 0QH, UK.
  • Yi S; Department of Oncology, Dell Medical School, The University of Texas at Austin, Austin, TX, 78712, USA. Electronic address: stephen.yi@austin.utexas.edu.
  • Babu MM; Medical Research Council Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge, CB2 0QH, UK. Electronic address: madanm@mrc-lmb.cam.ac.uk.
  • Sahni N; Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA; Program in Quantitative and Computational Biosciences, Baylor College of Medicine, Houston, TX, 77030, USA; Department of Bioinformatics and Computational Biology, The University of Texas MD An
Semin Cell Dev Biol ; 99: 3-11, 2020 03.
Article em En | MEDLINE | ID: mdl-29738884
Genes and gene products interact with each other to form signal transduction networks in the cell. The interactome networks are under intricate regulation in physiological conditions, but could go awry upon genome instability caused by genetic mutations. In the past decade with next-generation sequencing technologies, an increasing number of genomic mutations have been identified in a variety of disease patients and healthy individuals. As functional and systematic studies on these mutations leap forward, they begin to reveal insights into cellular homeostasis and disease mechanisms. In this review, we discuss recent advances in the field of network biology and signaling pathway perturbations upon genomic changes, and highlight the success of various omics datasets in unraveling genotype-to-phenotype relationships.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Fenótipo / Transdução de Sinais / Genótipo Limite: Animals / Humans Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Fenótipo / Transdução de Sinais / Genótipo Limite: Animals / Humans Idioma: En Ano de publicação: 2020 Tipo de documento: Article