Structure-energy-based predictions and network modelling of RASopathy and cancer missense mutations
about
RASopathies: unraveling mechanisms with animal modelsPersonalized respiratory medicine: exploring the horizon, addressing the issues. Summary of a BRN-AJRCCM workshop held in Barcelona on June 12, 2014How do oncoprotein mutations rewire protein-protein interaction networks?Solubis: a webserver to reduce protein aggregation through mutationFunctional consequences of somatic mutations in cancer using protein pocket-based prioritization approach.Structure-based predictions broadly link transcription factor mutations to gene expression changes in cancers.Predicting the impact of Lynch syndrome-causing missense mutations from structural calculationsPhospho-proteomic analyses of B-Raf protein complexes reveal new regulatory principles.In vivo severity ranking of Ras pathway mutations associated with developmental disorders.The yin-yang of kinase activation and unfolding explains the peculiarity of Val600 in the activation segment of BRAF.Docking-based modeling of protein-protein interfaces for extensive structural and functional characterization of missense mutations.Modeling of RAS complexes supports roles in cancer for less studied partners.RASopathies: Presentation at the Genome, Interactome, and Phenome Levels.Modeling Binding Affinity of Pathological Mutations for Computational Protein Design.RAS ubiquitylation modulates effector interactions.Blocking protein quality control to counter hereditary cancers.HIV-1 Uncoating and Reverse Transcription Require eEF1A Binding to Surface-Exposed Acidic Residues of the Reverse Transcriptase Thumb Domain.New insights into RAS biology reinvigorate interest in mathematical modeling of RAS signaling.Clinical characteristics and spectrum of NF1 mutations in 12 unrelated Chinese families with neurofibromatosis type 1.Quantitative Systems Pharmacology Analysis of KRAS G12C Covalent Inhibitors.From mutations to mechanisms and dysfunction via computation and mining of protein energy landscapes
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P2860
Structure-energy-based predictions and network modelling of RASopathy and cancer missense mutations
description
2014 nî lūn-bûn
@nan
2014 թուականի Մայիսին հրատարակուած գիտական յօդուած
@hyw
2014 թվականի մայիսին հրատարակված գիտական հոդված
@hy
2014年の論文
@ja
2014年論文
@yue
2014年論文
@zh-hant
2014年論文
@zh-hk
2014年論文
@zh-mo
2014年論文
@zh-tw
2014年论文
@wuu
name
Structure-energy-based predict ...... and cancer missense mutations
@ast
Structure-energy-based predict ...... and cancer missense mutations
@en
Structure-energy-based predict ...... and cancer missense mutations
@nl
type
label
Structure-energy-based predict ...... and cancer missense mutations
@ast
Structure-energy-based predict ...... and cancer missense mutations
@en
Structure-energy-based predict ...... and cancer missense mutations
@nl
prefLabel
Structure-energy-based predict ...... and cancer missense mutations
@ast
Structure-energy-based predict ...... and cancer missense mutations
@en
Structure-energy-based predict ...... and cancer missense mutations
@nl
P2860
P356
P1476
Structure-energy-based predict ...... and cancer missense mutations
@en
P2093
Christina Kiel
Luis Serrano
P2860
P356
10.1002/MSB.20145092
P577
2014-05-06T00:00:00Z